From 855934c3f3c5da7463790b5975a2b93938907c9c Mon Sep 17 00:00:00 2001 From: Adam Taranto Date: Thu, 12 Dec 2024 17:26:29 +1100 Subject: [PATCH 01/73] rm old releases --- code/flexidot_v1.00.py | 3129 ------------------------------------ code/flexidot_v1.01.py | 3153 ------------------------------------- code/flexidot_v1.02.py | 3177 ------------------------------------- code/flexidot_v1.03.py | 3161 ------------------------------------- code/flexidot_v1.04.py | 3325 --------------------------------------- code/flexidot_v1.05.py | 3390 --------------------------------------- code/flexidot_v1.06.py | 3403 ---------------------------------------- 7 files changed, 22738 deletions(-) delete mode 100644 code/flexidot_v1.00.py delete mode 100644 code/flexidot_v1.01.py delete mode 100644 code/flexidot_v1.02.py delete mode 100644 code/flexidot_v1.03.py delete mode 100644 code/flexidot_v1.04.py delete mode 100644 code/flexidot_v1.05.py delete mode 100644 code/flexidot_v1.06.py diff --git a/code/flexidot_v1.00.py b/code/flexidot_v1.00.py deleted file mode 100644 index 299780e..0000000 --- a/code/flexidot_v1.00.py +++ /dev/null @@ -1,3129 +0,0 @@ -#!/usr/bin/python2.7 -#!/usr/bin/python2.7 -# -*- coding: utf-8 -*- - -""" -FlexiDot: Highly customizable ambiguity-aware dotplots for visual sequence investigation - -Kathrin M. Seibt, Thomas Schmidt and Tony Heitkam -Institute of Botany, TU Dresden, Dresden, 01277, Germany - -(2018) - -version 1.0 -= version 0.121 -""" - - -############################### -# Requirements # -############################### - -# import system modules -import os, glob -import time, datetime -import sys -import shutil, getopt -import unicodedata - -def module_install_command(module_name, upgrade=False): - """ - create installation commands for Python modules and print information - """ - if upgrade: - load_command = "python -m pip install --upgrade %s" % module_name - else: - load_command = "python -m pip install %s" % module_name - - try: - logprint("Installing Python module: %s\n\t%s\n" % (module_name, load_command)) - except: - print "Installing Python module: %s\n\t%s\n" % (module_name, load_command) - - return load_command - -def load_modules(): - """ - load Python modules, if possible - otherwise try to install them - """ - - # make module names global - global cllct, gridspec, patches, rcParams, mplrc, P, Color, SeqIO, np, ccv, mcolors, rgb2hex, regex - - # matplotlib - try: - import matplotlib.collections as cllct - except: - command = module_install_command("matplotlib", upgrade=True) - try: - os.system(command) - print "\n" - import matplotlib.collections as cllct - except: - print "Please install module matplotlib manually" - from matplotlib.colors import colorConverter as ccv - import matplotlib.colors as mcolors - import matplotlib.gridspec as gridspec - import matplotlib.patches as patches - import pylab as P - - # specify matplotlib font settings - from matplotlib import rc as mplrc - mplrc('pdf', fonttype=42, compression=0) - from matplotlib import rcParams - rcParams['font.family'] = 'sans-serif' - rcParams['font.sans-serif'] = ['Helvetica', 'Verdana', 'Tahoma', ] - - # colour for color gradient palette - try: - from colour import Color - except: - command = module_install_command("colour") - try: - os.system(command) - print "\n" - from colour import Color - except: - print "Please install module colour manually" - - # color converter - try: - from colormap import rgb2hex - except: - command = module_install_command("colormap") - # additional module easydev.tools required by colormap - command2 = module_install_command("easydev") - try: - os.system(command) - os.system(command2) - print "\n" - from colormap import rgb2hex - except: - print "Please install module colormap manually" - - # biopython - try: - from Bio import SeqIO - except: - command = module_install_command("biopython") - try: - os.system(command) - print "\n" - from Bio import SeqIO - except: - print "Please install module biopython manually" - - # numpy - try: - import numpy as np - except: - command = module_install_command("numpy") - try: - os.system(command) - print "\n" - import numpy as np - except: - print "Please install module numpy manually" - - # regex for pattern matching - try: - import regex - except: - command = module_install_command("regex") - try: - os.system(command) - print "\n" - import regex - except: - print "Please install module regex manually" - -load_modules() - - -############################### -# Usage & Input # -############################### - -def usage(): - """ - usage and help - """ - - print """\n\n FLEXIDOT - ------------------------------------------------------------------- - - Version: - 1.00 - - Citation: - Kathrin M. Seibt, Thomas Schmidt, Tony Heitkam (in prep.) - "FlexiDot: Highly customizable, ambiguity-aware dotplots for visual sequence analyses" - - - General usage: - $ python flexidot.py -a [ARGUMENTS] - $ python flexidot.py -i [ARGUMENTS] - - - ARGUMENTS - ------------------------------------------------------------------- - - - INPUT/OUTPUT OPTIONS... required are [-a] OR [-i] - - -a, --auto_fas Imports all fasta files from current directory (*.fasta, *.fas, *.fa, *.fna) - Y or 1 = ON - N or 0 = OFF [default] - - -i, --in_file Input fasta file (fasta file name or comma-separated file list) - > Provide multiple files: Recall -i or provide comma-separated file names - - -o, --output_file_prefix File prefix to be added to the generated filenames [default = NONE] - - -c, --collage_output Multiple dotplots are combined in a collage - Y or 1 = ON [default] - N or 0 = OFF - - -m, --m_col Number of columns per page [default = 4] (only if --collage_output is ON) - - -n, --n_row Number of rows per page [default = 5] (only if --collage_output is ON) - - -f, --filetype Output file format - 0 = PNG [default] - 1 = PDF - 2 = SVG - - -s, --alphabetic_sorting Sort sequences alphabetically according to titles - Y or 1 = ON - N or 0 = OFF [default] - - - CALCULATION PARAMETERS... - - -k, --wordsize Wordsize (kmer length) for dotplot comparison [default = 7] - - -p, --plotting_mode Mode of FlexiDot dotplotting - 0 = self [default] - 1 = paired - 2 = poly (matrix with all-against-all dotplots) - > Run multiple plotting modes: Recall -p or provide comma-separated numbers - - -t, --type_nuc Type of residue is nucleotide - Y or 1 = nucleotide [default] - N or 0 = amino acid - - -w, --wobble_conversion Ambiguity handling for relaxed matching - Y or 1 = ON - N or 0 = OFF [default] - - -S, --substitution_count Number of substitutions (mismatches) allowed per window for relaxed matching - [default = 0] - - -r, --rc_option Find reverse complementary matches (only if type_nuc=y) - Y or 1 = ON [default] - N or 0 = OFF - - - GRAPHIC FORMATTING... - - -A, --line_width Line width [default = 1] - - -B, --line_col_for Line color [default = black] - - -C, --line_col_rev Reverse line color [default = green] - - -D, --x_label_pos Position of the X-label - Y or 1 = top [default] - N or 0 = bottom - - -E, --label_size Font size [default = 10] - - -F, --spacing Spacing between all-against-all dotplots (only if --plotting_mode=2) - [default = 0.04] - - -P, --plot_size Plotsize [default = 10] - - -L, --length_scaling Scale plot size for pairwise comparison (only if --plotting_mode=1) - Y or 1 = Scaling ON (axes scaled according to sequence length) - N or 0 = Scaling OFF (squared plots) [default] - - -T, --title_length Limit title length for self dotplot comparison (only if --plotting_mode=0) - [default = infinite] - - - GFF SHADING (for -p/--plotting_mode=0 only)... - - -g, --input_gff_files GFF3 file used for markup in self-dotplots - (provide multiple files: Recall -g or provide comma-separated file names) - - -G, --gff_color_config_file Tab-delimited config file for custom gff shading - column 1: feature type - column 2: color - column 3: alpha - column 4: zoom factor (for small regions) - - - LCS SHADING OPTIONS (for -p/--plotting_mode=2 only)... - - -x, --lcs_shading Shade subdotplot based on the length of the longest common substring (LCS) - Y or 1 = ON - N or 0 = OFF [default] - - -X, --lcs_shading_num Number of shading intervals (hues) for LCS (-x) and user matrix shading (-u) - [default = 5] - - -y, --lcs_shading_ref Reference for LCS shading - 0 = maximal LCS length [default] - 1 = maximally possible length (length of shorter sequence in pairwise comparison) - 2 = given interval sizes - DNA [default 100 bp] or proteins [default 10 aa] - see -Y - - -Y, --lcs_shading_interval_len Length of intervals for LCS shading (only if --lcs_shading_ref=2) - [default for nucleotides = 50; default for amino acids = 10] - - -z, --lcs_shading_ori Shade subdotplots according to LCS on - 0 = forward [default], - 1 = reverse, or - 2 = both strands (forward shading above diagonal, reverse shading on diagonal and below; - if using --input_user_matrix_file, best LCS is used below diagonal) - - - CUSTOM USER MATRIX SHADING OPTIONS (for -p/--plotting_mode=2 only)... - - -u, --input_user_matrix_file Shading above diagonal according to values in matrix file specified by the user - (tab-delimited or comma-separated matrix with sequence name in column 1 and numbers in columns 2-n - e.g. identity matrix from multiple sequence alignment - strings are ignored) - - -U, --user_matrix_print Display provided matrix entries in the fields above diagonal of all-against-all dotplot - Y or 1 = ON - N or 0 = OFF [default] - - - OTHERS... - - -h, --help Help screen - - -v, --verbose Verbose - - - """ - -def check_input(argv, trial_mode=False): - """ - commandline argument parsing - """ - - global log_txt, aa_bp_unit - - # helpers for argument parsing - ###################################### - - arguments = ["-a", "--auto_fas", "a:", "auto_fas=", - "-i", "--input_fasta", "i:", "input_fasta=", - "-o", "--output_file_prefix", "o:", "output_file_prefix=", - "-c", "--collage_output", "c:", "collage_output=", - "-m", "--m_col", "m:", "m_col=", - "-n", "--n_row", "n:", "n_row=", - "-f", "--filetype", "f:", "filetype=", - "-t", "--type_nuc", "t:", "type_nuc=", - "-g", "--input_gff_files", "g:", "input_gff_files", - "-G", "--gff_color_config_file", "G:", "gff_color_config_file", - "-k", "--wordsize", "k:", "wordsize=", - "-p", "--plotting_mode", "p:", "plotting_mode=", - "-w", "--wobble_conversion", "w:", "wobble_conversion=", - "-S", "--substitution_count", "S:", "substitution_count=", - "-r", "--rc_option", "r:", "rc_option=", - "-s", "--alphabetic_sorting", "s:", "alphabetic_sorting", - "-x", "--lcs_shading", "x:", "lcs_shading=", - "-X", "--lcs_shading_num", "X:", "lcs_shading_num=", - "-y", "--lcs_shading_ref", "y:", "lcs_shading_ref=", - "-Y", "--lcs_shading_interval_len", "Y:", "lcs_shading_interval_len=", - "-z", "--lcs_shading_ori", "z:", "lcs_shading_ori=", - "-u", "--input_user_matrix_file", "u:", "input_user_matrix_file=", - "-U", "--user_matrix_print", "U:", "user_matrix_print=", - "-P", "--plot_size", "P:", "plot_size=", - "-A", "--line_width", "A:", "line_width=", - "-B", "--line_col_for", "B:", "line_col_for=", - "-C", "--line_col_rev", "C:", "line_col_rev=", - "-D", "--x_label_pos", "D:", "x_label_pos=", - "-E", "--label_size", "E:", "label_size=", - "-F", "--spacing", "F:", "spacing=", - "-L", "--length_scaling", "L:", "length_scaling=", - "-T", "--title_length", "T:", "title_length=", - "-h", "--help", "h", "help", - "-v", "--verbose", "v", "verbose"] - - arguments_sysargv = tuple(arguments[0::4] + arguments[1::4]) - arguments_opts = "".join(arguments[2::4]) - arguments_args = arguments[3::4] - - - # setting defaults - ###################################### - - auto_fas = False # 0 - input_fasta = [] - output_file_prefix = None - collage_output = True # 1 - m_col = 4 - n_row = 5 - filetype = 0 - type_nuc = True - input_gff_files = [] - gff_color_config_file = "" - - wordsize = 7 - plotting_modes = [0] - wobble_conversion = False # 0 - substitution_count = 0 - rc_option = True # 1 - alphabetic_sorting = False # 0 - - lcs_shading = False # 0 - lcs_shading_num = 4 - lcs_shading_ref = 0 - lcs_shading_interval_len = 50 # interval default changes to "10" for amino acids [type_nuc = n] - lcs_shading_ori = 0 - - input_user_matrix_file = "" - user_matrix_print = False - - plot_size = 10 - line_width = 1 - line_col_for = "black" - line_col_rev = "#009243" - x_label_pos = True # 0 - label_size = 10 - spacing = 0.04 - length_scaling = False # 0 - title_length = float("Inf") - - aa_bp_unit = "bp" - - verbose = False # 0 - - filetype_dict = {0: "png", 1: "pdf", 2: "svg"} - lcs_shading_ref_dict = {0: "maximal LCS length", 1: "maximally possible length", 2: "given interval sizes"} - plotting_mode_dict = {0: "self", 1: "paired", 2: "all-against-all"} - lcs_shading_ori_dict = {0: "forward", 1: "reverse complement", 2: "both"} - - # return default parameters for testing purposes - if trial_mode: - print "ATTENTION: YOU ARE IN THE TRIAL MODE!!!\n\n" - - commandline = "trial_mode\n" - - parameters = [commandline, auto_fas, input_fasta, output_file_prefix, collage_output, m_col, n_row, filetype_dict[filetype], type_nuc, input_gff_files, gff_color_config_file, wordsize, plotting_modes, wobble_conversion, substitution_count, rc_option, alphabetic_sorting, lcs_shading, lcs_shading_num, lcs_shading_ref, lcs_shading_interval_len, lcs_shading_ori, input_user_matrix_file, user_matrix_print, plot_size, line_width, line_col_for, line_col_rev, x_label_pos, label_size, spacing, length_scaling, title_length, verbose] - return parameters - - - # read arguments - ###################################### - - commandline = "" - for arg in sys.argv: - commandline += arg + " " - - log_txt = "\n...reading input arguments..." - print log_txt - - if len(sys.argv) < 2: - print "\nERROR: More arguments are needed. Exit..." - log_txt += "\nERROR: More arguments are needed. Exit..." - usage() - sys.exit() - - elif sys.argv[1] not in arguments_sysargv: - print "\nINPUT ERROR: Input argument %s unknown. Please check the help screen." % sys.argv[1] - log_txt += "\nINPUT ERROR: Input argument %s unknown. Please check the help screen." % sys.argv[1] - # usage() - sys.exit() - - try: - opts, args = getopt.getopt(sys.argv[1:], arguments_opts, arguments_args) - - except getopt.GetoptError: - print "\nINPUT ERROR (getopt): Input argument %s unknown. Please check the help screen." % sys.argv[1:] - log_txt += "\nINPUT ERROR (getopt): Input argument %s unknown. Please check the help screen." % sys.argv[1:] - # usage() - sys.exit() - - for opt, arg in opts: - - if opt in ("-h", "--help"): - print "...fetch help screen" - log_txt += "\n...fetch help screen" - usage(), sys.exit() - - if opt in ("-v", "--verbose"): - print "...verbose output" - log_txt += "\n...verbose output" - verbose = True - - elif opt in ("-i", "--input_fasta"): - if "," in arg: - arg_list = arg.split(",") - for temp_file in arg_list: - if not os.path.exists(str(temp_file)): - message = "\nERROR: fasta_file '%s' was not found!" % str(temp_file) - sys.exit(message) - else: - input_fasta.append(str(temp_file)) - print "fasta file #%i: %s" % (len(input_fasta), str(temp_file)) - log_txt += "\nfasta file #%i: %s" % (len(input_fasta), str(temp_file)) - else: - if not os.path.exists(str(arg)): - message = "\nERROR: fasta_file '%s' was not found!" % str(arg) - log_txt += message - sys.exit(message) - else: - input_fasta.append(str(arg)) - print "fasta file #%i: %s" % (len(input_fasta), str(arg)) - log_txt += "\nfasta file #%i: %s" % (len(input_fasta), str(arg)) - - - elif opt in ("-a", "--auto_fas"): - auto_fas = check_bools(str(arg), default=auto_fas) - - - # multiple gff files: reads them into a list - elif opt in ("-g", "--input_gff_files"): - - # append gff file only if existing - if "," in arg: - arg_list = arg.split(",") - for temp_file in arg_list: - if not os.path.exists(str(temp_file)): - message = "\nERROR: gff_file '%s' was not found!" % str(temp_file) - print message - log_txt += message - print " -->Running FlexiDot without this gff file!" - log_txt += "\n -->Running FlexiDot without this gff file!" - else: - print "GFF file #%i: %s" %(len(input_gff_files), str(temp_file)) - log_txt += "\nGFF file #%i: %s" %(len(input_gff_files), str(temp_file)) - input_gff_files.append(str(temp_file)) - else: - if not os.path.exists(str(arg)): - message = "\nERROR: gff_file '%s' was not found!" % str(arg) - print message - log_txt += message - print " -->Running FlexiDot without this gff file!" - log_txt += "\n -->Running FlexiDot without this gff file!" - else: - input_gff_files.append(str(arg)) - print "GFF file #%i: %s" %(len(input_gff_files), str(arg)) - log_txt += "\nGFF file #%i: %s" %(len(input_gff_files), str(arg)) - - - elif opt in ("-G", "--gff_color_config_file"): - if not os.path.exists(str(arg)): - message = "\nERROR: gff_color_config_file '%s' was not found!" % str(arg) - print message + "\n -->Running FlexiDot with default gff coloring specification!" - log_txt += message + "\n -->Running FlexiDot with default gff coloring specification!" - else: - gff_color_config_file = str(arg) - - - elif opt in ("-u", "--input_user_matrix_file"): - if not os.path.exists(str(arg)): - message = "\nERROR: input_user_matrix_file '%s' was not found!" % str(arg) - print message + "\n -->Running FlexiDot without input_user_matrix_file %s!" % arg - log_txt += message + "\n -->Running FlexiDot withdefault matrix shading file!" - else: - input_user_matrix_file = str(arg) - - elif opt in ("-U", "--user_matrix_print"): - user_matrix_print = check_bools(str(arg), default=user_matrix_print) - - elif opt in ("-o", "--output_file_prefix"): - output_file_prefix = arg - - elif opt in ("-c", "--collage_output"): - collage_output = check_bools(str(arg), default=collage_output) - - elif opt in ("-m", "--m_col"): - try: m_col = int(arg) - except: - print "m_col - invalid argument - using default value" - log_txt += "\nm_col - invalid argument - using default value" - - elif opt in ("-n", "--n_row"): - try: n_row = int(arg) - except: - print "n_row - invalid argument - using default value" - log_txt += "\nn_row - invalid argument - using default value" - - elif opt in ("-f", "--filetype"): - if 0 <= int(arg) <= 2: - filetype = int(arg) - else: - print "\nERROR: Please provide valid filetype argument. %s is out of range. It will be set to -f 0 [default]." %(filetype) - log_txt += "\nERROR: Please provide valid filetype argument. %s is out of range. It will be set to -f 0 [default]." %(filetype) - - elif opt in ("-t", "--type_nuc"): - type_nuc = check_bools(str(arg), default=type_nuc) - - if type_nuc == False: - # interval default changed for amino acids - lcs_shading_interval_len = 10 - aa_bp_unit = "aa" - - elif opt in ("-k", "--wordsize"): - try: wordsize = int(arg) - except: - print "wordsize - invalid argument - using default value" - log_txt += "\nwordsize - invalid argument - using default value" - - elif opt in ("-p", "--plotting_mode"): - if "," in arg: - temp_modes = arg.split(",") - for item in temp_modes: - if item in ["0","1","2"]: - plotting_modes.append(int(item)) - elif arg in ["0","1","2"]: - plotting_modes = [int(arg)] - else: - print "Please provide valid plotting_modes argument - e.g. 1 or 0,1,2 - using default [0]" - log_txt += "\nPlease provide valid plotting_modes argument - e.g. 1 or 0,1,2 - using default [0]" - - elif opt in ("-w", "--wobble_conversion"): - wobble_conversion = check_bools(str(arg), default=wobble_conversion) - - elif opt in ("-S", "--substitution_count"): - try: substitution_count = int(arg) - except: - print "substitution_count - invalid argument - using default value" - log_txt += "\nsubstitution_count - invalid argument - using default value" - - elif opt in ("-r", "--rc_option"): - rc_option = check_bools(str(arg), default=rc_option) - - elif opt in ("-s", "--alphabetic_sorting"): - alphabetic_sorting = check_bools(str(arg), default=alphabetic_sorting) - - elif opt in ("-x", "--lcs_shading"): - lcs_shading = check_bools(str(arg), default=lcs_shading) - - elif opt in ("-X", "--lcs_shading_num"): - try: lcs_shading_num = int(arg) - 1 - except: - print "lcs_shading_num - invalid argument - using default value" - log_txt += "\nlcs_shading_num - invalid argument - using default value" - - elif opt in ("-y", "--lcs_shading_ref"): - try: - if 0 <= int(arg) <= 2: - lcs_shading_ref = int(arg) - else: - print "\nERROR: lcs_shading_ref %s out of range. It will be set to -y 0 [default]." %(lcs_shading_ref) - log_txt += "\nERROR: lcs_shading_ref %s out of range. It will be set to -y 0 [default]." %(lcs_shading_ref) - except: - print "lcs_shading_ref - invalid argument - using default value" - log_txt += "\nlcs_shading_ref - invalid argument - using default value" - - elif opt in ("-Y", "--lcs_shading_interval_len"): - try: lcs_shading_interval_len = int(arg) - except: - print "lcs_shading_interval_len - invalid argument - using default value" - log_txt += "\nlcs_shading_interval_len - invalid argument - using default value" - - elif opt in ("-z", "--lcs_shading_ori"): - if 0 <= int(arg) <= 2: - lcs_shading_ori = int(arg) - else: - print "\nERROR: Please provide valid lcs_shading_ori argument. %s is out of range. It will be set to -z 0 [default]." %(lcs_shading_ori) - log_txt += "\nERROR: Please provide valid lcs_shading_ori argument. %s is out of range. It will be set to -z 0 [default]." %(lcs_shading_ori) - - elif opt in ("-P", "--plot_size"): - try: plot_size = float(arg) - except: - print "plot_size - invalid argument - using default value" - log_txt += "\nplot_size - invalid argument - using default value" - - - elif opt in ("-A", "--line_width"): - try: line_width = float(arg) - except: - print "line_width - invalid argument - using default value" - log_txt += "\nline_width - invalid argument - using default value" - - elif opt in ("-B", "--line_col_for"): - if mcolors.is_color_like(arg): - line_col_for = arg - else: - print "line_col_for - invalid argument - using default value" - log_txt += "\nline_col_for - invalid argument - using default value" - - elif opt in ("-C", "--line_col_rev"): - if mcolors.is_color_like(arg): - line_col_rev = arg - else: - print "line_col_rev - invalid argument - using default value" - log_txt += "\nline_col_rev - invalid argument - using default value" - - elif opt in ("-D", "--x_label_pos"): - x_label_pos = check_bools(str(arg), default=x_label_pos) - - elif opt in ("-E", "--label_size"): - try: label_size = float(arg) - except: - print "label_size - invalid argument - using default value" - log_txt += "\nlabel_size - invalid argument - using default value" - - elif opt in ("-F", "--spacing"): - try: spacing = float(arg) - except: - print "spacing - invalid argument - using default value" - log_txt += "\nspacing - invalid argument - using default value" - - elif opt in ("-L", "--length_scaling"): - length_scaling = check_bools(str(arg), default=length_scaling) - - elif opt in ("-T", "--title_length"): - try: title_length = int(arg) - except: - print "title_length - invalid argument - using default value" - log_txt += "\ntitle_length - invalid argument - using default value" - - # start logging file - logprint(commandline, start=True, printing=False, prefix=output_file_prefix) - logprint(log_txt, start=False, printing=False) - - - # print chosen arguments - ###################################### - - text = "\n%s\n" % (70 * "-") - text += "\n" + "INPUT/OUTPUT OPTIONS...\n" - text += "\n" + "Input fasta file: " + ", ".join(input_fasta) - text += "\n" + "Automatic fasta collection from current directory: " + str(auto_fas) - text += "\n" + "Collage output: " + str(collage_output) - text += "\n" + "Number of columns per page: " + str(m_col) - text += "\n" + "Number of rows per page: " + str(n_row) - text += "\n" + "File format: " + filetype_dict[filetype] - text += "\n" + "Residue type is nucleotide: " + str(type_nuc) - - text += "\n" + "\n\nCALCULATION PARAMETERS...\n" - text += "\n" + "Wordsize: " + str(wordsize) - text += "\n" + "Plotting mode: " + str(plotting_modes).replace("[", "").replace("]", "") + "\n" + 51 * " " - for item in plotting_modes: - text += plotting_mode_dict[item] + " " - text += "\n" + "Ambiguity handling: " + str(wobble_conversion) - text += "\n" + "Reverse complement scanning: " + str(rc_option) - text += "\n" + "Alphabetic sorting: " + str(alphabetic_sorting) - - if 0 in plotting_modes and input_gff_files != []: - text += "\n" + "Input gff files: " + ", ".join(input_gff_files) - if gff_color_config_file != "": - text += "\n" + "GFF color config file: " + gff_color_config_file - text += "\n" + "Prefix for output files: " + str(output_file_prefix) - - if 2 in plotting_modes: - text += "\n" + "\n\nLCS SHADING OPTIONS (plotting_mode 'all-against-all' only)...\n" - text += "\n" + "LCS shading: " + str(lcs_shading) - text += "\n" + "LCS shading interval number: " + str(lcs_shading_num + 1) - text += "\n" + "LCS shading reference: " + lcs_shading_ref_dict[lcs_shading_ref] - if lcs_shading_ref == 2: - text += "\n" + "LCS shading interval size [%s]: " % (aa_bp_unit) + str(lcs_shading_interval_len) - text += "\n" + "LCS shading orientation: " + lcs_shading_ori_dict[lcs_shading_ori] - if input_user_matrix_file != "": - text += "\n" + "Custom user shading matrix file: " + input_user_matrix_file - text += "\n" + "Print user matrix values (instead of dotplot): " + str(user_matrix_print) - - text += "\n" + "\n\nGRAPHIC FORMATTING...\n" - text += "\n" + "Plot size: " + str(plot_size) - text += "\n" + "Line width: " + str(line_width) - text += "\n" + "Line color: " + line_col_for - text += "\n" + "Reverse line color: " + line_col_rev - text += "\n" + "X label position: " + str(x_label_pos) - text += "\n" + "Label size: " + str(label_size) - text += "\n" + "Spacing: " + str(spacing) - text += "\n" + "Title length (limit number of characters): " + str(title_length) - text += "\n" + "Length scaling: " + str(length_scaling) - text += "\n%s\n" % (70 * "-") - logprint(text) - - - # collect settings - parameters = [commandline, auto_fas, input_fasta, output_file_prefix, collage_output, m_col, n_row, filetype_dict[filetype], type_nuc, input_gff_files, gff_color_config_file, wordsize, plotting_modes, wobble_conversion, substitution_count, rc_option, alphabetic_sorting, lcs_shading, lcs_shading_num, lcs_shading_ref, lcs_shading_interval_len, lcs_shading_ori, input_user_matrix_file, user_matrix_print, plot_size, line_width, line_col_for, line_col_rev, x_label_pos, label_size, spacing, length_scaling, title_length, verbose] - - return parameters - - -############################### -# Helper Functions # -############################### - -def alphabets(type_nuc=True): - """ - provide ambiguity code for sequences - """ - - nucleotide_alphabet = ["A", "C", "G", "T"] - - nucleotide_alphabet_full = ["A", "C", "G", "T", "N", "B", "D", "H", - "V", "Y", "R", "W", "S", "K", "M"] - - nucleotide_ambiguity_code = {"N": ["A", "C", "G", "T"], # any - "B": ["C", "G", "T"], # not A - "D": ["A", "G", "T"], # not C - "H": ["A", "C", "T"], # not G - "V": ["A", "C", "G"], # not T - "Y": ["C", "T"], # pyrimidine - "R": ["A", "G"], # purine - "W": ["A", "T"], # weak - "S": ["C", "G"], # strong - "K": ["G", "T"], # keto - "M": ["A", "C"]} # amino - - nucleotide_match_dict = {"N": "[ACGTNBDHVYRWSKM]", # any - "B": "[CGTNBDHVYRWSKM]", # not A - "D": "[AGTNBDHVYRWSKM]", # not C - "H": "[ACTNBDHVYRWSKM]", # not G - "V": "[ACGNBDHVYRWSKM]", # not T - "K": "[GTNBDHVYRWSK]", # keto - not A,C,M - "M": "[ACNBDHVYRWSM]", # amino - not G,T,K - "W": "[ATNBDHVYRWKM]", # weak - not C,G,S - "S": "[CGNBDHVYRSKM]", # strong - not A,G,W - "Y": "[CTNBDHVYWSKM]", # pyrimidine - not A,G,R - "R": "[AGNBDHVRWSKM]", # purine - not C,T,Y - "A": "[ANDHVRWM]", - "C": "[CNBHVYSM]", - "G": "[GNBDVRSK]", - "T": "[TNBDHYWK]"} - - # nucleotide_match_dict = {"N": ".", # any - # "B": "[^A]", # not A - # "D": "[^C]", # not C - # "H": "[^G]", # not G - # "V": "[^T]", # not T - # "K": "[^ACM]", # keto - not A,C,M - # "M": "[^GTK]", # amino - not G,T,K - # "W": "[^CGS]", # weak - not C,G,S - # "S": "[^AGW]", # strong - not A,G,W - # "Y": "[^AGR]", # pyrimidine - not A,G,R - # "R": "[^CTY]", # purine - not C,T,Y - # "A": "[ANDHVRWM]", - # "C": "[CNBHVYSM]", - # "G": "[GNBDVRSK]", - # "T": "[TNBDHYWK]"} - - aminoacid_alphabet = ["A", "R", "N", "D", "C", "E", "Q", "G", - "H", "I", "L", "K", "M", "F", "P", "S", - "T", "W", "Y", "V", "U", "O", "*"] - - aminoacid_alphabet_full = ["A", "R", "N", "D", "C", "E", "Q", "G", - "H", "I", "L", "K", "M", "F", "P", "S", - "T", "W", "Y", "V", "U", "O", "*", "J", - "Z", "B", "X"] - - aminoacid_ambiguity_code = {"J": ["I", "L"], - "Z": ["Q", "E"], - "B": ["N", "D"], - "X": ["A", "R", "N", "D", "C", "E", "Q", "G", - "H", "I", "L", "K", "M", "F", "P", "S", - "T", "W", "Y", "V", "U", "O", "*"]} # any - - aminoacid_match_dict = {"J": "[ILJ]", - "Z": "[QEZ]", - "B": "[NDB]", - # "X": ".", - "X": "[ARNDCEQGHILKMFPSTWYVUO*XBZJ]", - "A": "[AX]", - "R": "[RX]", - "N": "[NXB]", - "D": "[DXB]", - "C": "[CX]", - "E": "[EXZ]", - "Q": "[QXZ]", - "G": "[GX]", - "H": "[HX]", - "I": "[IXJ]", - "L": "[LXJ]", - "K": "[KX]", - "M": "[MX]", - "F": "[FX]", - "P": "[PX]", - "S": "[SX]", - "T": "[TX]", - "W": "[WX]", - "Y": "[YX]", - "V": "[VX]", - "U": "[UX]", - "O": "[OX]", - "*": "[*X]"} - - aa_only = set(['E', 'F', 'I', 'J', 'L', 'O', 'Q', 'P', 'U', 'X', 'Z', '*']) - # return nucleotide_alphabet, nucleotide_alphabet_full, nucleotide_ambiguity_code, aminoacid_alphabet, aminoacid_alphabet_full, aminoacid_ambiguity_code, aa_only - - if type_nuc: - return nucleotide_alphabet, nucleotide_alphabet_full, nucleotide_ambiguity_code, nucleotide_match_dict - else: - return aminoacid_alphabet, aminoacid_alphabet_full, aminoacid_ambiguity_code, aminoacid_match_dict - -def logprint(text, start=False, printing=True, prefix=""): - """ - log output to log_file and optionally print - """ - - # define log file name and open file - global log_file_name - if start and trial_mode: - log_file_name = "log_file.txt" - if prefix != "" and prefix != None: - if not prefix.endswith("-"): - prefix = prefix + "-" - log_file_name = prefix + log_file_name - log_file = open(log_file_name, 'w') - log_file.write("Date: %s\n\n" % str(datetime.datetime.now())) - elif start: - date = datetime.date.today() - time = str(datetime.datetime.now()).split(" ")[1].split(".")[0].replace(":", "-") - log_file_name = "%s_%s_log_file.txt" % (date, time) - if prefix != "" and prefix != None: - if not prefix.endswith("-"): - prefix = prefix + "-" - log_file_name = prefix + log_file_name - log_file = open(log_file_name, 'w') - log_file.write("Date: %s\n\n" % str(datetime.datetime.now())) - else: - log_file = open(log_file_name, 'a') - - # write log (and print) - log_file.write(text + "\n") - if printing: - print text - log_file.close() - -def time_track(starting_time, show=True): - """ - calculate time passed since last time measurement - """ - now = time.time() - delta = now - starting_time - if show: - text = "\n\t %s seconds\n" % str(delta) - logprint(text, start=False, printing=True) - return now - -def calc_fig_ratio(ncols, nrows, plot_size, verbose=False): - """ - calculate size ratio for given number of columns (ncols) and rows (nrows) - with plot_size as maximum width and length - """ - ratio = ncols*1./nrows - if verbose: - text = " ".join([ncols, nrows, ratio]) - logprint(text, start=False, printing=True) - if ncols >= nrows: - figsize_x = plot_size - figsize_y = plot_size / ratio - else: - figsize_x = plot_size * ratio - figsize_y = plot_size - return figsize_x, figsize_y - -def shorten_name(seq_name, max_len=float("Inf"), delim="_"): - """ - shorten sequence names (for diagram titles) - """ - - if len(seq_name) <= max_len: - return seq_name - - # keep first and last part if multiple parts separated by delimiter (e.g. species_prefix + sequence_id) - if delim in seq_name: - if seq_name.count(delim) >= 2: - name = "%s..." % delim.join(seq_name.split(delim)[:1]) + seq_name.split(delim)[-1] # .replace("_000", "-") - else: - name = seq_name[:((max_len-2)//2)] + "..." + seq_name[((max_len-2)//2):] - - if len(name) > max_len: - name = name[:((max_len-2)//2)] + "..." + name[((max_len-2)//2):] - else: - name = seq_name[:((max_len-2)//2)] + "..." + seq_name[((max_len-2)//2):] - - return name - -def unicode_name(name): - """ - replace non-ascii characters in string (e.g. for use in matplotlib) - """ - unicode_string = eval('u"%s"' % name) - return unicodedata.normalize('NFKD', unicode_string).encode('ascii','ignore') - -def check_bools(arg, update_log_txt = True, default=None): - """ - converts commandline arguments into boolean - """ - - - # convert valid arguments - if str(arg).lower() == "y" or str(arg) == "1": - return True - elif str(arg).lower() == "n" or str(arg) == "0": - return False - - # use default in case of invalid argument - else: - if update_log_txt: - global log_txt - log_txt += "using default for " + str(arg) - else: - try: - logprint("using default for " + str(arg)) - except: - print "using default for " + str(arg) - return default - -def create_color_list(number, color_map=None, logging=False, max_grey="#595959"): - """ - create color list with given number of entries - grey by default, matplotlib color_map can be provided - """ - - try: - # create pylab colormap - cmap = eval("P.cm." + color_map) - # get descrete color list from pylab - cmaplist = [cmap(i) for i in range(cmap.N)] # extract colors from map - # determine positions for number of colors required - steps = len(cmaplist)/(number) - numbers = range(0, len(cmaplist), steps) - - # extract color and convert to hex code - colors = [] - for idx in numbers[:-1]: - rgb_color = cmaplist[idx] - col = rgb2hex(rgb_color[0]*255, rgb_color[1]*255, rgb_color[2]*255) - colors.append(col) - - # grey - except: - if not color_map == None: - logprint("Invalid color_map (%s) provided! - Examples: jet, Blues, OrRd, bwr,..." % color_map) - logprint("See https://matplotlib.org/users/colormaps.html\n") - old_max_grey = "#373737" - old_max_grey = "#444444" - colors = list(Color("#FFFFFF").range_to(Color(max_grey), number)) # grey - for idx in range(len(colors)): - colors[idx] = str(colors[idx]).replace("Color ", "") - if "#" in colors[idx] and len(colors[idx]) != 7: - # print colors[idx] - colors[idx] = colors[idx] + colors[idx][-(7-len(colors[idx])):] - - text = "%d Colors: %s" % (len(colors), ", ".join(colors)) - if logging: logprint(text, start=False, printing=True) - - return colors - - -############################### -# File Handling # -############################### - -def read_seq(input_fasta, verbose=False): - """ - read fasta sequences from (all) file(s) - """ - - # check if file provided - if input_fasta == [] or input_fasta == "": - text = "Attention: No valid file names provided: >%s<" % input_fasta - logprint(text, start=False, printing=True) - return {}, [] - - # combine sequence files, if required - if type(input_fasta) == list: - # concatenate fasta files - if len(input_fasta) > 1: - if verbose: - print "concatenating fastas...", - text = "concatenating fastas..." - input_fasta_combi = concatenate_files(input_fasta) - if verbose: - print "done" - text += "done" - logprint(text, start=False, printing=False) - else: - input_fasta_combi = input_fasta[0] - else: - input_fasta_combi = input_fasta - - # read sequences - if verbose: - print "reading fasta...", - text = "reading fasta...", - try: - seq_dict = SeqIO.index(input_fasta_combi, "fasta") - except ValueError: - logprint("Error reading fasta sequences - please check input files, e.g. for duplicate names!") - return {}, [] - except: - logprint("Error reading fasta sequences - please check input files!") - return {}, [] - - if verbose: - print "done" - text += "done" - logprint(text, start=False, printing=False) - - for seq in seq_dict: - if "-" in seq_dict[seq].seq: - # ungapped = seq_dict[seq].seq.ungap("-") # cannot be assigned back to sequence record - text = "\nSequences degapped prior Analysis!!!" - logprint(text, start=False, printing=True) - return read_seq(degap_fasta(input_fasta), verbose=verbose) - - # get ordered sequence names - sequences = [] - for item in SeqIO.parse(input_fasta_combi, "fasta"): - sequences.append(item.id) - return seq_dict, sequences - -def read_gff_color_config(gff_color_config_file=""): - """ - define coloring options for gff-based color shading of self-dotplots - """ - - # default aestetics for annotation shading (e.g. if no user config file is provided) - # dictionary with feature_type as key and tuple(color, transparency, zoom) as value - gff_feat_colors = {"orf": ("#b41a31", 0.2, 0), - "orf_rev": ("#ff773b", 0.3, 0), - "gene": ("#b41a31", 0.2, 0), - "cds": ("darkorange", 0.2, 0), - "exon": ("orange", 0.2, 0), - "intron": ("lightgrey", 0.2, 0), - "utr": ("lightblue", 0.2, 0), - "repeat_region": ("green", 0.3, 0), - "repeat": ("green", 0.3, 0), - "tandem_repeat": ("red", 0.3, 0), - "transposable_element": ("blue", 0.3, 0), - "ltr_retrotransposon": ("#cccccc", 0.5, 0), - "ltr-retro": ("#cccccc", 0.5, 0), - "long_terminal_repeat": ("#2dd0f0", 0.75, 2), - "ltr": ("#2dd0f0", 0.75, 2), - "pbs": ("purple", 0.75, 2), - "ppt": ("#17805a", 0.5, 2), - "target_site_duplication": ("red", 0.75, 2), - "misc_feature": ("grey", 0.3, 0), - "misc_feat": ("grey", 0.3, 0), - "misc": ("grey", 0.3, 0), - "others": ("grey", 0.5, 0)} - if gff_color_config_file in ["", None] or not os.path.exists(str(gff_color_config_file)): - return gff_feat_colors - - text = "Updating GFF color configuration with custom specifications\n" - logprint(text, start=False, printing=True) - - # read custom gff_color_config_file - in_file = open(gff_color_config_file, 'rb') - overwritten = set([]) - for line in in_file: - if not line.startswith("#") and len(line.strip().split("\t")) >= 4: - data = line.strip().split("\t") - feat = data[0].lower() - color = data[1].lower() - - # check, if settings are valid - if not mcolors.is_color_like(color): - color = "grey" - text = "Invalid color specified for %s: %s - default grey" % (data[0], data[1]) - logprint(text) - try: - alpha = float(data[2]) - except: - alpha = 0.75 - text = "Invalid alpha specified for %s: %s - default 0.75" % (data[0], data[2]) - logprint(text) - try: - zoom = float(data[3]) - except: - zoom = 0 - text = "Invalid zoom specified for %s: %s - default 0" % (data[0], data[3]) - logprint(text) - - # track changes of predefined settings - if feat in gff_feat_colors.keys(): - overwritten.add(data[0].lower()) - - gff_feat_colors[feat] = (color, alpha, zoom) - in_file.close() - - # default coloring for unknown annotations - if not "others" in gff_feat_colors.keys(): - gff_feat_colors["others"] = ("grey", 0.5, 0) - - if verbose: - # print configuration - text = "\n\nGFF color specification:\n%s\n" % (60 * ".") - for item in sorted(gff_feat_colors.keys()): - text += "%-30s\t%-10s\t%-5s\t%s\n" % (item, str(gff_feat_colors[item][0]), str(gff_feat_colors[item][1]), str(gff_feat_colors[item][2])) - logprint (text, printing=True) - - # print overwritting feature type specifications - if len(overwritten) != 0: - text = "%d feature type specifications overwritten:" % len(overwritten) - text += "\n\t"+ ", ".join(overwritten) + "\n" - logprint(text, start=False, printing=True) - - text = "GFF color specification updated acc. to %s\n\t%s\n\n" % (gff_color_config_file, ", ".join(gff_feat_colors)) - logprint(text, start=False, printing=True) - - return gff_feat_colors - -def read_gffs(input_gff_files, color_dict={"others": ("grey", 1, 0)}, type_nuc=True, prefix="", filetype='png', verbose=False): - """ - create feature dictionary from input_gff - sequence name as key and (feature type, start, stop) as value - """ - if type(input_gff_files) != list: - input_gff_files = [input_gff_files] - - # create dictionary with seq_name as key and (type, start and stop) as value - unknown_feats = set([]) - used_feats = set([]) - feat_dict = {} - for input_gff in input_gff_files: - text = "...reading " + input_gff - logprint(text, start=False, printing=True) - - in_file = open(input_gff, 'rb') - for line in in_file: - if not line.startswith("#") and line.strip() != "": - data = line.strip().split("\t") - feat_type = data[2].lower() - if data[6] == "-": - feat_type += "_rev" - if not feat_type.lower() in color_dict.keys(): - if feat_type.lower().replace("_rev", "") in color_dict.keys(): - feat_type = feat_type.replace("_rev", "") - else: - unknown_feats.add(feat_type) - feat_type = "others" - used_feats.add(feat_type) - if not data[0] in feat_dict.keys(): - feat_dict[data[0]] = [(feat_type, int(data[3]), int(data[4]))] # feature type, start, stop - else: - feat_dict[data[0]].append((feat_type, int(data[3]), int(data[4]))) # feature type, start, stop - if verbose: - text = "\nAnnotations for: %s\n" % ", ".join(feat_dict.keys()[:10]) - if len(feat_dict.keys()) > 10: - text = text[:-1] + ", ...\n" - logprint(text, start=False, printing=True) - in_file.close() - - # print feature types without specific shading settings - if len(unknown_feats) != 0: - text = "Missing shading specification for %d feature type(s):\n\t%s\n" % (len(unknown_feats), ", ".join(sorted(unknown_feats))) - logprint(text, start=False, printing=True) - - # create color legend - colors, alphas = [], [] - for item in sorted(used_feats): - colors.append(color_dict[item][0]) - alphas.append(color_dict[item][1]) - legend_figure(colors=colors, lcs_shading_num=len(used_feats), type_nuc=type_nuc, bins=sorted(used_feats), alphas=alphas, gff_legend=True, prefix=prefix, filetype=filetype) - - # print settings - text = "GFF Feature Types: %s\nGFF Colors: %s" % (", ".join(sorted(used_feats)), ", ".join(sorted(colors))) - logprint(text, start=False, printing=True) - - return feat_dict - -def read_matrix(matrix_file_name, delim="\t", symmetric=True, recursion=False, verbose=False): - input_file = open(matrix_file_name, 'rb') - - # read sequence names from first column - names = [] - for line in input_file: - if not line.startswith("#") and not line.startswith(delim) and delim in line: - names.append(line.strip().split(delim)[0]) - logprint("Delimiter '%s': %d names - %s\n" % (delim, len(names), ", ".join(names))) - - # check if names were found - otherwise try another delimiter - if names == [] and not recursion: - if delim == "\t": - new_delim = "," - else: - new_delim = "\t" - logprint("\nMatrix file not containing data delimited by '%s' - trying to read matrix with delimiter '%s'" % (delim.replace("\t", "\\t"), new_delim)) - info_dict = read_matrix(matrix_file_name, delim=new_delim, symmetric=symmetric, recursion=True, verbose=verbose) - return info_dict - elif names == []: - logprint("Empty matrix file with alternative delimiter!") - return info_dict - input_file.close() - - input_file = open(matrix_file_name, 'rb') - # read matrix entries as values in dictionary with tuple(names) as key - info_dict = {} - contradictory_entries = [] - for line in input_file: - if not line.startswith("#") and not line.startswith(delim) and delim in line: - data = line.strip().split(delim) - for idx in range(len(data[1:])): - # print tuple(sorted([data[0], names[idx]])), data[idx+1] - if symmetric: - key = tuple(sorted([names[idx], data[0]])) - else: - key = tuple(names[idx], data[0]) - if key in info_dict.keys(): - if symmetric and info_dict[key] != data[idx+1] and data[idx+1] not in ["", "-"] and info_dict[key] not in ["", "-"]: - contradictory_entries.append(key) - info_dict[key] = data[idx+1] - input_file.close() - - if len(contradictory_entries) != 0: - try: - logprint("\nContradictory entries in matrix file %s:\n\t%s" % (matrix_file_name, ", ".join(contradictory_entries))) - except: - log_txt = "\nContradictory entries in matrix file %s:\n\t" % (matrix_file_name) - for item in contradictory_entries: - log_txt += str(item).replace("'", "") + ", " - log_txt = log_txt[:-2] - logprint(log_txt) - logprint("Using value from bottom left triangle!") - if verbose: - logprint("\nMatrix information for Sequences named: " % ", ".join(names)) - - return info_dict - -def concatenate_files(file_list, combi_filename="temp_combined.fasta", verbose=False): - """ - concatenate content of all files in file_list into a combined file named combi_filename - """ - out_file = open(combi_filename, 'w') - text = "" - for item in file_list: - if verbose: - text += item + " " - print item, - # read in_file linewise and write to out_file - in_file = open(item, 'rb') - for line in in_file: - out_file.write(line.strip()+"\n") - in_file.close() - out_file.close() - if verbose: - logprint(text, start=False, printing=False) - return combi_filename - -def degap_fasta(input_fasta): - """ - remove gaps from fasta - new degapped sequence file created - """ - - # degap all sequence files - output_fastas = [] - if type(input_fasta) != list: - input_fasta = list(input_fasta) - for input_fas in input_fasta: - output_fas = input_fas[:input_fas.rfind(".")] + "_degapped.fas" - in_file = open(input_fas, 'rb') - out_file = open(output_fas, 'w') - for line in in_file: - if line.startswith(">"): - out_file.write(line.strip()+"\n") - else: - out_file.write(line.strip().replace("-", "")+"\n") - out_file.close() - in_file.close() - output_fastas.append(output_fas) - return output_fastas - -def legend_figure(colors, lcs_shading_num, type_nuc=True, unit="%", filetype="png", max_lcs_len=None, min_lcs_len=0, bins=[], alphas=[], gff_legend=False, prefix="", verbose=False): - """ - create figure color legend - """ - max_legend_length_row = 8 - max_legend_length_col = 4 - - # define output file - if filetype not in ["png", "pdf", "svg"]: - text = "Provide valid file type - png, pdf, or svg" - logprint(text, start=False, printing=True) - filetype="png" - - # check if length of information fit - if not gff_legend and ((bins != [] and len(colors) != lcs_shading_num+1) or (bins != [] and len(colors) != len(bins)+1)): - if bins != [] and len(colors) != lcs_shading_num+1: - text = "**Attention**\nlcs_shading_num (%d) does not match number of colors (%d)!\n"% (lcs_shading_num, len(bins)) - elif bins != [] and len(colors) != len(bins)+1: - text = "**Attention**\nnumber of LCS length bins (%d) does not match number of colors (%d)!\n" % (len(colors), len(bins)) - logprint(text, start=False, printing=True) - elif gff_legend and len(bins) != len(colors): - text = "**Attention**\nnumber of GFF Feature Types (%d) does not match number of colors (%d)!\n" % (len(colors), len(bins)) - logprint(text, start=False, printing=True) - - # set alpha values to opaque if none are provided - if alphas == []: - for item in colors: - alphas.append(1) - - # legend data points - data_points = range(len(colors)) - if not gff_legend: - - # specify intervals, if max_lcs_len provided - if max_lcs_len != None: - multi_factor = 100 # one digit - if max_lcs_len <= 1: - multi_factor = 1000 # two digits - # len_interval_size = (max_lcs_len-min_lcs_len) * multi_factor *1. // lcs_shading_num * (1./ multi_factor) - len_interval_size = (max_lcs_len-min_lcs_len) * 1. / lcs_shading_num - len_pos = [float("%.2f" % (min_lcs_len))] - # calculate interval positions - for idx in range(lcs_shading_num): - len_pos.append(float("%.2f" % (len_pos[-1] + len_interval_size))) - - if prefix.startswith("custom-matrix") and (0 <= max_lcs_len <= 100 and 0 <= min_lcs_len <= 100): - unit = "%" - elif prefix.startswith("custom-matrix"): - unit = "" - - text = "\n%d Legend intervals from %.2f to %.2f: \n\t%s - number: %d, step: %.2f, unit: %s\n" % (lcs_shading_num+1, min_lcs_len, max_lcs_len, str(len_pos), len(len_pos), len_interval_size, unit) - logprint(text, start=False, printing=True) - pos = len_pos - interval_size = len_interval_size - else: - # generate legend labels acc. to standard interval notation - interval_size = 100 // lcs_shading_num - pos = range(interval_size, 101+interval_size, interval_size) - - if bins != []: # labels provided - legend_labels = bins[:] - legend_labels.append("max") - legend_labels_lengths = [] - for item in bins: - legend_labels_lengths.append("[%d %s, %d %s)" % (item - min(bins), unit, item, unit)) - if len(bins) == len(colors) - 1: - legend_labels_lengths.append("[%d %s, %s]" % (max(bins), unit, u"\u221E")) # infinite - - else: - legend_labels = [] - legend_labels_lengths = [] - for idx in range(len(pos)): - num = pos[idx] - legend_labels.append("[%d%%, %d%%)" % (num - interval_size, num)) - if max_lcs_len != None: - num = len_pos[idx] - # as int or float - if num == int(num) and int(len_interval_size) == len_interval_size: - legend_labels_lengths.append("[%d %s, %d %s)" % (num, unit, num + len_interval_size, unit)) - else: - legend_labels_lengths.append("[%.2f %s, %.2f %s)" % (num, unit, num + len_interval_size, unit)) - legend_labels[-1] = "100" + unit - if max_lcs_len != None: - if num == int(num) and int(len_interval_size) == len_interval_size: - legend_labels_lengths[-1] = "%d %s" % (max_lcs_len, unit) - else: - legend_labels_lengths[-1] = "%.2f %s" % (max_lcs_len, unit) - - # set labels and choose file name - if gff_legend: - label_text = bins[:] - edge_col = None - legend_file_name = "Selfdotplot_GFF_Shading_Legend_n%d." % lcs_shading_num + filetype - elif max_lcs_len != None: - label_text = legend_labels_lengths[:] - edge_col = "black" - legend_file_name = "Polydotplot_LCS_Shading_Legend_max%d%s_n%d." % (max_lcs_len, unit, lcs_shading_num) + filetype - elif bins != []: - label_text = legend_labels_lengths[:] - edge_col = "black" - legend_file_name = "Polydotplot_LCS_Shading_Legend_%d%s_n%d." % (bins[0], unit, lcs_shading_num) + filetype - else: - label_text = legend_labels[:] - edge_col = "black" - legend_file_name = "Polydotplot_LCS_Shading_Legend_%%len_n%d." % lcs_shading_num + filetype - - if prefix != None and prefix != "": - if not prefix.endswith("-"): - prefix = prefix + "-" - legend_type = "LCS" - if prefix.startswith("custom-matrix"): - prefix = prefix.replace("custom-matrix", "")[1:] - legend_type = "CustomMatrix" - legend_file_name = prefix + legend_file_name.replace("LCS", legend_type) - - # plot legend figure - fig, ax = P.subplots(3, 1, figsize=(len(colors)*2, len(colors)*2)) - for idx in range(len(colors)): - ax[0].bar(data_points[idx]+1, data_points[idx]+1, color=colors[idx], label=label_text[idx], - alpha=alphas[idx], edgecolor=edge_col) - ax[1].bar(data_points[idx]+1, 0, color=colors[idx], label=label_text[idx], - alpha=alphas[idx], edgecolor=edge_col) - ax[2].bar(data_points[idx]+1, 0, color=colors[idx], label=label_text[idx], - alpha=alphas[idx], edgecolor=edge_col) - ax[1].set_ylim(0,1) - ax[2].set_ylim(0,1) - ax[1].legend(ncol=((len(colors)-1)//max_legend_length_row)+1, framealpha=1) # vertical legend - col_num = len(colors) - if len(colors) > max_legend_length_col: - remainder = 0 - if len(colors) % max_legend_length_col != 0: - remainder = 1 - row_num = len(colors) // max_legend_length_col + remainder - remainder = 0 - if len(colors) % row_num != 0: - remainder = 1 - col_num = len(colors) // row_num + remainder - ax[2].legend(ncol=col_num, framealpha=1) # horizontal legend - - P.savefig(legend_file_name) - - return legend_file_name - - -############################### -# Analysis Functions # -############################### - -def wobble_replacement(sequence, general_ambiguity_code, verbose=False): - """ - get all degenerated sequences for sequence with ambiguous residues - (only residues considered that are keys in wobble_dictionary) - """ - - # get positions of ambiguous residues - wobble_pos = [] - for idx in range(len(sequence)): - letter = sequence[idx] - if letter in general_ambiguity_code.keys(): - wobble_pos.append(idx) - - if verbose: - text = "\t%d wobbles" % len(wobble_pos) - logprint(text, start=False, printing=True) - - # replace one wobble through each iteration by all possible residues - # repeat if still wobbles in new kmers - kmer_variants = [sequence] - while True: - if verbose: - text = "\t\t%d kmer variants" % len(kmer_variants) - logprint(text, start=False, printing=True) - temp_kmers = set([]) - for kmer in kmer_variants: - for idx in wobble_pos: - letter = kmer[idx] - if letter in general_ambiguity_code.keys(): - for base in general_ambiguity_code[kmer[idx]]: - newkmer = kmer[:idx] + base + kmer[idx+1:] - temp_kmers.add(newkmer) - wobble = False - for kmer in temp_kmers: - for idx in range(len(kmer)): - letter = kmer[idx] - if letter in general_ambiguity_code.keys(): - wobble = True - break - if wobble: - break - kmer_variants = set(list(temp_kmers)[:]) - if not wobble: - break - - return kmer_variants - -def split_diagonals(data, stepsize=1): - """ - split array if point difference exceeds stepsize - data = sorted list of numbers - """ - return np.split(data, np.where(np.diff(data) != stepsize)[0]+1) - -def longest_common_substring(s1, s2): - m = [[0] * (1 + len(s2)) for i in xrange(1 + len(s1))] - longest, x_longest = 0, 0 - for x in xrange(1, 1 + len(s1)): - for y in xrange(1, 1 + len(s2)): - if s1[x - 1] == s2[y - 1]: - m[x][y] = m[x - 1][y - 1] + 1 - if m[x][y] > longest: - longest = m[x][y] - x_longest = x - else: - m[x][y] = 0 - return longest - -def lcs_from_x_values(x_values): - """ - calculate length of longest common substring based on nested list of numbers - """ - if len(x_values) == 0: - return 0 - # get lengths of each subarray data - lengths = np.array([len(i) for i in x_values]) - return max(lengths) - - -############################### -# Matching Functions # -############################### - -def find_match_pos_diag(seq1, seq2, wordsize, report_lcs=False, rc_option=True, convert_wobbles=False, max_N_percentage=49, type_nuc=True, verbose=False): - """ - find all matching positions with matches >= wordsize - convert matching points into lines of the length of the match - (+ optional handling of ambiguities) - """ - global t1 # timer - - # look for Ns in DNA or Xs in proeins (minimum word size) - if type_nuc == True: - any_residue = "N" - else: - any_residue = "X" - - # read sequences - seq_one = seq1.upper(); len_one = len(seq_one) - seq_two = seq2.upper(); len_two = len(seq_two) - - # set ambiguity code for wobble replacement - general_ambiguity_code = alphabets(type_nuc)[2] # nucleotide_ambiguity_code or aminoacid_ambiguity_code - - # forward - ################################# - kmer_pos_dict_one = {}; kmer_pos_dict_two = {} # dictionaries for both sequences - - # reverse complement - ################################# - kmer_pos_dict_three = {}; kmer_pos_dict_four = {} # dictionaries for both sequences - - # create dictionaries with kmers (wordsize) and there position(s) in the sequence - if rc_option: - data_list = [(str(seq_one), kmer_pos_dict_one), - (str(seq_two), kmer_pos_dict_two), - (str(seq_one), kmer_pos_dict_three), - (str(seq_two.reverse_complement()), kmer_pos_dict_four)] - else: - data_list = [(str(seq_one), kmer_pos_dict_one), - (str(seq_two), kmer_pos_dict_two)] - for (seq, kmer_pos_dict) in data_list: - for i in range(len(seq)-wordsize+1): - kmer = seq[i:i+wordsize] - # discard kmer, if too many Ns included - if kmer.count(any_residue)*100./wordsize <= max_N_percentage: - if not convert_wobbles: - try: - kmer_pos_dict[kmer].append(i) - except KeyError: - kmer_pos_dict[kmer] = [i] - else: - wobbles = False - for item in general_ambiguity_code.keys(): - if item in kmer: - wobbles = True - break - if not wobbles: - try: - kmer_pos_dict[kmer].append(i) - except KeyError: - kmer_pos_dict[kmer] = [i] - else: - kmer_variants = wobble_replacement(kmer, general_ambiguity_code) - for new_kmer in kmer_variants: - # print "\t", new_kmer - try: - kmer_pos_dict[new_kmer].append(i) - except KeyError: - kmer_pos_dict[new_kmer] = [i] - - # find kmers shared between both sequences - matches_for = set(kmer_pos_dict_one).intersection(kmer_pos_dict_two) # forward - matches_rc = set(kmer_pos_dict_three).intersection(kmer_pos_dict_four) # reverse complement - - if verbose: - text = "[matches: %i for; %.i rc]" % (len(matches_for), len(matches_rc)) - logprint(text, start=False, printing=True) - - # create lists of x and y co-ordinates for scatter plot - # keep all coordinates of all shared kmers (may match multiple times) - diag_dict_for = {} - diag_dict_rc = {} - for (match_list, pos_dict1, pos_dict2, diag_dict) in [(matches_for, kmer_pos_dict_one, kmer_pos_dict_two, diag_dict_for), - (matches_rc, kmer_pos_dict_three, kmer_pos_dict_four, diag_dict_rc)]: - for kmer in match_list: - for i in pos_dict1[kmer]: - for j in pos_dict2[kmer]: - diag = i-j - points = set(range(i+1, i+wordsize+1)) - if not diag in diag_dict.keys(): - diag_dict[diag] = points - else: - diag_dict[diag].update(points) - - # convert coordinate points to line start and stop positions - x1 = [] # x values reverse - y1 = [] # y values forward - for diag in diag_dict_for.keys(): - x_values = np.array(sorted(diag_dict_for[diag])) - x1.extend(split_diagonals(x_values)) - y_values = split_diagonals(x_values - diag) - y1.extend(y_values) - - x2 = [] # x values rc - y2 = [] # y values rc - if rc_option: - for diag in diag_dict_rc.keys(): - factor = len_two + diag + 1 - x_values = np.array(sorted(diag_dict_rc[diag])) - x2.extend(split_diagonals(x_values)) - y_values = split_diagonals(factor - x_values, -1) - y2.extend(y_values) - - if verbose: - t1 = time_track(t1) - - if not report_lcs: - return np.array(x1), np.array(y1), np.array(x2), np.array(y2) - else: - # get length of longest common substring based on match lengths - lcs_for = lcs_from_x_values(x1) - lcs_rev = lcs_from_x_values(x2) - return np.array(x1), np.array(y1), np.array(x2), np.array(y2), lcs_for, lcs_rev - -def find_match_pos_regex(seq1, seq2, wordsize, substitution_count=0, report_lcs=False, rc_option=True, convert_wobbles=False, max_N_percentage=49, type_nuc=True, verbose=False): - """ - find all matching positions with matches >= wordsize via regular expression search - fuzzy matching - allow up to substitution_count substitutions - convert matching points into lines of the length of the match - (+ optional handling of ambiguities) - """ - global t1 # timer - - # read sequences - seq_one = seq1.upper(); len_one = len(seq_one) - seq_two = seq2.upper(); len_two = len(seq_two) - - # set ambiguity code for wobble replacement - general_ambiguity_code = alphabets(type_nuc)[2] # nucleotide_ambiguity_code or aminoacid_ambiguity_code - ambiguity_match_dict = alphabets(type_nuc)[3] - - ambiq_residues = "[%s]" % "".join(general_ambiguity_code.keys()) - - # look for Ns in DNA or Xs in proeins (minimum word size) - if type_nuc == True: - any_residue = "N" - else: - any_residue = "X" - - # check for wobble presence - if not (regex.search(ambiq_residues, str(seq_one)) == None and regex.search(ambiq_residues, str(seq_two)) == None): - wobble_found = True - else: - wobble_found = False - - # dictionary for matches - diag_dict_for = {} - diag_dict_rc = {} - counter = [0, 0] - - # one-way matching - if rc_option: - data_list = [(str(seq_one), str(seq_two), diag_dict_for, 0), - (str(seq_one), str(seq_two.reverse_complement()), diag_dict_rc, 1)] - else: - data_list = [(str(seq_one), str(seq_two), diag_dict_for, 0)] - - for seq_query, seq_target, diag_dict, counter_pos in data_list: - # split query sequence into kmers - if not rc_option and counter_pos == 1: - break - - for idx in range(len(str(seq_query))-wordsize+1): - kmer = str(seq_query)[idx:idx+wordsize] - - # skip excessive N/X stretches (big black areas) - if kmer.count(any_residue)*100./wordsize <= max_N_percentage: - # convert kmer to regular expression for wobble_matching - if convert_wobbles and wobble_found: - kmer_string = "" - # replace each residue with matching residues or wobbles - for jdx in range(len(kmer)): - kmer_string += ambiguity_match_dict[kmer[jdx]] - else: - kmer_string = kmer - - # convert to regular expression tolerating substitution errors - if type(substitution_count) == int and substitution_count != 0: - kmer_string = "(%s){s<=%d}" % (kmer_string, substitution_count) - - # search for regular expression in target sequence - kdx = 0 - start = True - if regex.search(kmer_string, seq_target[kdx:]) != None: - counter[counter_pos] += 1 - while regex.search(kmer_string, seq_target[kdx:]) != None: - # search for regular expression pattern in target sequence - result = regex.search(kmer_string, seq_target[kdx:]) - - kmer2 = seq_target[kdx:][result.start():result.end()] - - # skip excessive N/X stretches (big black areas) - if kmer2.count(any_residue)*100./wordsize <= max_N_percentage: - diag = idx-(kdx+result.start()) - points = set(range(idx+1, idx+wordsize+1)) - if not diag in diag_dict.keys(): - diag_dict[diag] = points - else: - diag_dict[diag].update(points) - - kdx += result.start() + 1 - if kdx >= len(seq_target): - break - elif regex.search(kmer_string, seq_target[kdx:]) != None: - counter[counter_pos] += 1 - - if verbose: - text = "%5.i \tforward matches" % counter[0] - text += "\n%5.i \treverse complementary matches" % counter[1] - logprint(text, start=False, printing=True) - - # convert coordinate points to line start and stop positions - x1 = [] # x values reverse - y1 = [] # y values forward - for diag in diag_dict_for.keys(): - x_values = np.array(sorted(diag_dict_for[diag])) - x1.extend(split_diagonals(x_values)) - y_values = split_diagonals(x_values - diag) - y1.extend(y_values) - - x2 = [] # x values rc - y2 = [] # y values rc - if rc_option: - for diag in diag_dict_rc.keys(): - factor = len_two + diag + 1 - x_values = np.array(sorted(diag_dict_rc[diag])) - x2.extend(split_diagonals(x_values)) - y_values = split_diagonals(factor - x_values, -1) - y2.extend(y_values) - - if verbose: - t1 = time_track(t1) - - if not report_lcs: - return np.array(x1), np.array(y1), np.array(x2), np.array(y2) - else: - # get length of longest common substring based on match lengths - lcs_for = lcs_from_x_values(x1) - lcs_rev = lcs_from_x_values(x2) - return np.array(x1), np.array(y1), np.array(x2), np.array(y2), lcs_for, lcs_rev - - -############################### -# Dot Plot Functions # -############################### - -def selfdotplot(input_fasta, wordsize, prefix=None, plot_size=10, label_size=10, filetype='png', type_nuc=True, convert_wobbles=False, substitution_count=0, alphabetic_sorting=False, max_N_percentage=49, verbose=False, multi=True, ncols=4, nrows=5, gff_files=[], gff_color_dict={"others": ("grey", 1, 0)}, title_length=float("Inf")): - """ - self-against-self dotplot - partially from biopython cookbook - """ - - # read sequences - seq_dict, sequences = read_seq(input_fasta) - if seq_dict == {}: - logprint("\nFailed to load sequences") - return [] - - if alphabetic_sorting: - sequences = sorted(sequences) - - # check if at least one input sequence - if len(sequences) == 0: - text = "\n%s\n\nCreating %s selfdotplot images\n%s\n\n=>" % (50*"=", len(sequences), 28*"-") - text += " No sequences provided for selfdotplot!\n\nTerminating polydotplot!" - logprint(text, start=False, printing=True) - return - elif len(sequences) == 1 and multi: - text = "\n\nCreating collage output for single selfdotplot!" - text += "\nRecommendation: Change to individual mode by using '--collage_output n'!\n\n" - logprint(text, start=False, printing=True) - - if multi and (ncols == 0 or nrows == 0): - ncols = max(ncols, 1) - nrows = max(nrows, 1) - text = "\n\nSelfdotplot Collage: Invalid collage - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - if multi and ncols > len(sequences): - ncols = len(sequences) - nrows = 1 - text = "\n\nSelfdotplot Collage: Few sequences - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - elif multi and ncols*(nrows-1) > len(sequences): - nrows = ((len(sequences)-1) // ncols) + 1 - text = "\n\nSelfdotplot Collage: Few sequences - correcting number of rows:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - if multi and not (nrows == 1 and ncols == 1) and plot_size <= label_size/2: - label_size = plot_size * 3 // 2 - text = "Reducing label size for better visualization to %d\n" % label_size - logprint(text, start=False, printing=True) - - - if gff_files != None and gff_files != []: - text = "\n%s\n\nReading %s GFF annotation files\n%s\n\n=> %s\n" % (50*"=", len(gff_files), 28*"-", ", ".join(gff_files)) - logprint(text, start=False, printing=True) - feat_dict = read_gffs(gff_files, color_dict=gff_color_dict, type_nuc=type_nuc, prefix=prefix, filetype=filetype, verbose=verbose) - - # check input variables - if convert_wobbles and max_N_percentage > 49: - max_N_percentage=49 - text = "Provide valid max_N_percentage, kmers with >=50% Ns are ignored\n" - logprint(text, start=False, printing=True) - - if filetype not in ["png", "pdf", "svg"]: - text = "Provide valid file type - png, pdf, or svg - given:%s\n" % filetype - logprint(text, start=False, printing=True) - filetype = "png" - - global t1 - - print "\n%s\n\nCreating %s selfdotplot images\n%s\n\n=>" % (50*"=", len(sequences), 28*"-"), - log_txt = "\n%s\n\nCreating %s selfdotplot images\n%s\n\n=>" % (50*"=", len(sequences), 28*"-") - - # preparations for file name - name_graph = "Selfdotplots" - if prefix != None: - if not prefix[-1] == "-": - prefix = prefix + "-" - else: - prefix = "" - suffix = "" - if convert_wobbles: - suffix += "_wobbles" - if substitution_count != 0: - suffix += "_S%d" % substitution_count - if multi: - suffix += "_collage" - - # calculate fig ratios - if not multi: - ncols = 1 - nrows = 1 - figsize_x, figsize_y = calc_fig_ratio(ncols, nrows, plot_size) - - P.cla() # clear any prior graph - if multi: - fig = P.figure(figsize=(figsize_x, figsize_y)) - page_counter = 1 - list_of_png_names = [] - - counter = 0 - for seq_name in sequences: - print seq_name, - log_txt += " " + seq_name - - counter += 1 - if not multi: - P.cla() # clear any prior graph - - # read sequence - seq_record = seq_dict[seq_name] - name_seq = seq_record.id - seq_one = seq_record.seq.upper() - length_seq = len(seq_one) - - # get positions of matches - if substitution_count != 0: - # print "RE" - x_lists, y_lists, x_lists_rc, y_lists_rc = find_match_pos_regex(seq_one, seq_one, wordsize, substitution_count=substitution_count, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, type_nuc=type_nuc, verbose=verbose) - else: - # print "DIAG", - x_lists, y_lists, x_lists_rc, y_lists_rc = find_match_pos_diag(seq_one, seq_one, wordsize, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, type_nuc=type_nuc, verbose=verbose) - - # plotting with matplotlib - ################################# - - # combined plotting - if multi: - # plotting subplot with matplotlib - ax = P.subplot(nrows, ncols, counter) # rows, columns, plotnumber - - # shade annotated regions - if gff_files != None and gff_files != []: - if seq_name in feat_dict.keys(): - features = feat_dict[seq_name] - for item in features: - feat_type, start, stop = item - feat_color, strength, zoom = gff_color_dict[feat_type.lower()] - start = max(0, start - zoom - 0.5) - stop = min(length_seq+1, stop + zoom + 0.5) - width = stop - start - ax.add_patch(patches.Rectangle((start, start), # (x,y) - width, width, # width, height - edgecolor=None, linewidth=line_width+zoom, - fill=True, facecolor=feat_color, - alpha=strength)) - - # collect lines - lines = [] - color_list = [] - for (x_lines, y_lines, col) in [(x_lists_rc, y_lists_rc, line_col_rev), (x_lists, y_lists, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # format axes - P.xlim(0, length_seq+1) - P.ylim(length_seq+1, 0) # rotate y axis (point downwards) - P.xlabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.ylabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - P.title(unicode_name(shorten_name(name_seq, max_len=title_length)), fontsize=label_size, fontweight='bold') - # P.title(unicode_name(name_seq), fontsize=label_size*1.3, fontweight='bold') - - # save figure and reinitiate if page is full - if counter == ncols * nrows: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - P.subplots_adjust(hspace=0.5, wspace=0.5) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' % (prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() - - list_of_png_names.append(fig_name) - - counter = 0 - page_counter += 1 - - fig = P.figure(figsize=(figsize_x, figsize_y)) - - # plotting separate figure files - else: # not multi - - fig = P.figure(figsize=(plot_size, plot_size)) # figure size needs to be a square - ax = P.subplot(1, 1, 1) # rows, columns, plotnumber - - # shade annotated regions - if gff_files != None and gff_files != []: - if seq_name in feat_dict.keys(): - features = feat_dict[seq_name] - for item in features: - feat_type, start, stop = item - feat_color, strength, zoom = gff_color_dict[feat_type.lower()] - start = max(0, start - zoom - 0.5) - stop = min(length_seq+1, stop + zoom + 0.5) - width = stop - start - ax.add_patch(patches.Rectangle((start, start), # (x,y) - width, width, # width, height - edgecolor=None, linewidth=line_width+zoom, - fill=True, facecolor=feat_color, - alpha=strength)) - - # collect lines - lines = [] - number = 0 - color_list = [] - for (x_lines, y_lines, col) in [(x_lists_rc, y_lists_rc, line_col_rev), (x_lists, y_lists, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # format axes - P.xlim(0, length_seq+1) - P.ylim(length_seq+1, 0) # rotate y axis (point downwards) - P.xlabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.ylabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - P.title(unicode_name(shorten_name(name_seq, max_len=title_length)), fontsize=label_size*1.3, fontweight='bold') - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s-%d_%s_wordsize%i%s.%s' %(prefix, name_graph, counter, name_seq, wordsize, suffix, filetype) - P.savefig(fig_name, bbox_inches='tight') - - P.close() - P.cla() # clear any prior graph - - list_of_png_names.append(fig_name) - - if multi and counter >= 1: - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - P.subplots_adjust(hspace=0.5, wspace=0.5) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' %(prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() # clear any prior graph - - list_of_png_names.append(fig_name) - - print "\n\nDrawing selfdotplots done" - log_txt += "\n\nDrawing selfdotplots done" - logprint(log_txt, start=False, printing=False) - - return list_of_png_names - -def pairdotplot(input_fasta, wordsize, prefix=None, plot_size=10, label_size=10, filetype='png', type_nuc=True, convert_wobbles=False, substitution_count=0, alphabetic_sorting=False, max_N_percentage=49, verbose=False, multi=True, ncols=4, nrows=5, length_scaling=True, scale_delim_col="red"): - """ - pairwise dotplot (all-against-all) - """ - - # read sequences - seq_dict, sequences = read_seq(input_fasta) - if seq_dict == {}: - logprint("\nFailed to load sequences") - return [] - - if alphabetic_sorting: - sequences = sorted(sequences) - - # check if at least two input sequences - if len(sequences) < 2: - text = "\n%s\n\nCreating %d paired dotplot image \n%s\n\n=>" % (50*"=", len(sequences)*(len(sequences)-1)/2, 36*"-") - text += " Please provide at least two sequences for pairdotplot!\n\nTerminating paired dotplot!" - logprint(text, start=False, printing=True) - return - elif len(sequences) == 2 and multi: - text = "\n\nCreating collage output for single pairdotplot!" - text += "\nRecommendation: Change to individual mode by using '--collage_output n'!\n\n" - logprint(text, start=False, printing=True) - - if multi and (ncols == 0 or nrows == 0): - ncols = max(ncols, 1) - nrows = max(nrows, 1) - text = "\n\nPairdotplot Collage: Invalid collage settings - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - if multi and ncols > len(sequences)*(len(sequences)-1): - ncols = len(sequences) - nrows = 1 - text = "\n\nPairdotplot Collage: Few sequences - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - elif multi and ncols*(nrows-1) > len(sequences)*(len(sequences)-1): - nrows = ((len(sequences)-1) // ncols) + 1 - text = "\n\nPairdotplot Collage: Few sequences - correcting number of rows:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - - text = "\n%s\n\nCreating %d paired dotplot image for\n%s\n\n=>" % (50*"=", len(sequences)*(len(sequences)-1)/2, 36*"-") - text += ", ".join(sequences) + "\n" - logprint(text, start=False, printing=True) - - if multi and not (nrows == 1 and ncols == 1) and plot_size <= label_size/2: - label_size = plot_size * 3 // 2 - text = "Reducing label size for better visualization to %d\n" % label_size - logprint(text, start=False, printing=True) - - y_label_rotation = "vertical" - - # check input variables - if convert_wobbles and max_N_percentage > 49: - max_N_percentage=49 - text = "Provide valid max_N_percentage, kmers with >50% are ignored\n" - logprint(text, start=False, printing=True) - - if filetype not in ["png", "pdf", "svg"]: - text = "Provide valid file type - png, pdf, or svg - given: %s\n" % filetype - logprint(text, start=False, printing=True) - filetype = "png" - - # preparations for file name - name_graph = "Pairdotplot" - if prefix != None: - if not prefix[-1] == "-": - prefix = prefix + "-" - else: - prefix = "" - suffix = "" - if convert_wobbles: - suffix += "_wobbles" - if substitution_count != 0: - suffix += "_S%d" % substitution_count - if length_scaling: - suffix += "_scaled" - if multi: - suffix += "_collage" - - - - # calculate fig ratios - if not multi: - ncols = 1 - nrows = 1 - figsize_x, figsize_y = calc_fig_ratio(ncols, nrows, plot_size) - - P.cla() # clear any prior graph - list_of_png_names = [] - if multi: - fig = P.figure(figsize=(figsize_x, figsize_y)) - page_counter = 1 - - # prepare LCS data file - lcs_data_file = open("%sPairdotplot_lcs_data_file%s.txt" % (prefix, suffix.replace("_scaled", "").replace("_collage", "")), 'w') - lcs_data_file.write("\t".join(["#title1", "title2", "len_seq1", "len_seq2", "len_lcs_for", "%_min_seq_len", "len_lcs_rev", "%_min_seq_len"])+"\n") - - counter, seq_counter = 0, 0 - print "Drawing pairwise dotplot...", - log_txt = "Drawing pairwise dotplot..." - if verbose: - seq_text = "" - for idx in range(len(sequences)-1): - if verbose: - print "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]), - seq_text += "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]) - rec_two = seq_dict[sequences[idx]] - name_two = rec_two.id - seq_two = rec_two.seq - len_two = len(seq_two) - - for jdx in range(idx+1, len(sequences)): - rec_one = seq_dict[sequences[jdx]] - name_one = rec_one.id - seq_one = rec_one.seq - len_one = len(seq_one) - - counter += 1 - seq_counter += 1 - if verbose: - print sequences[jdx], - seq_text += " " + sequences[jdx] - elif not seq_counter % 25: - print seq_counter, - log_txt += " " + str(seq_counter) - - # get positions of matches - if substitution_count != 0: - # print "RE" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_regex(seq_one, seq_two, wordsize, substitution_count=substitution_count, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - else: - # print "DIAG" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_diag(seq_one, seq_two, wordsize, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - - # write LCS data file - lcs_data_file.write("\t".join([name_one, name_two, str(len_one), str(len_two), - str(lcs_for), str(round((lcs_for*100./min(len_one, len_two)), 3)), - str(lcs_rev), str(round((lcs_rev*100./min(len_one, len_two)), 3))]) + "\n") - - - # plotting with matplotlib - ################################# - - # combined plotting - if multi: - # plotting subplot with matplotlib - ax = P.subplot(nrows, ncols, counter) # rows, columns, plotnumber - else: - # calculate figure size for separate figures - if len_one >= len_two: - sizing = (plot_size, max(2, (plot_size)*len_two*1./len_one)) - # sizing = (plot_size, min(plot_size, max(2, (plot_size-2)*len_two*1./len_one+2))) - else: - sizing = (max(2, (plot_size)*len_one*1./len_two), plot_size) - # sizing = (min(plot_size, max(2, (plot_size-2)*len_one*1./len_two+2)), plot_size) - fig = P.figure(figsize=(plot_size, plot_size)) - - ax = P.subplot(1, 1, 1) - - # collect lines - lines = [] - color_list = [] - for (x_lines, y_lines, col) in [(x2, y2, line_col_rev), (x1, y1, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # format axes - P.xlabel(unicode_name(shorten_name(name_one, max_len=title_length)) + " [%s]" % aa_bp_unit, fontsize=label_size, fontweight='bold', labelpad=4) - P.ylabel(unicode_name(shorten_name(name_two, max_len=title_length)) + " [%s]" % aa_bp_unit, fontsize=label_size, fontweight='bold', labelpad=4) - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - - if not multi: - if length_scaling: - ax.set_aspect(aspect='equal', adjustable='box', anchor='NW') - P.xlim(0, len_one+1) - P.ylim(len_two+1, 0) # rotate y axis (point downwards) - elif not length_scaling: - P.xlim(0, len_one+1) - P.ylim(len_two+1, 0) # rotate y axis (point downwards) - else: - max_len = max(len_one, len_two) - P.xlim(0, max_len+1) - P.ylim(max_len+1, 0) # rotate y axis (point downwards) - - # plot line deliminating shorter sequence - if max_len != len_one: - ax.plot((len_one+1, len_one+1), (0, len_two), marker="", linestyle="--", color=scale_delim_col, markerfacecolor="r") - if max_len != len_two: - ax.plot((0, len_one), (len_two+1, len_two+1), marker="", linestyle="--", color=scale_delim_col, markerfacecolor="r") - - # evtl. switch x axis position - if x_label_pos_top: - ax.xaxis.tick_top() - ax.xaxis.set_label_position('top') - P.setp(ax.get_xticklabels(), fontsize=label_size*.9) - P.setp(ax.get_yticklabels(), fontsize=label_size*.9) - - # save figure and reinitiate if page is full - if multi and counter == ncols * nrows: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - if x_label_pos_top: - P.subplots_adjust(hspace=.5, wspace=.5, top=0.95) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=.5, wspace=.5, bottom=0.05) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' %(prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() - - list_of_png_names.append(fig_name) - - counter = 0 - page_counter += 1 - - fig = P.figure(figsize=(figsize_x, figsize_y)) - - # plotting separate figure files - elif not multi: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - if y_label_rotation == "horizontal": - if x_label_pos_top: - P.subplots_adjust(hspace=0.02, wspace=0.02, left=0.13, top=0.95) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=0.02, wspace=0.02, left=0.13, bottom=0.05) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=0.02, wspace=0.02) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s-%d_wordsize%i%s.%s' % (prefix, name_graph, counter, wordsize, suffix, filetype) - P.savefig(fig_name) - P.close() - P.cla() - - list_of_png_names.append(fig_name) - fig = P.figure() - - # save figure - if multi and counter >= 1: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - if x_label_pos_top: - P.subplots_adjust(hspace=0.5, wspace=0.5, top=0.95) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=0.5, wspace=0.5, bottom=0.05) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' %(prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() - - list_of_png_names.append(fig_name) - - if not verbose: - print seq_counter, "done" - log_txt += str(seq_counter) + " done" - else: - print "\n%d done" % seq_counter - log_txt += "\n%d done" % seq_counter - logprint(log_txt, start=False, printing=False) - - if verbose: - print - logprint(seq_text, start=False, printing=False) - - return list_of_png_names - -def polydotplot(input_fasta, wordsize, prefix=None, plot_size=10, label_size=10, filetype='png', type_nuc=True, convert_wobbles=False, substitution_count=0, alphabetic_sorting=False, max_N_percentage=49, verbose=False, lcs_shading=True, lcs_shading_ref=0, lcs_shading_interval_len=100, lcs_shading_ori=0, lcs_shading_num=5, spacing=0.04, input_user_matrix_file="", user_matrix_print=True): - """ - all-against-all dotplot - derived from dotplot function - - lcs_shading_refs: - 0 color relative to maximum lcs observed in dataset [default] - 1 color by coverage of shorter sequence (e.g. lcs = 70% of seq1) - lcs_shading_ori - 0 forward only - 1 reverse only - 2 both orientations (in opposite plot) - """ - - # read sequences - seq_dict, sequences = read_seq(input_fasta) - if seq_dict == {}: - logprint("\nFailed to load sequences") - return [] - - if alphabetic_sorting: - sequences = sorted(sequences) - - if len(sequences) == 0: - text = "\n%s\n\nCreating %dx%d polydotplot image\n%s\n\n=>" % (50*"=", len(sequences), len(sequences), 30*"-") - text += " No sequences provided for polydotplot!\n\nTerminating polydotplot!" - logprint(text, start=False, printing=True) - return - elif len(sequences) == 1: - text = "\n\nCreating polydotplot for single sequence!" - text += "\nRecommendation: Use selfdotplot via '--plotting_mode 0'!\n\n" - logprint(text, start=False, printing=True) - - - text = "\n%s\n\nCreating %dx%d polydotplot image\n%s\n\n=>" % (50*"=", len(sequences), len(sequences), 30*"-") - text += " " + " ".join(sequences) + "\n" - logprint(text, start=False, printing=True) - - # check input variables - if convert_wobbles and max_N_percentage > 49: - max_N_percentage=49 - text = "Provide valid max_N_percentage, kmers with >50% are ignored\n" - logprint(text, start=False, printing=True) - - if filetype not in ["png", "pdf", "svg"]: - text = "Provide valid file type - png, pdf, or svg - given: %s\n" % filetype - logprint(text, start=False, printing=True) - filetype = "png" - - if lcs_shading and not type_nuc: - if lcs_shading_ori != 0: - lcs_shading_ori = 0 - text = "Protein shading does not support reverse complementary matching!\n" - logprint(text, start=False, printing=True) - - # read custom shading matrix & match names of sequences to fasta - if input_user_matrix_file != "" and input_user_matrix_file != None: - logprint("Reading user matrix file: %s" % input_user_matrix_file) - # lcs_shading_ori = 2 - custom_dict = read_matrix(input_user_matrix_file) - if custom_dict != {}: - custom_shading = True - custom_similarity_dict = {} - invalid_entries = [] - custom_max = 0 - custom_min = float("Inf") - for key in custom_dict.keys(): - number_key = [] - - # convert number into float - try: - value = float(custom_dict[key]) - if not "." in custom_dict[key]: - value = int(custom_dict[key]) - custom_max = max(custom_max, value) - custom_min = min(custom_min, value) - except: - value = custom_dict[key] - if value == "": - value = None - invalid_entries.append(key) - # match matrix names with sequence names - for item in key: - if item in sequences: - number_key.append(sequences.index(item)) - else: - number_key.append(-1) - # dictionary with tuple of sorted sequence indices as key and number as value - custom_similarity_dict[tuple(sorted(number_key))] = value - if len(invalid_entries) != 0: - text = "No valid number in custom similarity matrix for %d entries: \n\t" % (len(invalid_entries)) - for key in invalid_entries: - text += str(key) + " - " + str(custom_dict[key]) + "; " - logprint(text[:-2]+"\n") - - text = "Custom user matrix given: min %.2f, max %.2f\n" % (custom_min, custom_max) - - # artificially rounding intervals if likely identity/divergence percentages - if 0 <= custom_min < 1 and 0 < custom_max <= 1: - rounding_factor = 5 - multi_factor = 100 - text += " > artificially rounding custom shading intervals: old (%.2f, %.2f) - " % (custom_min, custom_max) - custom_min = max(0, (multi_factor*custom_min // rounding_factor) * (1.*rounding_factor/multi_factor)) - custom_max = min((multi_factor*custom_max // rounding_factor) * (1.*rounding_factor/multi_factor), 1) - text += "new (%.2f, %2f)\n" % (custom_min, custom_max) - - elif 0 <= custom_min < 100 and 0 < custom_max <= 100: - rounding_factor = 5 - text += " > artificially rounding custom shading intervals: old (%.2f, %.2f) - " % (custom_min, custom_max) - custom_min = max(0, (custom_min // rounding_factor) * rounding_factor) - custom_max = min((custom_max // rounding_factor) * rounding_factor, 100) - text += "new (%d, %d)\n" % (custom_min, custom_max) - - logprint(text) - - else: - custom_shading = False - - name_graph = "Polydotplot" - suffix = "" - if convert_wobbles: - suffix += "_wobbles" - if substitution_count != 0: - suffix += "_S%d" % substitution_count - if custom_shading: - suffix += "_matrix" - if lcs_shading: - suffix += "_%dshades_ref%d_ori%s" % (lcs_shading_num+1, lcs_shading_ref, lcs_shading_ori) - if "ref2" in suffix and type_nuc: - suffix = suffix.replace("ref2", "%dbp" % lcs_shading_interval_len) - elif "ref2" in suffix: - suffix = suffix.replace("ref2", "%daa" % lcs_shading_interval_len) - - - # name and create output files (names derived from SEQNAME) - if prefix != None and str(prefix) != "": - prefix = str(prefix) + "-" - else: - prefix = "" - - # preparations for background shading - if lcs_shading or custom_shading: - # create color range white to grey - colors = create_color_list(lcs_shading_num+1, color_map=None, logging=True) - colors_2 = create_color_list(lcs_shading_num+1, color_map="OrRd", logging=True) - - if custom_shading: - text = "Custom Matrix Colors: " + ", ".join(colors_2) - - # write lcs lengths to file - lcs_data_file = open("%sPolydotplot_lcs_data_file%s.txt" % (prefix, suffix.replace("_scaled", "").replace("_collage", "")), 'w') - lcs_data_file.write("\t".join(["#title1", "title2", "len_seq1", "len_seq2", "len_lcs_for", "%_min_seq_len", "len_lcs_rev", "%_min_seq_len"])+"\n") - - # compare sequences pairwise - save lcs and line information in dictionary for plotting - data_dict = {} # keys = tuple(idx, jdx), value = x1, y1, x2, y2 (line positions) - lcs_dict = {} # keys = tuple(idx, jdx), value = length of lcs: lcs_len or (lcs_for, lcs_rev) - for_lcs_set = set([]) # keep lengths to calculate max (excluding self comparisons) - rev_lcs_set = set([]) # keep lengths to calculate max (all) - - text = "\nTotal plot count: %d" % (len(sequences)*(len(sequences))) - text += "\nTotal calculations: %d" % (len(sequences)*(len(sequences)+1)/2) - logprint(text, start=False, printing=True) - - print "\nCalculating shared regions and lengths of longest_common_substring...", - log_txt = "\nCalculating shared regions and lengths of longest_common_substring..." - # determine matches and length of lcs by comparing all sequence pairs - if verbose: - seq_text = "" - counter = 0 - for idx in range(len(sequences)): - if verbose: - print "\n%d\t%s vs." % ((counter+1), sequences[idx]), - seq_text += "\n%d\t%s vs." % ((counter+1), sequences[idx]) - rec_two = seq_dict[sequences[idx]] - name_two = rec_two.id - seq_two = rec_two.seq - len_two = len(seq_two) - - for jdx in range(idx, len(sequences)): - rec_one = seq_dict[sequences[jdx]] - name_one = rec_one.id - seq_one = rec_one.seq - len_one = len(seq_one) - - counter += 1 - if verbose: - print sequences[jdx], - seq_text += " " + sequences[jdx] - elif len(sequences) < 5: - print "\t%s (%d %s), %s (%d %s)" % (name_one, len_one, aa_bp_unit, name_two, len_two, aa_bp_unit) - log_txt += "\t%s (%d %s), %s (%d %s)\n" % (name_one, len_one, aa_bp_unit, name_two, len_two, aa_bp_unit) - else: - if not counter % 25: - print counter, - log_txt += str(counter) - - # get positions of matches & length of longest common substring based on match lengths - if substitution_count != 0: - # print "RE" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_regex(seq_one, seq_two, wordsize, substitution_count=substitution_count, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - else: - # print "DIAG" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_diag(seq_one, seq_two, wordsize, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - data_dict[(idx, jdx)] = x1[:], y1[:], x2[:], y2[:] - lcs_dict[idx, jdx] = lcs_for, lcs_rev - - if idx != jdx: - for_lcs_set.add(lcs_for) - rev_lcs_set.add(lcs_rev) - - lcs_data_file.write("\t".join([name_one, name_two, str(len_one), str(len_two), - str(lcs_for), str(round((lcs_for*100./min(len_one, len_two)), 3)), - str(lcs_rev), str(round((lcs_rev*100./min(len_one, len_two)), 3))]) + "\n") - - if not verbose: - print len(sequences)*(len(sequences)+1)/2, " done\n" - log_txt += str(len(sequences)*(len(sequences)+1)/2) + " done\n" - else: - print "\n%d done" % (len(sequences)*(len(sequences)+1)/2) - log_txt += "\n%d done" % (len(sequences)*(len(sequences)+1)/2) - logprint(log_txt, start=False, printing=False) - - if verbose: - logprint ("\n\nlcs_dict\n" + str(lcs_dict)) - if custom_shading: - logprint ("\ncustom_dict\n" + str(custom_dict)) - logprint ("\ncustom_similarity_dict\n\n" + str(custom_similarity_dict)) - - if verbose: - print - logprint(seq_text+"\n", start=False, printing=False) - - if lcs_shading_ref == 2: - color_bins = [] - text = "\nLCS lengh bins: " - for idx in range(lcs_shading_num): - color_bins.append(lcs_shading_interval_len*(idx+1)) - text += " " + str(lcs_shading_interval_len*(idx+1)) - logprint(text, start=False, printing=True) - - # calculate maximum lcs length - if lcs_shading_ori == 0: # forward only - if len(for_lcs_set) != 0: - max_lcs = max(for_lcs_set) - else: - max_lcs = None - elif lcs_shading_ori == 1: # reverse complement only - if len(rev_lcs_set) != 0: - max_lcs = max(rev_lcs_set) - else: - max_lcs = None - else: # both orientations - if len(rev_lcs_set) != 0 and len(for_lcs_set) != 0: - max_lcs = max(max(rev_lcs_set), max(for_lcs_set)) - elif len(rev_lcs_set) != 0: - max_lcs = max(rev_lcs_set) - elif len(for_lcs_set) != 0: - max_lcs = max(for_lcs_set) - else: - max_lcs = None - - if not max_lcs == None: - text = "Maximum LCS: %d %s" % (max_lcs, aa_bp_unit) - logprint(text, start=False, printing=True) - if custom_shading: - text = "Maximum custom value: %d\n" % custom_max - logprint(text, start=False, printing=True) - - # count sequences - ncols = len(sequences); nrows = len(sequences) - - # get sequence lengths to scale plot widths and heights accordingly - size_ratios = [] - for item in sequences: - size_ratios.append(len(seq_dict[item].seq)) - - P.cla() # clear any prior graph - # use GridSpec to resize plots according to sequence length - gs = gridspec.GridSpec(nrows, ncols, - width_ratios=size_ratios, - height_ratios=size_ratios) - fig = P.figure(figsize=(plot_size, plot_size)) - - # determine label orientations - if len(sequences) > 5: - x_label_rotation = 45 - y_label_rotation = "horizontal" - if x_label_pos_top: - xhalign = 'left' - xvalign = 'bottom' - else: - xhalign = 'right' - xvalign = 'top' - yhalign = "right" - else: - x_label_rotation = "horizontal" - y_label_rotation = "vertical" - xvalign = "center" - xhalign = "center" - yhalign = "center" - yvalign = 'center' - - print "\nDrawing polydotplot...", - log_txt = "\nDrawing polydotplot..." - - # draw subplots - if verbose: - if lcs_shading and custom_shading: - lcs_text = "\n" + "\t".join(["#Seq1", "Seq2", "LCS for [%s]" %aa_bp_unit, "LCS for [%s]" %aa_bp_unit, "Custom matrix value", "Matrix color index", "LCS color index"]) + "\n" - elif lcs_shading: - lcs_text = "\n" + "\t".join(["#Seq1", "Seq2", "LCS for [%s]" %aa_bp_unit, "LCS for [%s]" %aa_bp_unit, "LCS color index for", "LCS color index rev"]) + "\n" - elif custom_shading: - lcs_text = "\n" + "\t".join(["#Seq1", "Seq2", "Custom matrix value", "Color index for", "Color index rev"]) + "\n" - - if verbose: - seq_text = "" - counter, seq_counter = 0, 0 - for idx in range(len(sequences)): - if verbose: - print "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]), - seq_text += "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]) - rec_two = seq_dict[sequences[idx]] - len_two = len(rec_two.seq) - name_two = rec_two.id - - for jdx in range(idx, len(sequences)): - rec_one = seq_dict[sequences[jdx]] - len_one = len(rec_one.seq) - name_one = rec_one.id - - counter += 1 - seq_counter += 1 - if verbose: - print sequences[jdx], - seq_text += " " + sequences[jdx] - elif not seq_counter % 25: - print seq_counter, - log_txt += str(seq_counter) - - # optional shade background according to length of LCS and/or user matrix - ######################################################################### - - # get interval based on LCS - background_colors = [None, None] - if lcs_shading and (lcs_shading_ref==1 or lcs_shading_ref==2 or max_lcs!=None): # self plot max_lcs_for == None - lcs_len = lcs_dict[(idx, jdx)] - l1 = lcs_len[0] # forward - l2 = lcs_len[1] # reverse complement - - lcs_shading_bool = True - - # calculate shading acc. to chosen option - if lcs_shading_ref == 1: # percentage of shorter sequence - color_idx0 = min(len(colors)-1, l1*lcs_shading_num // min(len_one, len_two)) - color_idx1 = min(len(colors)-1, l2*lcs_shading_num // min(len_one, len_two)) - elif lcs_shading_ref == 2: # by given interval size - color_idx0 = min(len(colors)-1, l1 // lcs_shading_interval_len) - color_idx1 = min(len(colors)-1, l2 // lcs_shading_interval_len) - if color_idx0 >= len(colors): - color_idx0 = len(colors) - if color_idx1 >= len(colors): - color_idx1 = len(colors) - else: # percentage of maximum lcs length - color_idx0 = min(len(colors)-1, l1*lcs_shading_num // max_lcs) - color_idx1 = min(len(colors)-1, l2*lcs_shading_num // max_lcs) - else: - lcs_shading_bool = False - - # get interval based on custom matrix - if custom_shading: - # matrix value - try: - custom_value = custom_similarity_dict[(idx, jdx)] - except: - custom_value = "" - - # bottom left triangle = LCS forward/reverse or best of both - if lcs_shading_bool: - if lcs_shading_ori == 0: # forward - color_idx1 = color_idx0 - elif lcs_shading_ori == 2: # both directions - color_idx1 = max(color_idx0, color_idx1) - - # top right triangle = custom value (not colored if text matrix provided) - if type(custom_value) == int or type(custom_value) == float: - color_idx0 = int((custom_value-custom_min)*lcs_shading_num // (custom_max-custom_min)) - # if string is proviced - else: - color_idx0 = 0 - - # set colors dependent on lcs dependent on orientation - if lcs_shading_bool and not custom_shading: - if idx != jdx: - if lcs_shading_ori == 0: - color_idx1 = color_idx0 - elif lcs_shading_ori == 1: - color_idx0 = color_idx1 - background_colors[0] = colors[color_idx0] - background_colors[1] = colors[color_idx1] - # for selfcomparison, only color reverse complement - elif lcs_shading_ori != 0 and not custom_shading: - background_colors[0] = colors[color_idx1] - # set different colors for shading by LCS + user matrix - elif lcs_shading_bool and custom_shading: - # print colors, background_colors, color_idx0, color_idx1 - background_colors[0] = colors_2[color_idx0] - background_colors[1] = colors[color_idx1] - # set grey color range for user matrix if no LCS shading - elif custom_shading: - background_colors[0] = colors[color_idx0] - background_colors[1] = colors[color_idx0] - - if verbose: - if custom_shading and lcs_shading_bool: - lcs_text += "\t".join([name_one, name_two, str(lcs_len[0]), str(lcs_len[1]), str(custom_value), str(color_idx0), str(color_idx1)]) + "\n" - elif lcs_shading_bool: - lcs_text += "\t".join([name_one, name_two, str(lcs_len[0]), str(lcs_len[1]), str(color_idx0), str(color_idx1)]) + "\n" - elif custom_shading: - lcs_text += "\t".join([name_one, name_two, str(custom_value), str(color_idx0), str(color_idx1)]) + "\n" - - # diagonal (self-dotplots) - if idx == jdx: - # skip positions below diagonal - counter = counter + (counter - 1) // (nrows) # + row_pos - counters = [counter] - # draw both graphs at once (due to symmetry) - else: - col_pos = (counter - 1) % ncols - row_pos = (counter - 1) // (nrows) - counter2 = col_pos * ncols + row_pos + 1 - counters = [counter, counter2] - - if len(counters) == 2: - seq_counter += 1 - if not verbose and not seq_counter % 25: - print seq_counter, - log_txt += str(seq_counter) - - x_lists, y_lists, x_lists_rc, y_lists_rc = data_dict[(idx, jdx)] - - # plot diagram(s) - for kdx in range(len(counters)): - # if custom matrix value printed into upper matrix triangle, skip data plotting - - # text print in top triangle - if user_matrix_print and custom_shading and kdx==0 and idx!=jdx: - data_plotting = False - # dotplot in bottom triangle - else: - data_plotting = True - - fig_pos = counters[kdx] - # plotting subplot with matplotlib - ax = P.subplot(gs[fig_pos-1]) # rows, columns, plotnumber - - # mirror plot, if plotting below diagonal - if kdx == 0: - l1, l2 = len_one, len_two - n1, n2 = name_one, name_two - x1, y1 = x_lists, y_lists - x2, y2 = x_lists_rc, y_lists_rc - else: - l2, l1 = len_one, len_two - n2, n1 = name_one, name_two - x1, y1 = y_lists, x_lists - x2, y2 = y_lists_rc, x_lists_rc - - if data_plotting: - # collect lines - lines = [] - color_list = [] - for (x_lines, y_lines, col) in [(x2, y2, line_col_rev), (x1, y1, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # plot value provided by customer instead of dotplot - else: - alignment = {'horizontalalignment': 'center', 'verticalalignment': 'center'} - # P.text(0.5, 0.5, custom_value, size='medium', transform=ax.transAxes, **alignment) - P.text(0.5, 0.5, custom_value, size=label_size*1.5, transform=ax.transAxes, **alignment) - # P.text(0.5, 0.5, custom_value, size=label_size*1.5, transform=ax.transAxes, - # horizontalalignment='center', verticalalignment='center', color="black") - - if custom_shading: - # omit diagonal - if idx == jdx: - ax.set_facecolor("white") - # use white background for text fields (top right triangle only [kdx 0]) - elif type(custom_value) != int and type(custom_value) != float and kdx == 0: - ax.set_facecolor("white") - else: - ax.set_facecolor(background_colors[kdx]) - # set background color if lcs shading - elif lcs_shading_bool and background_colors[kdx] != None: - ax.set_facecolor(background_colors[kdx]) - - # set axis limits - P.xlim(0, l1+1) - P.ylim(l2+1, 0) # rotate y axis (point downwards) - - # determine axis positions - if x_label_pos_top: - ax.xaxis.tick_top() - ax.xaxis.set_label_position('top') - x_label_bool = fig_pos <= ncols - x_tick_bool = fig_pos > ncols*(ncols-1) - else: - x_label_bool = fig_pos > ncols*(ncols-1) - x_tick_bool = fig_pos <= ncols - - # x axis labels dependent on plot position/number - if x_label_bool: # x title and labels on top or bottom - P.xlabel(unicode_name(shorten_name(n1, max_len=title_length)), fontsize=label_size, rotation=x_label_rotation, verticalalignment=xvalign, horizontalalignment=xhalign, fontweight='bold', labelpad=8) # axis naming - if not x_label_rotation in ["horizontal", "vertical"]: - P.setp(ax.get_xticklabels(), fontsize=label_size*.9, rotation="vertical") - else: - P.setp(ax.get_xticklabels(), fontsize=label_size*.9, rotation=x_label_rotation) - elif x_tick_bool and x_label_pos_top: # x ticks on bottom row - ax.xaxis.tick_bottom() # ticks without labels on bottom - P.setp(ax.get_xticklabels(), fontsize=label_size, rotation=x_label_rotation, visible=False) - elif x_tick_bool: # x ticks on top row - ax.xaxis.tick_top() # # ticks without labels on top - P.setp(ax.get_xticklabels(), fontsize=label_size, rotation=x_label_rotation, visible=False) # inner diagrams without labelling - else: # no x ticks on internal rows - ax.axes.get_xaxis().set_visible(False) - - # y axis labels dependent on plot position/number - if fig_pos % ncols == 1 or (ncols == 1 and nrows == 1): # y title and labels in 1st column - P.ylabel(unicode_name(shorten_name(n2, max_len=title_length)), fontsize=label_size, rotation=y_label_rotation, verticalalignment=yvalign, horizontalalignment=yhalign, fontweight='bold', labelpad=8) - P.setp(ax.get_yticklabels(), fontsize=label_size*.9) # axis naming - elif fig_pos % ncols == 0: # y ticks in last column - ax.yaxis.tick_right() - P.setp(ax.get_yticklabels(), visible=False) # inner diagrams without labelling - else: - ax.axes.get_yaxis().set_visible(False) - - if not verbose: - print seq_counter, "done" - log_txt += str(seq_counter) + " done" - else: - print "\n%d done" % seq_counter - log_txt += "\n%d done" % seq_counter - logprint(log_txt, start=False, printing=False) - - if verbose: - try: - logprint(lcs_text, start=False, printing=True) - except: - pass - - # finalize layout - margins & spacing between plots - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - # gs.tight_layout(fig, h_pad=.02, w_pad=.02) # less overlapping tick labels, but also disturbingly large spacing - if y_label_rotation == "horizontal": - if x_label_pos_top: - P.subplots_adjust(hspace=spacing, wspace=spacing, left=0.13, top=0.87) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=spacing, wspace=spacing, left=0.13, bottom=0.13) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=spacing, wspace=spacing) # space between rows - def 0.4 - - # save figure and close instance - fig_name = '%s%s_wordsize%i%s.%s' % (prefix, name_graph, wordsize, suffix, filetype) - P.savefig(fig_name) - P.close() - P.cla() - - - # create figure color legend - if lcs_shading: - if lcs_shading_ref == 1: # percentage of shorter sequence - legend_file_name = legend_figure(colors, lcs_shading_num, unit="%", filetype=filetype, prefix=prefix) - elif lcs_shading_ref == 2: # interval sizes - legend_file_name = legend_figure(colors, lcs_shading_num, unit=aa_bp_unit, filetype=filetype, prefix=prefix, bins=color_bins) - else: # relative of maximum lcs - legend_file_name = legend_figure(colors, lcs_shading_num, unit=aa_bp_unit, filetype=filetype, prefix=prefix, max_lcs_len=max_lcs) - - if custom_shading: - custom_prefix = "custom-matrix-" + prefix - legend_file_name_custom = legend_figure(colors_2, lcs_shading_num, unit="%", filetype=filetype, prefix=custom_prefix, max_lcs_len=custom_max, min_lcs_len=custom_min) - - if lcs_shading and custom_shading: - return [fig_name, legend_file_name, legend_file_name_custom] - elif lcs_shading: - return [fig_name, legend_file_name] - elif custom_shading: - return [fig_name, legend_file_name_custom] - else: - return [fig_name] - - -############################### -# Function Call # -############################### - -def main(seq_list, wordsize, modes=[0, 1, 2], prefix=None, plot_size=10, label_size=10, filetype="png", type_nuc=True, convert_wobbles=False, substitution_count=0, rc_option=True, alphabetic_sorting=False, gff=None, multi=True, ncols=1, nrows=1, lcs_shading=True, lcs_shading_num=5, lcs_shading_ref=0, lcs_shading_interval_len=100, lcs_shading_ori=0, gff_color_config_file="", input_user_matrix_file="", user_matrix_print=False, length_scaling=True, title_length=50, spacing=0.04, verbose=False): - - global t1, line_col_rev - - # read gff color config file if provided - if len(input_gff_files) != 0 and input_gff_files != None: - if gff_color_config_file not in ["", None]: - text = "\n%s\n\nReading GFF color configuration file\n%s\n\n=> %s\n" % (50*"=", 28*"-", gff_color_config_file) - logprint(text, start=False, printing=True) - gff_feat_colors = read_gff_color_config(gff_color_config_file) - else: - gff_feat_colors = {} - if gff_color_config_file not in ["", None]: - text = "Please provide GFF annotation files to use configuration file", gff_color_config_file - logprint(text, start=False, printing=True) - - # if color is set to white, reverse complementary matches are skipped - if not rc_option: - line_col_rev = "white" # reverse matches not calculated - elif not type_nuc: - logprint("Reverse complement deactivated for proteins!") - line_col_rev = "white" # reverse matches not calculated - - mode_text = [] - for item in modes: - mode_text.append(str(item)) - text = "%s\n\nRunning plotting modes %s" % (50*"=", ", ".join(mode_text)) - logprint(text, start=False, printing=True) - - - # create dotplots - ########################################## - - # self dotplots - t1 = time.time() - if 0 in modes: - list_of_png_names = selfdotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, multi=multi, ncols=ncols, nrows=nrows, gff_files=gff, gff_color_dict=gff_feat_colors, verbose=verbose) - t1 = time_track(t1) - if list_of_png_names != [] and list_of_png_names != None: - text = "-> Image file(s): %s\n" % ", ".join(list_of_png_names) - else: - text = "No image files were created!\n" - logprint(text, start=False, printing=True) - logprint(50*"=") - - # paired dotplots - if 1 in modes: - if multi: - list_of_png_names = pairdotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, multi=multi, ncols=ncols, nrows=nrows, length_scaling=length_scaling, verbose=verbose) - t1 = time_track(t1) - else: - if not length_scaling: - text = "\nPairwise dotplot with individual output files scaled by sequence length automatically!" - logprint(text, start=False, printing=True) - list_of_png_names = pairdotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, multi=multi, ncols=ncols, nrows=nrows, length_scaling=True, verbose=verbose) - t1 = time_track(t1) - if list_of_png_names != [] and list_of_png_names != None: - text = "-> Image file(s): %s\n" % ", ".join(list_of_png_names) - else: - text = "No image files were created!\n" - logprint(text, start=False, printing=True) - logprint(50*"=") - - # all-against-all dotplot - if 2 in modes: - list_of_png_names = polydotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, lcs_shading=lcs_shading, lcs_shading_num=lcs_shading_num, lcs_shading_ref=lcs_shading_ref, lcs_shading_interval_len=lcs_shading_interval_len, lcs_shading_ori=lcs_shading_ori, input_user_matrix_file=input_user_matrix_file, user_matrix_print=user_matrix_print, spacing=spacing, verbose=verbose) - t1 = time_track(t1) - if list_of_png_names != [] and list_of_png_names != None: - text = "-> Image file(s): %s\n" % ", ".join(list_of_png_names) - else: - text = "No image files were created!\n" - logprint(text, start=False, printing=True) - logprint(50*"=") - - text = "\n" + 50 * "#" + "\n" + 50 * "#" - text += "\n\nThank you for using FlexiDot!\n" - logprint(text, start=False, printing=True) - -# testing mode for debugging -trial_mode = False -# trial_mode = True - -# parameters = check_input(sys.argv) -parameters = check_input(sys.argv, trial_mode=trial_mode) - -# read out parameters -commandline, auto_fas, input_fasta, output_file_prefix, collage_output, m_col, n_row, filetype, type_nuc, input_gff_files, gff_color_config_file, wordsize, plotting_modes, wobble_conversion, substitution_count, rc_option, alphabetic_sorting, lcs_shading, lcs_shading_num, lcs_shading_ref, lcs_shading_interval_len, lcs_shading_ori, input_user_matrix_file, user_matrix_print, plot_size, line_width, line_col_for, line_col_rev, x_label_pos_top, label_size, spacing, length_scaling, title_length, verbose = parameters - -# evtl. overwrite parameters for testing purposes in trial mode -if trial_mode: - # input_user_matrix_file = "AngioSINE-v18-alignment-identities.csv" - input_fasta = ["test-sequences-9-Ns.fas"] - input_fasta = ["Beta_SINEs__select_consensus.fas"] - # input_user_matrix_file = "Beta_SINEs__select_consensus_matrix.txt" - # input_user_matrix_file = "Beta_SINEs__select_consensus_matrix-01.txt" - # input_user_matrix_file = "Beta_SINEs__select_consensus_matrix-comma-str.txt" - # input_user_matrix_file = "Beta_SINEs__select_consensus_matrix-100+.txt" - # user_matrix_print = True - output_file_prefix = "SINEmatrix" - output_file_prefix = "SINEmatrix-NoShading" - plot_size = 10 - plotting_modes = [0,1,2] - plotting_modes = [2] - lcs_shading = False - lcs_shading = True - lcs_shading_ref = 2 - lcs_shading_num = 4 - lcs_shading_ori = 0 - lcs_shading_interval_len = 15 - wordsize = 10 - wordsize = 7 - x_label_pos_top = True - filetype = "pdf" - filetype = "png" - - wobble_conversion = False - wobble_conversion = True - - substitution_count = 0 - - rc_option = True - rc_option = False - label_size = 10 - - verbose = False - verbose = True - -if auto_fas: - path = os.path.dirname(os.path.abspath(__file__)) - files_long = glob.glob(path+"/*.fasta") - files_long.extend(glob.glob(path+"/*.fas")) - files_long.extend(glob.glob(path+"/*.fa")) - files_long.extend(glob.glob(path+"/*.fna")) - input_fasta = [] - for i in files_long: - if not "combined" in i: - filename = i[i.rfind('\\')+1:] - input_fasta.append(filename) - -if trial_mode: - # start logging file - logprint(commandline, start=True, printing=False, prefix=output_file_prefix) - -main(input_fasta, wordsize, modes=plotting_modes, prefix=output_file_prefix, plot_size=plot_size, label_size=label_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=wobble_conversion, substitution_count=substitution_count, rc_option=rc_option, gff=input_gff_files, multi=collage_output, ncols=m_col, nrows=n_row, alphabetic_sorting=alphabetic_sorting, lcs_shading=lcs_shading, lcs_shading_num=lcs_shading_num, lcs_shading_ref=lcs_shading_ref, lcs_shading_interval_len=lcs_shading_interval_len, lcs_shading_ori=lcs_shading_ori, gff_color_config_file=gff_color_config_file, input_user_matrix_file=input_user_matrix_file, user_matrix_print=user_matrix_print, length_scaling=length_scaling, title_length=title_length, spacing=spacing, verbose=verbose) - - diff --git a/code/flexidot_v1.01.py b/code/flexidot_v1.01.py deleted file mode 100644 index 8e5443f..0000000 --- a/code/flexidot_v1.01.py +++ /dev/null @@ -1,3153 +0,0 @@ -#!/usr/bin/python2.7 -#!/usr/bin/python2.7 -# -*- coding: utf-8 -*- - -""" -FlexiDot: Highly customizable ambiguity-aware dotplots for visual sequence investigation - -Kathrin M. Seibt, Thomas Schmidt and Tony Heitkam -Institute of Botany, TU Dresden, Dresden, 01277, Germany - -(Bioinformatics, 2018) -""" - - -############################### -# Requirements # -############################### - -# import system modules -import os, glob -import time, datetime -import sys -import shutil, getopt -import unicodedata - -def module_install_command(module_name, upgrade=False): - """ - create installation commands for Python modules and print information - """ - if upgrade: - load_command = "python -m pip install --upgrade %s" % module_name - else: - load_command = "python -m pip install %s" % module_name - - try: - logprint("Installing Python module: %s\n\t%s\n" % (module_name, load_command)) - except: - print "Installing Python module: %s\n\t%s\n" % (module_name, load_command) - - return load_command - -def load_modules(): - """ - load Python modules, if possible - otherwise try to install them - """ - - # make module names global - global cllct, gridspec, patches, rcParams, mplrc, P, Color, SeqIO, np, ccv, mcolors, rgb2hex, regex - - # matplotlib - try: - import matplotlib.collections as cllct - except: - command = module_install_command("matplotlib", upgrade=True) - try: - os.system(command) - print "\n" - import matplotlib.collections as cllct - except: - print "Please install module matplotlib manually" - from matplotlib.colors import colorConverter as ccv - import matplotlib.colors as mcolors - import matplotlib.gridspec as gridspec - import matplotlib.patches as patches - import pylab as P - - # specify matplotlib font settings - from matplotlib import rc as mplrc - mplrc('pdf', fonttype=42, compression=0) - from matplotlib import rcParams - rcParams['font.family'] = 'sans-serif' - rcParams['font.sans-serif'] = ['Helvetica', 'Verdana', 'Tahoma', ] - - # colour for color gradient palette - try: - from colour import Color - except: - command = module_install_command("colour") - try: - os.system(command) - print "\n" - from colour import Color - except: - print "Please install module colour manually" - - # color converter - try: - from colormap import rgb2hex - except: - command = module_install_command("colormap") - # additional module easydev.tools required by colormap - command2 = module_install_command("easydev") - try: - os.system(command) - os.system(command2) - print "\n" - from colormap import rgb2hex - except: - print "Please install module colormap manually" - - # biopython - try: - from Bio import SeqIO - except: - command = module_install_command("biopython") - try: - os.system(command) - print "\n" - from Bio import SeqIO - except: - print "Please install module biopython manually" - - # numpy - try: - import numpy as np - except: - command = module_install_command("numpy") - try: - os.system(command) - print "\n" - import numpy as np - except: - print "Please install module numpy manually" - - # regex for pattern matching - try: - import regex - except: - command = module_install_command("regex") - try: - os.system(command) - print "\n" - import regex - except: - print "Please install module regex manually" - -load_modules() - - -############################### -# Usage & Input # -############################### - -def usage(): - """ - usage and help - """ - - print """\n\n FLEXIDOT - ------------------------------------------------------------------- - - Version: - 1.01 - - Citation: - Kathrin M. Seibt, Thomas Schmidt, Tony Heitkam (in prep.) - "FlexiDot: Highly customizable ambiguity-aware dotplots for visual sequence investigation" - - - General usage: - $ python flexidot.py -a [ARGUMENTS] - $ python flexidot.py -i [ARGUMENTS] - - - ARGUMENTS - ------------------------------------------------------------------- - - - INPUT/OUTPUT OPTIONS... required are [-a] OR [-i] - - -a, --auto_fas Imports all fasta files from current directory (*.fasta, *.fas, *.fa, *.fna) - -i is not needed, if -a is activated - [inactive by default] - - -i, --in_file Input fasta file (fasta file name or comma-separated file list) - > Provide multiple files: Recall -i or provide comma-separated file names - - -o, --output_file_prefix File prefix to be added to the generated filenames [default = NONE] - - -c, --collage_output Multiple dotplots are combined in a collage - Y or 1 = ON [default] - N or 0 = OFF - - -m, --m_col Number of columns per page [default = 4] (only if --collage_output is ON) - - -n, --n_row Number of rows per page [default = 5] (only if --collage_output is ON) - - -f, --filetype Output file format - 0 = PNG [default] - 1 = PDF - 2 = SVG - - -s, --alphabetic_sorting Sort sequences alphabetically according to titles - Y or 1 = ON - N or 0 = OFF [default] - - - CALCULATION PARAMETERS... - - -k, --wordsize Wordsize (kmer length) for dotplot comparison [default = 7] - - -p, --plotting_mode Mode of FlexiDot dotplotting - 0 = self [default] - 1 = paired - 2 = poly (matrix with all-against-all dotplots) - > Run multiple plotting modes: Recall -p or provide comma-separated numbers - - -t, --type_nuc Type of residue is nucleotide - Y or 1 = nucleotide [default] - N or 0 = amino acid - - -w, --wobble_conversion Ambiguity handling for relaxed matching - Y or 1 = ON - N or 0 = OFF [default] - - -S, --substitution_count Number of substitutions (mismatches) allowed per window for relaxed matching - [default = 0] - - -r, --rc_option Find reverse complementary matches (only if type_nuc=y) - Y or 1 = ON [default] - N or 0 = OFF - - - GRAPHIC FORMATTING... - - -A, --line_width Line width [default = 1] - - -B, --line_col_for Line color [default = black] - - -C, --line_col_rev Reverse line color [default = green] - - -D, --x_label_pos Position of the X-label - Y or 1 = top [default] - N or 0 = bottom - - -E, --label_size Font size [default = 10] - - -F, --spacing Spacing between all-against-all dotplots (only if --plotting_mode=2) - [default = 0.04] - - -P, --plot_size Plotsize [default = 10] - - -L, --length_scaling Scale plot size for pairwise comparison (only if --plotting_mode=1) - Y or 1 = Scaling ON (axes scaled according to sequence length) - N or 0 = Scaling OFF (squared plots) [default] - - -T, --title_length Limit title length for self dotplot comparison (only if --plotting_mode=0) - [default = infinite] - - - GFF SHADING (for -p/--plotting_mode=0 only)... - - -g, --input_gff_files GFF3 file used for markup in self-dotplots - (provide multiple files: Recall -g or provide comma-separated file names) - - -G, --gff_color_config_file Tab-delimited config file for custom gff shading - column 1: feature type - column 2: color - column 3: alpha - column 4: zoom factor (for small regions) - - - LCS SHADING OPTIONS (for -p/--plotting_mode=2 only)... - - -x, --lcs_shading Shade subdotplot based on the length of the longest common substring (LCS) - Y or 1 = ON - N or 0 = OFF [default] - - -X, --lcs_shading_num Number of shading intervals (hues) for LCS (-x) and user matrix shading (-u) - [default = 5] - - -y, --lcs_shading_ref Reference for LCS shading - 0 = maximal LCS length [default] - 1 = maximally possible length (length of shorter sequence in pairwise comparison) - 2 = given interval sizes - DNA [default 100 bp] or proteins [default 10 aa] - see -Y - - -Y, --lcs_shading_interval_len Length of intervals for LCS shading (only if --lcs_shading_ref=2) - [default for nucleotides = 50; default for amino acids = 10] - - -z, --lcs_shading_ori Shade subdotplots according to LCS on - 0 = forward [default], - 1 = reverse, or - 2 = both strands (forward shading above diagonal, reverse shading on diagonal and below; - if using --input_user_matrix_file, best LCS is used below diagonal) - - - CUSTOM USER MATRIX SHADING OPTIONS (for -p/--plotting_mode=2 only)... - - -u, --input_user_matrix_file Shading above diagonal according to values in matrix file specified by the user - (tab-delimited or comma-separated matrix with sequence name in column 1 and numbers in columns 2-n - e.g. identity matrix from multiple sequence alignment - strings are ignored) - - -U, --user_matrix_print Display provided matrix entries in the fields above diagonal of all-against-all dotplot - Y or 1 = ON - N or 0 = OFF [default] - - - OTHERS... - - -h, --help Help screen - - -v, --verbose Verbose - - - - - """ - -def check_input(argv, trial_mode=False): - """ - commandline argument parsing - """ - - global log_txt, aa_bp_unit - - # helpers for argument parsing - ###################################### - - arguments = ["-a", "--auto_fas", "a", "auto_fas", - "-i", "--input_fasta", "i:", "input_fasta=", - "-o", "--output_file_prefix", "o:", "output_file_prefix=", - "-c", "--collage_output", "c:", "collage_output=", - "-m", "--m_col", "m:", "m_col=", - "-n", "--n_row", "n:", "n_row=", - "-f", "--filetype", "f:", "filetype=", - "-t", "--type_nuc", "t:", "type_nuc=", - "-g", "--input_gff_files", "g:", "input_gff_files", - "-G", "--gff_color_config_file", "G:", "gff_color_config_file", - "-k", "--wordsize", "k:", "wordsize=", - "-p", "--plotting_mode", "p:", "plotting_mode=", - "-w", "--wobble_conversion", "w:", "wobble_conversion=", - "-S", "--substitution_count", "S:", "substitution_count=", - "-r", "--rc_option", "r:", "rc_option=", - "-s", "--alphabetic_sorting", "s:", "alphabetic_sorting=", - "-x", "--lcs_shading", "x:", "lcs_shading=", - "-X", "--lcs_shading_num", "X:", "lcs_shading_num=", - "-y", "--lcs_shading_ref", "y:", "lcs_shading_ref=", - "-Y", "--lcs_shading_interval_len", "Y:", "lcs_shading_interval_len=", - "-z", "--lcs_shading_ori", "z:", "lcs_shading_ori=", - "-u", "--input_user_matrix_file", "u:", "input_user_matrix_file=", - "-U", "--user_matrix_print", "U:", "user_matrix_print=", - "-P", "--plot_size", "P:", "plot_size=", - "-A", "--line_width", "A:", "line_width=", - "-B", "--line_col_for", "B:", "line_col_for=", - "-C", "--line_col_rev", "C:", "line_col_rev=", - "-D", "--x_label_pos", "D:", "x_label_pos=", - "-E", "--label_size", "E:", "label_size=", - "-F", "--spacing", "F:", "spacing=", - "-L", "--length_scaling", "L:", "length_scaling=", - "-T", "--title_length", "T:", "title_length=", - "-h", "--help", "h", "help", - "-v", "--verbose", "v", "verbose"] - - arguments_sysargv = tuple(arguments[0::4] + arguments[1::4]) - arguments_opts = "".join(arguments[2::4]) - arguments_args = arguments[3::4] - - - # setting defaults - ###################################### - - auto_fas = False # 0 - input_fasta = [] - output_file_prefix = None - collage_output = True # 1 - m_col = 4 - n_row = 5 - filetype = 0 - type_nuc = True - input_gff_files = [] - gff_color_config_file = "" - - wordsize = 7 - plotting_modes = [0] - wobble_conversion = False # 0 - substitution_count = 0 - rc_option = True # 1 - alphabetic_sorting = False # 0 - - lcs_shading = False # 0 - lcs_shading_num = 4 - lcs_shading_ref = 0 - lcs_shading_interval_len = 50 # interval default changes to "10" for amino acids [type_nuc = n] - lcs_shading_ori = 0 - - input_user_matrix_file = "" - user_matrix_print = False - - plot_size = 10 - line_width = 1 - line_col_for = "black" - line_col_rev = "#009243" - x_label_pos = True # 0 - label_size = 10 - spacing = 0.04 - length_scaling = False # 0 - title_length = float("Inf") - - aa_bp_unit = "bp" - - verbose = False # 0 - - filetype_dict = {0: "png", 1: "pdf", 2: "svg"} - lcs_shading_ref_dict = {0: "maximal LCS length", 1: "maximally possible length", 2: "given interval sizes"} - plotting_mode_dict = {0: "self", 1: "paired", 2: "all-against-all"} - lcs_shading_ori_dict = {0: "forward", 1: "reverse complement", 2: "both"} - - # return default parameters for testing purposes - if trial_mode: - print "ATTENTION: YOU ARE IN THE TRIAL MODE!!!\n\n" - - commandline = "trial_mode\n" - - parameters = [commandline, auto_fas, input_fasta, output_file_prefix, collage_output, m_col, n_row, filetype_dict[filetype], type_nuc, input_gff_files, gff_color_config_file, wordsize, plotting_modes, wobble_conversion, substitution_count, rc_option, alphabetic_sorting, lcs_shading, lcs_shading_num, lcs_shading_ref, lcs_shading_interval_len, lcs_shading_ori, input_user_matrix_file, user_matrix_print, plot_size, line_width, line_col_for, line_col_rev, x_label_pos, label_size, spacing, length_scaling, title_length, verbose] - return parameters - - - # read arguments - ###################################### - - commandline = "" - for arg in sys.argv: - commandline += arg + " " - - log_txt = "\n...reading input arguments..." - print log_txt - - if len(sys.argv) < 2: - print "\nERROR: More arguments are needed. Exit..." - log_txt += "\nERROR: More arguments are needed. Exit..." - usage() - sys.exit() - - elif sys.argv[1] not in arguments_sysargv: - print "\nINPUT ERROR: Input argument %s unknown. Please check the help screen." % sys.argv[1] - log_txt += "\nINPUT ERROR: Input argument %s unknown. Please check the help screen." % sys.argv[1] - # usage() - sys.exit() - - try: - opts, args = getopt.getopt(sys.argv[1:], arguments_opts, arguments_args) - - except getopt.GetoptError: - print "\nINPUT ERROR (getopt): Input argument %s unknown. Please check the help screen." % sys.argv[1:] - log_txt += "\nINPUT ERROR (getopt): Input argument %s unknown. Please check the help screen." % sys.argv[1:] - # usage() - sys.exit() - - for opt, arg in opts: - - if opt in ("-h", "--help"): - print "...fetch help screen" - log_txt += "\n...fetch help screen" - usage(), sys.exit() - - if opt in ("-v", "--verbose"): - print "...verbose output" - log_txt += "\n...verbose output" - verbose = True - - elif opt in ("-i", "--input_fasta"): - if "," in arg: - arg_list = arg.split(",") - for temp_file in arg_list: - if not os.path.exists(str(temp_file)): - message = "\nERROR: fasta_file '%s' was not found!" % str(temp_file) - sys.exit(message) - else: - input_fasta.append(str(temp_file)) - print "fasta file #%i: %s" % (len(input_fasta), str(temp_file)) - log_txt += "\nfasta file #%i: %s" % (len(input_fasta), str(temp_file)) - else: - if not os.path.exists(str(arg)): - message = "\nERROR: fasta_file '%s' was not found!" % str(arg) - log_txt += message - sys.exit(message) - else: - input_fasta.append(str(arg)) - print "fasta file #%i: %s" % (len(input_fasta), str(arg)) - log_txt += "\nfasta file #%i: %s" % (len(input_fasta), str(arg)) - - - elif opt in ("-a", "--auto_fas"): - auto_fas = True - - - # multiple gff files: reads them into a list - elif opt in ("-g", "--input_gff_files"): - - # append gff file only if existing - if "," in arg: - arg_list = arg.split(",") - for temp_file in arg_list: - if not os.path.exists(str(temp_file)): - message = "\nERROR: gff_file '%s' was not found!" % str(temp_file) - print message - log_txt += message - print " -->Running FlexiDot without this gff file!" - log_txt += "\n -->Running FlexiDot without this gff file!" - else: - print "GFF file #%i: %s" %(len(input_gff_files), str(temp_file)) - log_txt += "\nGFF file #%i: %s" %(len(input_gff_files), str(temp_file)) - input_gff_files.append(str(temp_file)) - else: - if not os.path.exists(str(arg)): - message = "\nERROR: gff_file '%s' was not found!" % str(arg) - print message - log_txt += message - print " -->Running FlexiDot without this gff file!" - log_txt += "\n -->Running FlexiDot without this gff file!" - else: - input_gff_files.append(str(arg)) - print "GFF file #%i: %s" %(len(input_gff_files), str(arg)) - log_txt += "\nGFF file #%i: %s" %(len(input_gff_files), str(arg)) - - - elif opt in ("-G", "--gff_color_config_file"): - if not os.path.exists(str(arg)): - message = "\nERROR: gff_color_config_file '%s' was not found!" % str(arg) - print message + "\n -->Running FlexiDot with default gff coloring specification!" - log_txt += message + "\n -->Running FlexiDot with default gff coloring specification!" - else: - gff_color_config_file = str(arg) - - - elif opt in ("-u", "--input_user_matrix_file"): - if not os.path.exists(str(arg)): - message = "\nERROR: input_user_matrix_file '%s' was not found!" % str(arg) - print message + "\n -->Running FlexiDot without input_user_matrix_file %s!" % arg - log_txt += message + "\n -->Running FlexiDot withdefault matrix shading file!" - else: - input_user_matrix_file = str(arg) - - elif opt in ("-U", "--user_matrix_print"): - user_matrix_print = check_bools(str(arg), default=user_matrix_print) - - elif opt in ("-o", "--output_file_prefix"): - output_file_prefix = arg - - elif opt in ("-c", "--collage_output"): - collage_output = check_bools(str(arg), default=collage_output) - - elif opt in ("-m", "--m_col"): - try: m_col = int(arg) - except: - print "m_col - invalid argument - using default value" - log_txt += "\nm_col - invalid argument - using default value" - - elif opt in ("-n", "--n_row"): - try: n_row = int(arg) - except: - print "n_row - invalid argument - using default value" - log_txt += "\nn_row - invalid argument - using default value" - - elif opt in ("-f", "--filetype"): - if 0 <= int(arg) <= 2: - filetype = int(arg) - else: - print "\nERROR: Please provide valid filetype argument. %s is out of range. It will be set to -f 0 [default]." %(filetype) - log_txt += "\nERROR: Please provide valid filetype argument. %s is out of range. It will be set to -f 0 [default]." %(filetype) - - elif opt in ("-t", "--type_nuc"): - type_nuc = check_bools(str(arg), default=type_nuc) - - if type_nuc == False: - # interval default changed for amino acids - lcs_shading_interval_len = 10 - aa_bp_unit = "aa" - - elif opt in ("-k", "--wordsize"): - try: wordsize = int(arg) - except: - print "wordsize - invalid argument - using default value" - log_txt += "\nwordsize - invalid argument - using default value" - - elif opt in ("-p", "--plotting_mode"): - if "," in arg: - temp_modes = arg.split(",") - for item in temp_modes: - if item in ["0","1","2"]: - plotting_modes.append(int(item)) - elif arg in ["0","1","2"]: - plotting_modes = [int(arg)] - else: - print "Please provide valid plotting_modes argument - e.g. 1 or 0,1,2 - using default [0]" - log_txt += "\nPlease provide valid plotting_modes argument - e.g. 1 or 0,1,2 - using default [0]" - - elif opt in ("-w", "--wobble_conversion"): - wobble_conversion = check_bools(str(arg), default=wobble_conversion) - - elif opt in ("-S", "--substitution_count"): - try: substitution_count = int(arg) - except: - print "substitution_count - invalid argument - using default value" - log_txt += "\nsubstitution_count - invalid argument - using default value" - - elif opt in ("-r", "--rc_option"): - rc_option = check_bools(str(arg), default=rc_option) - - elif opt in ("-s", "--alphabetic_sorting"): - alphabetic_sorting = check_bools(str(arg), default=alphabetic_sorting) - - elif opt in ("-x", "--lcs_shading"): - lcs_shading = check_bools(str(arg), default=lcs_shading) - - elif opt in ("-X", "--lcs_shading_num"): - try: lcs_shading_num = int(arg) - 1 - except: - print "lcs_shading_num - invalid argument - using default value" - log_txt += "\nlcs_shading_num - invalid argument - using default value" - - elif opt in ("-y", "--lcs_shading_ref"): - try: - if 0 <= int(arg) <= 2: - lcs_shading_ref = int(arg) - else: - print "\nERROR: lcs_shading_ref %s out of range. It will be set to -y 0 [default]." %(lcs_shading_ref) - log_txt += "\nERROR: lcs_shading_ref %s out of range. It will be set to -y 0 [default]." %(lcs_shading_ref) - except: - print "lcs_shading_ref - invalid argument - using default value" - log_txt += "\nlcs_shading_ref - invalid argument - using default value" - - elif opt in ("-Y", "--lcs_shading_interval_len"): - try: lcs_shading_interval_len = int(arg) - except: - print "lcs_shading_interval_len - invalid argument - using default value" - log_txt += "\nlcs_shading_interval_len - invalid argument - using default value" - - elif opt in ("-z", "--lcs_shading_ori"): - if 0 <= int(arg) <= 2: - lcs_shading_ori = int(arg) - else: - print "\nERROR: Please provide valid lcs_shading_ori argument. %s is out of range. It will be set to -z 0 [default]." %(lcs_shading_ori) - log_txt += "\nERROR: Please provide valid lcs_shading_ori argument. %s is out of range. It will be set to -z 0 [default]." %(lcs_shading_ori) - - elif opt in ("-P", "--plot_size"): - try: plot_size = float(arg) - except: - print "plot_size - invalid argument - using default value" - log_txt += "\nplot_size - invalid argument - using default value" - - - elif opt in ("-A", "--line_width"): - try: line_width = float(arg) - except: - print "line_width - invalid argument - using default value" - log_txt += "\nline_width - invalid argument - using default value" - - elif opt in ("-B", "--line_col_for"): - if mcolors.is_color_like(arg): - line_col_for = arg - else: - print "line_col_for - invalid argument - using default value" - log_txt += "\nline_col_for - invalid argument - using default value" - - elif opt in ("-C", "--line_col_rev"): - if mcolors.is_color_like(arg): - line_col_rev = arg - else: - print "line_col_rev - invalid argument - using default value" - log_txt += "\nline_col_rev - invalid argument - using default value" - - elif opt in ("-D", "--x_label_pos"): - x_label_pos = check_bools(str(arg), default=x_label_pos) - - elif opt in ("-E", "--label_size"): - try: label_size = float(arg) - except: - print "label_size - invalid argument - using default value" - log_txt += "\nlabel_size - invalid argument - using default value" - - elif opt in ("-F", "--spacing"): - try: spacing = float(arg) - except: - print "spacing - invalid argument - using default value" - log_txt += "\nspacing - invalid argument - using default value" - - elif opt in ("-L", "--length_scaling"): - length_scaling = check_bools(str(arg), default=length_scaling) - - elif opt in ("-T", "--title_length"): - try: title_length = int(arg) - except: - print "title_length - invalid argument - using default value" - log_txt += "\ntitle_length - invalid argument - using default value" - - # start logging file - logprint(commandline, start=True, printing=False, prefix=output_file_prefix) - logprint(log_txt, start=False, printing=False) - - - # print chosen arguments - ###################################### - - text = "\n%s\n" % (70 * "-") - text += "\n" + "INPUT/OUTPUT OPTIONS...\n" - text += "\n" + "Input fasta file: " + ", ".join(input_fasta) - text += "\n" + "Automatic fasta collection from current directory: " + str(auto_fas) - text += "\n" + "Collage output: " + str(collage_output) - text += "\n" + "Number of columns per page: " + str(m_col) - text += "\n" + "Number of rows per page: " + str(n_row) - text += "\n" + "File format: " + filetype_dict[filetype] - text += "\n" + "Residue type is nucleotide: " + str(type_nuc) - - text += "\n" + "\n\nCALCULATION PARAMETERS...\n" - text += "\n" + "Wordsize: " + str(wordsize) - text += "\n" + "Plotting mode: " + str(plotting_modes).replace("[", "").replace("]", "") + "\n" + 51 * " " - for item in plotting_modes: - text += plotting_mode_dict[item] + " " - text += "\n" + "Ambiguity handling: " + str(wobble_conversion) - text += "\n" + "Reverse complement scanning: " + str(rc_option) - text += "\n" + "Alphabetic sorting: " + str(alphabetic_sorting) - - if 0 in plotting_modes and input_gff_files != []: - text += "\n" + "Input gff files: " + ", ".join(input_gff_files) - if gff_color_config_file != "": - text += "\n" + "GFF color config file: " + gff_color_config_file - text += "\n" + "Prefix for output files: " + str(output_file_prefix) - - if 2 in plotting_modes: - text += "\n" + "\n\nLCS SHADING OPTIONS (plotting_mode 'all-against-all' only)...\n" - text += "\n" + "LCS shading: " + str(lcs_shading) - text += "\n" + "LCS shading interval number: " + str(lcs_shading_num + 1) - text += "\n" + "LCS shading reference: " + lcs_shading_ref_dict[lcs_shading_ref] - if lcs_shading_ref == 2: - text += "\n" + "LCS shading interval size [%s]: " % (aa_bp_unit) + str(lcs_shading_interval_len) - text += "\n" + "LCS shading orientation: " + lcs_shading_ori_dict[lcs_shading_ori] - if input_user_matrix_file != "": - text += "\n" + "Custom user shading matrix file: " + input_user_matrix_file - text += "\n" + "Print user matrix values (instead of dotplot): " + str(user_matrix_print) - - text += "\n" + "\n\nGRAPHIC FORMATTING...\n" - text += "\n" + "Plot size: " + str(plot_size) - text += "\n" + "Line width: " + str(line_width) - text += "\n" + "Line color: " + line_col_for - text += "\n" + "Reverse line color: " + line_col_rev - text += "\n" + "X label position: " + str(x_label_pos) - text += "\n" + "Label size: " + str(label_size) - text += "\n" + "Spacing: " + str(spacing) - text += "\n" + "Title length (limit number of characters): " + str(title_length) - text += "\n" + "Length scaling: " + str(length_scaling) - text += "\n%s\n" % (70 * "-") - logprint(text) - - - # collect settings - parameters = [commandline, auto_fas, input_fasta, output_file_prefix, collage_output, m_col, n_row, filetype_dict[filetype], type_nuc, input_gff_files, gff_color_config_file, wordsize, plotting_modes, wobble_conversion, substitution_count, rc_option, alphabetic_sorting, lcs_shading, lcs_shading_num, lcs_shading_ref, lcs_shading_interval_len, lcs_shading_ori, input_user_matrix_file, user_matrix_print, plot_size, line_width, line_col_for, line_col_rev, x_label_pos, label_size, spacing, length_scaling, title_length, verbose] - - return parameters - - -############################### -# Helper Functions # -############################### - -def alphabets(type_nuc=True): - """ - provide ambiguity code for sequences - """ - - nucleotide_alphabet = ["A", "C", "G", "T"] - - nucleotide_alphabet_full = ["A", "C", "G", "T", "N", "B", "D", "H", - "V", "Y", "R", "W", "S", "K", "M"] - - nucleotide_ambiguity_code = {"N": ["A", "C", "G", "T"], # any - "B": ["C", "G", "T"], # not A - "D": ["A", "G", "T"], # not C - "H": ["A", "C", "T"], # not G - "V": ["A", "C", "G"], # not T - "Y": ["C", "T"], # pyrimidine - "R": ["A", "G"], # purine - "W": ["A", "T"], # weak - "S": ["C", "G"], # strong - "K": ["G", "T"], # keto - "M": ["A", "C"]} # amino - - nucleotide_match_dict = {"N": "[ACGTNBDHVYRWSKM]", # any - "B": "[CGTNBDHVYRWSKM]", # not A - "D": "[AGTNBDHVYRWSKM]", # not C - "H": "[ACTNBDHVYRWSKM]", # not G - "V": "[ACGNBDHVYRWSKM]", # not T - "K": "[GTNBDHVYRWSK]", # keto - not A,C,M - "M": "[ACNBDHVYRWSM]", # amino - not G,T,K - "W": "[ATNBDHVYRWKM]", # weak - not C,G,S - "S": "[CGNBDHVYRSKM]", # strong - not A,G,W - "Y": "[CTNBDHVYWSKM]", # pyrimidine - not A,G,R - "R": "[AGNBDHVRWSKM]", # purine - not C,T,Y - "A": "[ANDHVRWM]", - "C": "[CNBHVYSM]", - "G": "[GNBDVRSK]", - "T": "[TNBDHYWK]"} - - # nucleotide_match_dict = {"N": ".", # any - # "B": "[^A]", # not A - # "D": "[^C]", # not C - # "H": "[^G]", # not G - # "V": "[^T]", # not T - # "K": "[^ACM]", # keto - not A,C,M - # "M": "[^GTK]", # amino - not G,T,K - # "W": "[^CGS]", # weak - not C,G,S - # "S": "[^AGW]", # strong - not A,G,W - # "Y": "[^AGR]", # pyrimidine - not A,G,R - # "R": "[^CTY]", # purine - not C,T,Y - # "A": "[ANDHVRWM]", - # "C": "[CNBHVYSM]", - # "G": "[GNBDVRSK]", - # "T": "[TNBDHYWK]"} - - aminoacid_alphabet = ["A", "R", "N", "D", "C", "E", "Q", "G", - "H", "I", "L", "K", "M", "F", "P", "S", - "T", "W", "Y", "V", "U", "O", "*"] - - aminoacid_alphabet_full = ["A", "R", "N", "D", "C", "E", "Q", "G", - "H", "I", "L", "K", "M", "F", "P", "S", - "T", "W", "Y", "V", "U", "O", "*", "J", - "Z", "B", "X"] - - aminoacid_ambiguity_code = {"J": ["I", "L"], - "Z": ["Q", "E"], - "B": ["N", "D"], - "X": ["A", "R", "N", "D", "C", "E", "Q", "G", - "H", "I", "L", "K", "M", "F", "P", "S", - "T", "W", "Y", "V", "U", "O", "*"]} # any - - aminoacid_match_dict = {"J": "[ILJ]", - "Z": "[QEZ]", - "B": "[NDB]", - # "X": ".", - "X": "[ARNDCEQGHILKMFPSTWYVUO*XBZJ]", - "A": "[AX]", - "R": "[RX]", - "N": "[NXB]", - "D": "[DXB]", - "C": "[CX]", - "E": "[EXZ]", - "Q": "[QXZ]", - "G": "[GX]", - "H": "[HX]", - "I": "[IXJ]", - "L": "[LXJ]", - "K": "[KX]", - "M": "[MX]", - "F": "[FX]", - "P": "[PX]", - "S": "[SX]", - "T": "[TX]", - "W": "[WX]", - "Y": "[YX]", - "V": "[VX]", - "U": "[UX]", - "O": "[OX]", - "*": "[*X]"} - - aa_only = set(['E', 'F', 'I', 'J', 'L', 'O', 'Q', 'P', 'U', 'X', 'Z', '*']) - # return nucleotide_alphabet, nucleotide_alphabet_full, nucleotide_ambiguity_code, aminoacid_alphabet, aminoacid_alphabet_full, aminoacid_ambiguity_code, aa_only - - if type_nuc: - return nucleotide_alphabet, nucleotide_alphabet_full, nucleotide_ambiguity_code, nucleotide_match_dict - else: - return aminoacid_alphabet, aminoacid_alphabet_full, aminoacid_ambiguity_code, aminoacid_match_dict - -def logprint(text, start=False, printing=True, prefix=""): - """ - log output to log_file and optionally print - """ - - # define log file name and open file - global log_file_name - if start and trial_mode: - log_file_name = "log_file.txt" - if prefix != "" and prefix != None: - if not prefix.endswith("-"): - prefix = prefix + "-" - log_file_name = prefix + log_file_name - log_file = open(log_file_name, 'w') - log_file.write("Date: %s\n\n" % str(datetime.datetime.now())) - elif start: - date = datetime.date.today() - time = str(datetime.datetime.now()).split(" ")[1].split(".")[0].replace(":", "-") - log_file_name = "%s_%s_log_file.txt" % (date, time) - if prefix != "" and prefix != None: - if not prefix.endswith("-"): - prefix = prefix + "-" - log_file_name = prefix + log_file_name - log_file = open(log_file_name, 'w') - log_file.write("Date: %s\n\n" % str(datetime.datetime.now())) - else: - log_file = open(log_file_name, 'a') - - # write log (and print) - log_file.write(text + "\n") - if printing: - print text - log_file.close() - -def time_track(starting_time, show=True): - """ - calculate time passed since last time measurement - """ - now = time.time() - delta = now - starting_time - if show: - text = "\n\t %s seconds\n" % str(delta) - logprint(text, start=False, printing=True) - return now - -def calc_fig_ratio(ncols, nrows, plot_size, verbose=False): - """ - calculate size ratio for given number of columns (ncols) and rows (nrows) - with plot_size as maximum width and length - """ - ratio = ncols*1./nrows - if verbose: - text = " ".join([ncols, nrows, ratio]) - logprint(text, start=False, printing=True) - if ncols >= nrows: - figsize_x = plot_size - figsize_y = plot_size / ratio - else: - figsize_x = plot_size * ratio - figsize_y = plot_size - return figsize_x, figsize_y - -def shorten_name(seq_name, max_len=float("Inf"), delim="_"): - """ - shorten sequence names (for diagram titles) - """ - - if len(seq_name) <= max_len: - return seq_name - - # keep first and last part if multiple parts separated by delimiter (e.g. species_prefix + sequence_id) - if delim in seq_name: - if seq_name.count(delim) >= 2: - name = "%s..." % delim.join(seq_name.split(delim)[:1]) + seq_name.split(delim)[-1] # .replace("_000", "-") - else: - name = seq_name[:((max_len-2)//2)] + "..." + seq_name[((max_len-2)//2):] - - if len(name) > max_len: - name = name[:((max_len-2)//2)] + "..." + name[((max_len-2)//2):] - else: - name = seq_name[:((max_len-2)//2)] + "..." + seq_name[((max_len-2)//2):] - - return name - -def unicode_name(name): - """ - replace non-ascii characters in string (e.g. for use in matplotlib) - """ - unicode_string = eval('u"%s"' % name) - return unicodedata.normalize('NFKD', unicode_string).encode('ascii','ignore') - -def check_bools(arg, update_log_txt = True, default=None): - """ - converts commandline arguments into boolean - """ - - - # convert valid arguments - if str(arg).lower() == "y" or str(arg) == "1": - return True - elif str(arg).lower() == "n" or str(arg) == "0": - return False - - # use default in case of invalid argument - else: - if update_log_txt: - global log_txt - log_txt += "using default for " + str(arg) - else: - try: - logprint("using default for " + str(arg)) - except: - print "using default for " + str(arg) - return default - -def create_color_list(number, color_map=None, logging=False, max_grey="#595959"): - """ - create color list with given number of entries - grey by default, matplotlib color_map can be provided - """ - - try: - # create pylab colormap - cmap = eval("P.cm." + color_map) - # get descrete color list from pylab - cmaplist = [cmap(i) for i in range(cmap.N)] # extract colors from map - # determine positions for number of colors required - steps = (len(cmaplist)-1)/(number) - numbers = range(0, len(cmaplist), steps) - - # extract color and convert to hex code - colors = [] - for idx in numbers[:-1]: - rgb_color = cmaplist[idx] - col = rgb2hex(rgb_color[0]*255, rgb_color[1]*255, rgb_color[2]*255) - colors.append(col) - - # grey - except: - if not color_map == None: - logprint("Invalid color_map (%s) provided! - Examples: jet, Blues, OrRd, bwr,..." % color_map) - logprint("See https://matplotlib.org/users/colormaps.html\n") - old_max_grey = "#373737" - old_max_grey = "#444444" - colors = list(Color("#FFFFFF").range_to(Color(max_grey), number)) # grey - for idx in range(len(colors)): - colors[idx] = str(colors[idx]).replace("Color ", "") - if "#" in colors[idx] and len(colors[idx]) != 7: - # print colors[idx] - colors[idx] = colors[idx] + colors[idx][-(7-len(colors[idx])):] - - text = "%d Colors: %s" % (len(colors), ", ".join(colors)) - if logging: logprint(text, start=False, printing=True) - - if len(colors) < number: - logprint("\nError in color range definition! %d colors missing\n" % (number - len(colors))) - - return colors - - -############################### -# File Handling # -############################### - -def read_seq(input_fasta, verbose=False): - """ - read fasta sequences from (all) file(s) - """ - - # check if file provided - if input_fasta == [] or input_fasta == "": - text = "Attention: No valid file names provided: >%s<" % input_fasta - logprint(text, start=False, printing=True) - return {}, [] - - # combine sequence files, if required - if type(input_fasta) == list: - # concatenate fasta files - if len(input_fasta) > 1: - if verbose: - print "concatenating fastas...", - text = "concatenating fastas..." - input_fasta_combi = concatenate_files(input_fasta) - if verbose: - print "done" - text += "done" - logprint(text, start=False, printing=False) - else: - input_fasta_combi = input_fasta[0] - else: - input_fasta_combi = input_fasta - - # read sequences - if verbose: - print "reading fasta...", - text = "reading fasta...", - try: - seq_dict = SeqIO.index(input_fasta_combi, "fasta") - except ValueError: - logprint("Error reading fasta sequences - please check input files, e.g. for duplicate names!") - return {}, [] - except: - logprint("Error reading fasta sequences - please check input files!") - return {}, [] - - if verbose: - print "done" - text += "done" - logprint(text, start=False, printing=False) - - for seq in seq_dict: - if "-" in seq_dict[seq].seq: - # ungapped = seq_dict[seq].seq.ungap("-") # cannot be assigned back to sequence record - text = "\nSequences degapped prior Analysis!!!" - logprint(text, start=False, printing=True) - return read_seq(degap_fasta(input_fasta), verbose=verbose) - - # get ordered sequence names - sequences = [] - for item in SeqIO.parse(input_fasta_combi, "fasta"): - sequences.append(item.id) - return seq_dict, sequences - -def read_gff_color_config(gff_color_config_file=""): - """ - define coloring options for gff-based color shading of self-dotplots - """ - - # default aestetics for annotation shading (e.g. if no user config file is provided) - # dictionary with feature_type as key and tuple(color, transparency, zoom) as value - gff_feat_colors = {"orf": ("#b41a31", 0.2, 0), - "orf_rev": ("#ff773b", 0.3, 0), - "gene": ("#b41a31", 0.2, 0), - "cds": ("darkorange", 0.2, 0), - "exon": ("orange", 0.2, 0), - "intron": ("lightgrey", 0.2, 0), - "utr": ("lightblue", 0.2, 0), - "repeat_region": ("green", 0.3, 0), - "repeat": ("green", 0.3, 0), - "tandem_repeat": ("red", 0.3, 0), - "transposable_element": ("blue", 0.3, 0), - "ltr_retrotransposon": ("#cccccc", 0.5, 0), - "ltr-retro": ("#cccccc", 0.5, 0), - "long_terminal_repeat": ("#2dd0f0", 0.75, 2), - "ltr": ("#2dd0f0", 0.75, 2), - "pbs": ("purple", 0.75, 2), - "ppt": ("#17805a", 0.5, 2), - "target_site_duplication": ("red", 0.75, 2), - "misc_feature": ("grey", 0.3, 0), - "misc_feat": ("grey", 0.3, 0), - "misc": ("grey", 0.3, 0), - "others": ("grey", 0.5, 0)} - if gff_color_config_file in ["", None] or not os.path.exists(str(gff_color_config_file)): - return gff_feat_colors - - text = "Updating GFF color configuration with custom specifications\n" - logprint(text, start=False, printing=True) - - # read custom gff_color_config_file - in_file = open(gff_color_config_file, 'rb') - overwritten = set([]) - for line in in_file: - if not line.startswith("#") and len(line.strip().split("\t")) >= 4: - data = line.strip().split("\t") - feat = data[0].lower() - color = data[1].lower() - - # check, if settings are valid - if not mcolors.is_color_like(color): - color = "grey" - text = "Invalid color specified for %s: %s - default grey" % (data[0], data[1]) - logprint(text) - try: - alpha = float(data[2]) - except: - alpha = 0.75 - text = "Invalid alpha specified for %s: %s - default 0.75" % (data[0], data[2]) - logprint(text) - try: - zoom = float(data[3]) - except: - zoom = 0 - text = "Invalid zoom specified for %s: %s - default 0" % (data[0], data[3]) - logprint(text) - - # track changes of predefined settings - if feat in gff_feat_colors.keys(): - overwritten.add(data[0].lower()) - - gff_feat_colors[feat] = (color, alpha, zoom) - in_file.close() - - # default coloring for unknown annotations - if not "others" in gff_feat_colors.keys(): - gff_feat_colors["others"] = ("grey", 0.5, 0) - - if verbose: - # print configuration - text = "\n\nGFF color specification:\n%s\n" % (60 * ".") - for item in sorted(gff_feat_colors.keys()): - text += "%-30s\t%-10s\t%-5s\t%s\n" % (item, str(gff_feat_colors[item][0]), str(gff_feat_colors[item][1]), str(gff_feat_colors[item][2])) - logprint (text, printing=True) - - # print overwritting feature type specifications - if len(overwritten) != 0: - text = "%d feature type specifications overwritten:" % len(overwritten) - text += "\n\t"+ ", ".join(overwritten) + "\n" - logprint(text, start=False, printing=True) - - text = "GFF color specification updated acc. to %s\n\t%s\n\n" % (gff_color_config_file, ", ".join(gff_feat_colors)) - logprint(text, start=False, printing=True) - - return gff_feat_colors - -def read_gffs(input_gff_files, color_dict={"others": ("grey", 1, 0)}, type_nuc=True, prefix="", filetype='png', verbose=False): - """ - create feature dictionary from input_gff - sequence name as key and (feature type, start, stop) as value - """ - if type(input_gff_files) != list: - input_gff_files = [input_gff_files] - - # create dictionary with seq_name as key and (type, start and stop) as value - unknown_feats = set([]) - used_feats = set([]) - feat_dict = {} - for input_gff in input_gff_files: - text = "...reading " + input_gff - logprint(text, start=False, printing=True) - - in_file = open(input_gff, 'rb') - for line in in_file: - if not line.startswith("#") and line.strip() != "": - data = line.strip().split("\t") - feat_type = data[2].lower() - if data[6] == "-": - feat_type += "_rev" - if not feat_type.lower() in color_dict.keys(): - if feat_type.lower().replace("_rev", "") in color_dict.keys(): - feat_type = feat_type.replace("_rev", "") - else: - unknown_feats.add(feat_type) - feat_type = "others" - used_feats.add(feat_type) - if not data[0] in feat_dict.keys(): - feat_dict[data[0]] = [(feat_type, int(data[3]), int(data[4]))] # feature type, start, stop - else: - feat_dict[data[0]].append((feat_type, int(data[3]), int(data[4]))) # feature type, start, stop - if verbose: - text = "\nAnnotations for: %s\n" % ", ".join(feat_dict.keys()[:10]) - if len(feat_dict.keys()) > 10: - text = text[:-1] + ", ...\n" - logprint(text, start=False, printing=True) - in_file.close() - - # print feature types without specific shading settings - if len(unknown_feats) != 0: - text = "Missing shading specification for %d feature type(s):\n\t%s\n" % (len(unknown_feats), ", ".join(sorted(unknown_feats))) - logprint(text, start=False, printing=True) - - # create color legend - colors, alphas = [], [] - for item in sorted(used_feats): - colors.append(color_dict[item][0]) - alphas.append(color_dict[item][1]) - legend_figure(colors=colors, lcs_shading_num=len(used_feats), type_nuc=type_nuc, bins=sorted(used_feats), alphas=alphas, gff_legend=True, prefix=prefix, filetype=filetype) - - # print settings - text = "GFF Feature Types: %s\nGFF Colors: %s" % (", ".join(sorted(used_feats)), ", ".join(sorted(colors))) - logprint(text, start=False, printing=True) - - return feat_dict - -def read_matrix(matrix_file_name, delim="\t", symmetric=True, recursion=False, verbose=False): - input_file = open(matrix_file_name, 'rb') - - # read sequence names from first column - names = [] - for line in input_file: - if not line.startswith("#") and not line.startswith(delim) and delim in line: - names.append(line.strip().split(delim)[0]) - logprint("Delimiter '%s': %d names - %s\n" % (delim, len(names), ", ".join(names))) - - # check if names were found - otherwise try another delimiter - if names == [] and not recursion: - if delim == "\t": - new_delim = "," - else: - new_delim = "\t" - logprint("\nMatrix file not containing data delimited by '%s' - trying to read matrix with delimiter '%s'" % (delim.replace("\t", "\\t"), new_delim)) - info_dict = read_matrix(matrix_file_name, delim=new_delim, symmetric=symmetric, recursion=True, verbose=verbose) - return info_dict - elif names == []: - logprint("Empty matrix file with alternative delimiter!") - return info_dict - input_file.close() - - input_file = open(matrix_file_name, 'rb') - # read matrix entries as values in dictionary with tuple(names) as key - info_dict = {} - contradictory_entries = [] - for line in input_file: - if not line.startswith("#") and not line.startswith(delim) and delim in line: - data = line.strip().split(delim) - for idx in range(len(data[1:])): - # print tuple(sorted([data[0], names[idx]])), data[idx+1] - if symmetric: - key = tuple(sorted([names[idx], data[0]])) - else: - key = tuple(names[idx], data[0]) - if key in info_dict.keys(): - if symmetric and info_dict[key] != data[idx+1] and data[idx+1] not in ["", "-"] and info_dict[key] not in ["", "-"]: - contradictory_entries.append(key) - info_dict[key] = data[idx+1] - input_file.close() - - if len(contradictory_entries) != 0: - try: - logprint("\nContradictory entries in matrix file %s:\n\t%s" % (matrix_file_name, ", ".join(contradictory_entries))) - except: - log_txt = "\nContradictory entries in matrix file %s:\n\t" % (matrix_file_name) - for item in contradictory_entries: - log_txt += str(item).replace("'", "") + ", " - log_txt = log_txt[:-2] - logprint(log_txt) - logprint("Using value from bottom left triangle!") - if verbose: - logprint("\nMatrix information for Sequences named: " % ", ".join(names)) - - return info_dict - -def concatenate_files(file_list, combi_filename="temp_combined.fasta", verbose=False): - """ - concatenate content of all files in file_list into a combined file named combi_filename - """ - out_file = open(combi_filename, 'w') - text = "" - for item in file_list: - if verbose: - text += item + " " - print item, - # read in_file linewise and write to out_file - in_file = open(item, 'rb') - for line in in_file: - out_file.write(line.strip()+"\n") - in_file.close() - out_file.close() - if verbose: - logprint(text, start=False, printing=False) - return combi_filename - -def degap_fasta(input_fasta): - """ - remove gaps from fasta - new degapped sequence file created - """ - - # degap all sequence files - output_fastas = [] - if type(input_fasta) != list: - input_fasta = list(input_fasta) - for input_fas in input_fasta: - output_fas = input_fas[:input_fas.rfind(".")] + "_degapped.fas" - in_file = open(input_fas, 'rb') - out_file = open(output_fas, 'w') - for line in in_file: - if line.startswith(">"): - out_file.write(line.strip()+"\n") - else: - out_file.write(line.strip().replace("-", "")+"\n") - out_file.close() - in_file.close() - output_fastas.append(output_fas) - return output_fastas - -def legend_figure(colors, lcs_shading_num, type_nuc=True, unit="%", filetype="png", max_lcs_len=None, min_lcs_len=0, bins=[], alphas=[], gff_legend=False, prefix="", verbose=False): - """ - create figure color legend - """ - max_legend_length_row = 8 - max_legend_length_col = 4 - - # define output file - if filetype not in ["png", "pdf", "svg"]: - text = "Provide valid file type - png, pdf, or svg" - logprint(text, start=False, printing=True) - filetype="png" - - # check if length of information fit - if not gff_legend and ((bins != [] and len(colors) != lcs_shading_num+1) or (bins != [] and len(colors) != len(bins)+1)): - if bins != [] and len(colors) != lcs_shading_num+1: - text = "**Attention**\nlcs_shading_num (%d) does not match number of colors (%d)!\n"% (lcs_shading_num, len(bins)) - elif bins != [] and len(colors) != len(bins)+1: - text = "**Attention**\nnumber of LCS length bins (%d) does not match number of colors (%d)!\n" % (len(colors), len(bins)) - logprint(text, start=False, printing=True) - elif gff_legend and len(bins) != len(colors): - text = "**Attention**\nnumber of GFF Feature Types (%d) does not match number of colors (%d)!\n" % (len(colors), len(bins)) - logprint(text, start=False, printing=True) - - # set alpha values to opaque if none are provided - if alphas == []: - for item in colors: - alphas.append(1) - - # legend data points - data_points = range(len(colors)) - if not gff_legend: - - # specify intervals, if max_lcs_len provided - if max_lcs_len != None: - multi_factor = 100 # one digit - if max_lcs_len <= 1: - multi_factor = 1000 # two digits - # len_interval_size = (max_lcs_len-min_lcs_len) * multi_factor *1. // lcs_shading_num * (1./ multi_factor) - len_interval_size = (max_lcs_len-min_lcs_len) * 1. / lcs_shading_num - len_pos = [float("%.2f" % (min_lcs_len))] - # calculate interval positions - for idx in range(lcs_shading_num): - len_pos.append(float("%.2f" % (len_pos[-1] + len_interval_size))) - - if prefix.startswith("custom-matrix") and (0 <= max_lcs_len <= 100 and 0 <= min_lcs_len <= 100): - unit = "%" - elif prefix.startswith("custom-matrix"): - unit = "" - - text = "\n%d Legend intervals from %.2f to %.2f: \n\t%s - number: %d, step: %.2f, unit: %s\n" % (lcs_shading_num+1, min_lcs_len, max_lcs_len, str(len_pos), len(len_pos), len_interval_size, unit) - logprint(text, start=False, printing=True) - pos = len_pos - interval_size = len_interval_size - else: - # generate legend labels acc. to standard interval notation - interval_size = 100 // lcs_shading_num - pos = range(interval_size, 101+interval_size, interval_size) - - if bins != []: # labels provided - legend_labels = bins[:] - legend_labels.append("max") - legend_labels_lengths = [] - for item in bins: - legend_labels_lengths.append("[%d %s, %d %s)" % (item - min(bins), unit, item, unit)) - if len(bins) == len(colors) - 1: - legend_labels_lengths.append("[%d %s, %s]" % (max(bins), unit, u"\u221E")) # infinite - - else: - legend_labels = [] - legend_labels_lengths = [] - for idx in range(len(pos)): - num = pos[idx] - legend_labels.append("[%d%%, %d%%)" % (num - interval_size, num)) - if max_lcs_len != None: - num = len_pos[idx] - # as int or float - if num == int(num) and int(len_interval_size) == len_interval_size: - legend_labels_lengths.append("[%d %s, %d %s)" % (num, unit, num + len_interval_size, unit)) - else: - legend_labels_lengths.append("[%.2f %s, %.2f %s)" % (num, unit, num + len_interval_size, unit)) - legend_labels[-1] = "100" + unit - if max_lcs_len != None: - if num == int(num) and int(len_interval_size) == len_interval_size: - legend_labels_lengths[-1] = "%d %s" % (max_lcs_len, unit) - else: - legend_labels_lengths[-1] = "%.2f %s" % (max_lcs_len, unit) - - # set labels and choose file name - if gff_legend: - label_text = bins[:] - edge_col = None - legend_file_name = "Selfdotplot_GFF_Shading_Legend_n%d." % lcs_shading_num + filetype - elif max_lcs_len != None: - label_text = legend_labels_lengths[:] - edge_col = "black" - legend_file_name = "Polydotplot_LCS_Shading_Legend_max%d%s_n%d." % (max_lcs_len, unit, lcs_shading_num) + filetype - elif bins != []: - label_text = legend_labels_lengths[:] - edge_col = "black" - legend_file_name = "Polydotplot_LCS_Shading_Legend_%d%s_n%d." % (bins[0], unit, lcs_shading_num) + filetype - else: - label_text = legend_labels[:] - edge_col = "black" - legend_file_name = "Polydotplot_LCS_Shading_Legend_%%len_n%d." % lcs_shading_num + filetype - - if prefix != None and prefix != "": - if not prefix.endswith("-"): - prefix = prefix + "-" - legend_type = "LCS" - if prefix.startswith("custom-matrix"): - prefix = prefix.replace("custom-matrix", "")[1:] - legend_type = "CustomMatrix" - legend_file_name = prefix + legend_file_name.replace("LCS", legend_type) - - # plot legend figure - fig, ax = P.subplots(3, 1, figsize=(len(colors)*2, len(colors)*2)) - for idx in range(len(colors)): - ax[0].bar(data_points[idx]+1, data_points[idx]+1, color=colors[idx], label=label_text[idx], - alpha=alphas[idx], edgecolor=edge_col) - ax[1].bar(data_points[idx]+1, 0, color=colors[idx], label=label_text[idx], - alpha=alphas[idx], edgecolor=edge_col) - ax[2].bar(data_points[idx]+1, 0, color=colors[idx], label=label_text[idx], - alpha=alphas[idx], edgecolor=edge_col) - ax[1].set_ylim(0,1) - ax[2].set_ylim(0,1) - ax[1].legend(ncol=((len(colors)-1)//max_legend_length_row)+1, framealpha=1) # vertical legend - col_num = len(colors) - if len(colors) > max_legend_length_col: - remainder = 0 - if len(colors) % max_legend_length_col != 0: - remainder = 1 - row_num = len(colors) // max_legend_length_col + remainder - remainder = 0 - if len(colors) % row_num != 0: - remainder = 1 - col_num = len(colors) // row_num + remainder - ax[2].legend(ncol=col_num, framealpha=1) # horizontal legend - - P.savefig(legend_file_name) - - return legend_file_name - - -############################### -# Analysis Functions # -############################### - -def wobble_replacement(sequence, general_ambiguity_code, verbose=False): - """ - get all degenerated sequences for sequence with ambiguous residues - (only residues considered that are keys in wobble_dictionary) - """ - - # get positions of ambiguous residues - wobble_pos = [] - for idx in range(len(sequence)): - letter = sequence[idx] - if letter in general_ambiguity_code.keys(): - wobble_pos.append(idx) - - if verbose: - text = "\t%d wobbles" % len(wobble_pos) - logprint(text, start=False, printing=True) - - # replace one wobble through each iteration by all possible residues - # repeat if still wobbles in new kmers - kmer_variants = [sequence] - while True: - if verbose: - text = "\t\t%d kmer variants" % len(kmer_variants) - logprint(text, start=False, printing=True) - temp_kmers = set([]) - for kmer in kmer_variants: - for idx in wobble_pos: - letter = kmer[idx] - if letter in general_ambiguity_code.keys(): - for base in general_ambiguity_code[kmer[idx]]: - newkmer = kmer[:idx] + base + kmer[idx+1:] - temp_kmers.add(newkmer) - wobble = False - for kmer in temp_kmers: - for idx in range(len(kmer)): - letter = kmer[idx] - if letter in general_ambiguity_code.keys(): - wobble = True - break - if wobble: - break - kmer_variants = set(list(temp_kmers)[:]) - if not wobble: - break - - return kmer_variants - -def split_diagonals(data, stepsize=1): - """ - split array if point difference exceeds stepsize - data = sorted list of numbers - """ - return np.split(data, np.where(np.diff(data) != stepsize)[0]+1) - -def longest_common_substring(s1, s2): - m = [[0] * (1 + len(s2)) for i in xrange(1 + len(s1))] - longest, x_longest = 0, 0 - for x in xrange(1, 1 + len(s1)): - for y in xrange(1, 1 + len(s2)): - if s1[x - 1] == s2[y - 1]: - m[x][y] = m[x - 1][y - 1] + 1 - if m[x][y] > longest: - longest = m[x][y] - x_longest = x - else: - m[x][y] = 0 - return longest - -def lcs_from_x_values(x_values): - """ - calculate length of longest common substring based on nested list of numbers - """ - if len(x_values) == 0: - return 0 - # get lengths of each subarray data - lengths = np.array([len(i) for i in x_values]) - return max(lengths) - - -############################### -# Matching Functions # -############################### - -def find_match_pos_diag(seq1, seq2, wordsize, report_lcs=False, rc_option=True, convert_wobbles=False, max_N_percentage=49, type_nuc=True, verbose=False): - """ - find all matching positions with matches >= wordsize - convert matching points into lines of the length of the match - (+ optional handling of ambiguities) - """ - global t1 # timer - - # look for Ns in DNA or Xs in proeins (minimum word size) - if type_nuc == True: - any_residue = "N" - else: - any_residue = "X" - - # read sequences - seq_one = seq1.upper(); len_one = len(seq_one) - seq_two = seq2.upper(); len_two = len(seq_two) - - # set ambiguity code for wobble replacement - general_ambiguity_code = alphabets(type_nuc)[2] # nucleotide_ambiguity_code or aminoacid_ambiguity_code - - # forward - ################################# - kmer_pos_dict_one = {}; kmer_pos_dict_two = {} # dictionaries for both sequences - - # reverse complement - ################################# - kmer_pos_dict_three = {}; kmer_pos_dict_four = {} # dictionaries for both sequences - - # create dictionaries with kmers (wordsize) and there position(s) in the sequence - if rc_option: - data_list = [(str(seq_one), kmer_pos_dict_one), - (str(seq_two), kmer_pos_dict_two), - (str(seq_one), kmer_pos_dict_three), - (str(seq_two.reverse_complement()), kmer_pos_dict_four)] - else: - data_list = [(str(seq_one), kmer_pos_dict_one), - (str(seq_two), kmer_pos_dict_two)] - for (seq, kmer_pos_dict) in data_list: - for i in range(len(seq)-wordsize+1): - kmer = seq[i:i+wordsize] - # discard kmer, if too many Ns included - if kmer.count(any_residue)*100./wordsize <= max_N_percentage: - if not convert_wobbles: - try: - kmer_pos_dict[kmer].append(i) - except KeyError: - kmer_pos_dict[kmer] = [i] - else: - wobbles = False - for item in general_ambiguity_code.keys(): - if item in kmer: - wobbles = True - break - if not wobbles: - try: - kmer_pos_dict[kmer].append(i) - except KeyError: - kmer_pos_dict[kmer] = [i] - else: - kmer_variants = wobble_replacement(kmer, general_ambiguity_code) - for new_kmer in kmer_variants: - # print "\t", new_kmer - try: - kmer_pos_dict[new_kmer].append(i) - except KeyError: - kmer_pos_dict[new_kmer] = [i] - - # find kmers shared between both sequences - matches_for = set(kmer_pos_dict_one).intersection(kmer_pos_dict_two) # forward - matches_rc = set(kmer_pos_dict_three).intersection(kmer_pos_dict_four) # reverse complement - - if verbose: - text = "[matches: %i for; %.i rc]" % (len(matches_for), len(matches_rc)) - logprint(text, start=False, printing=True) - - # create lists of x and y co-ordinates for scatter plot - # keep all coordinates of all shared kmers (may match multiple times) - diag_dict_for = {} - diag_dict_rc = {} - for (match_list, pos_dict1, pos_dict2, diag_dict) in [(matches_for, kmer_pos_dict_one, kmer_pos_dict_two, diag_dict_for), - (matches_rc, kmer_pos_dict_three, kmer_pos_dict_four, diag_dict_rc)]: - for kmer in match_list: - for i in pos_dict1[kmer]: - for j in pos_dict2[kmer]: - diag = i-j - points = set(range(i+1, i+wordsize+1)) - if not diag in diag_dict.keys(): - diag_dict[diag] = points - else: - diag_dict[diag].update(points) - - # convert coordinate points to line start and stop positions - x1 = [] # x values reverse - y1 = [] # y values forward - for diag in diag_dict_for.keys(): - x_values = np.array(sorted(diag_dict_for[diag])) - x1.extend(split_diagonals(x_values)) - y_values = split_diagonals(x_values - diag) - y1.extend(y_values) - - x2 = [] # x values rc - y2 = [] # y values rc - if rc_option: - for diag in diag_dict_rc.keys(): - factor = len_two + diag + 1 - x_values = np.array(sorted(diag_dict_rc[diag])) - x2.extend(split_diagonals(x_values)) - y_values = split_diagonals(factor - x_values, -1) - y2.extend(y_values) - - if verbose: - t1 = time_track(t1) - - if not report_lcs: - return np.array(x1), np.array(y1), np.array(x2), np.array(y2) - else: - # get length of longest common substring based on match lengths - lcs_for = lcs_from_x_values(x1) - lcs_rev = lcs_from_x_values(x2) - return np.array(x1), np.array(y1), np.array(x2), np.array(y2), lcs_for, lcs_rev - -def find_match_pos_regex(seq1, seq2, wordsize, substitution_count=0, report_lcs=False, rc_option=True, convert_wobbles=False, max_N_percentage=49, type_nuc=True, verbose=False): - """ - find all matching positions with matches >= wordsize via regular expression search - fuzzy matching - allow up to substitution_count substitutions - convert matching points into lines of the length of the match - (+ optional handling of ambiguities) - """ - global t1 # timer - - # read sequences - seq_one = seq1.upper(); len_one = len(seq_one) - seq_two = seq2.upper(); len_two = len(seq_two) - - # set ambiguity code for wobble replacement - general_ambiguity_code = alphabets(type_nuc)[2] # nucleotide_ambiguity_code or aminoacid_ambiguity_code - ambiguity_match_dict = alphabets(type_nuc)[3] - - ambiq_residues = "[%s]" % "".join(general_ambiguity_code.keys()) - - # look for Ns in DNA or Xs in proeins (minimum word size) - if type_nuc == True: - any_residue = "N" - else: - any_residue = "X" - - # check for wobble presence - if not (regex.search(ambiq_residues, str(seq_one)) == None and regex.search(ambiq_residues, str(seq_two)) == None): - wobble_found = True - else: - wobble_found = False - - # dictionary for matches - diag_dict_for = {} - diag_dict_rc = {} - counter = [0, 0] - - # one-way matching - if rc_option: - data_list = [(str(seq_one), str(seq_two), diag_dict_for, 0), - (str(seq_one), str(seq_two.reverse_complement()), diag_dict_rc, 1)] - else: - data_list = [(str(seq_one), str(seq_two), diag_dict_for, 0)] - - for seq_query, seq_target, diag_dict, counter_pos in data_list: - # split query sequence into kmers - if not rc_option and counter_pos == 1: - break - - for idx in range(len(str(seq_query))-wordsize+1): - kmer = str(seq_query)[idx:idx+wordsize] - - # skip excessive N/X stretches (big black areas) - if kmer.count(any_residue)*100./wordsize <= max_N_percentage: - # convert kmer to regular expression for wobble_matching - if convert_wobbles and wobble_found: - kmer_string = "" - # replace each residue with matching residues or wobbles - for jdx in range(len(kmer)): - kmer_string += ambiguity_match_dict[kmer[jdx]] - else: - kmer_string = kmer - - # convert to regular expression tolerating substitution errors - if type(substitution_count) == int and substitution_count != 0: - kmer_string = "(%s){s<=%d}" % (kmer_string, substitution_count) - - # search for regular expression in target sequence - kdx = 0 - start = True - if regex.search(kmer_string, seq_target[kdx:]) != None: - counter[counter_pos] += 1 - while regex.search(kmer_string, seq_target[kdx:]) != None: - # search for regular expression pattern in target sequence - result = regex.search(kmer_string, seq_target[kdx:]) - - kmer2 = seq_target[kdx:][result.start():result.end()] - - # skip excessive N/X stretches (big black areas) - if kmer2.count(any_residue)*100./wordsize <= max_N_percentage: - diag = idx-(kdx+result.start()) - points = set(range(idx+1, idx+wordsize+1)) - if not diag in diag_dict.keys(): - diag_dict[diag] = points - else: - diag_dict[diag].update(points) - - kdx += result.start() + 1 - if kdx >= len(seq_target): - break - elif regex.search(kmer_string, seq_target[kdx:]) != None: - counter[counter_pos] += 1 - - if verbose: - text = "%5.i \tforward matches" % counter[0] - text += "\n%5.i \treverse complementary matches" % counter[1] - logprint(text, start=False, printing=True) - - # convert coordinate points to line start and stop positions - x1 = [] # x values reverse - y1 = [] # y values forward - for diag in diag_dict_for.keys(): - x_values = np.array(sorted(diag_dict_for[diag])) - x1.extend(split_diagonals(x_values)) - y_values = split_diagonals(x_values - diag) - y1.extend(y_values) - - x2 = [] # x values rc - y2 = [] # y values rc - if rc_option: - for diag in diag_dict_rc.keys(): - factor = len_two + diag + 1 - x_values = np.array(sorted(diag_dict_rc[diag])) - x2.extend(split_diagonals(x_values)) - y_values = split_diagonals(factor - x_values, -1) - y2.extend(y_values) - - if verbose: - t1 = time_track(t1) - - if not report_lcs: - return np.array(x1), np.array(y1), np.array(x2), np.array(y2) - else: - # get length of longest common substring based on match lengths - lcs_for = lcs_from_x_values(x1) - lcs_rev = lcs_from_x_values(x2) - return np.array(x1), np.array(y1), np.array(x2), np.array(y2), lcs_for, lcs_rev - - -############################### -# Dot Plot Functions # -############################### - -def selfdotplot(input_fasta, wordsize, prefix=None, plot_size=10, label_size=10, filetype='png', type_nuc=True, convert_wobbles=False, substitution_count=0, alphabetic_sorting=False, max_N_percentage=49, verbose=False, multi=True, ncols=4, nrows=5, gff_files=[], gff_color_dict={"others": ("grey", 1, 0)}, title_length=float("Inf")): - """ - self-against-self dotplot - partially from biopython cookbook - """ - - # read sequences - seq_dict, sequences = read_seq(input_fasta) - if seq_dict == {}: - logprint("\nFailed to load sequences") - return [] - - if alphabetic_sorting: - sequences = sorted(sequences) - - # check if at least one input sequence - if len(sequences) == 0: - text = "\n%s\n\nCreating %s selfdotplot images\n%s\n\n=>" % (50*"=", len(sequences), 28*"-") - text += " No sequences provided for selfdotplot!\n\nTerminating polydotplot!" - logprint(text, start=False, printing=True) - return - elif len(sequences) == 1 and multi: - text = "\n\nCreating collage output for single selfdotplot!" - text += "\nRecommendation: Change to individual mode by using '--collage_output n'!\n\n" - logprint(text, start=False, printing=True) - - if multi and (ncols == 0 or nrows == 0): - ncols = max(ncols, 1) - nrows = max(nrows, 1) - text = "\n\nSelfdotplot Collage: Invalid collage - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - if multi and ncols > len(sequences): - ncols = len(sequences) - nrows = 1 - text = "\n\nSelfdotplot Collage: Few sequences - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - elif multi and ncols*(nrows-1) > len(sequences): - nrows = ((len(sequences)-1) // ncols) + 1 - text = "\n\nSelfdotplot Collage: Few sequences - correcting number of rows:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - if multi and not (nrows == 1 and ncols == 1) and plot_size <= label_size/2: - label_size = plot_size * 3 // 2 - text = "Reducing label size for better visualization to %d\n" % label_size - logprint(text, start=False, printing=True) - - # read gff annotation data if provided for shading - if gff_files != None and gff_files != []: - text = "\n%s\n\nReading %s GFF annotation files\n%s\n\n=> %s\n" % (50*"=", len(gff_files), 28*"-", ", ".join(gff_files)) - logprint(text, start=False, printing=True) - feat_dict = read_gffs(gff_files, color_dict=gff_color_dict, type_nuc=type_nuc, prefix=prefix, filetype=filetype, verbose=verbose) - - # check input variables - if convert_wobbles and max_N_percentage > 49: - max_N_percentage=49 - text = "Provide valid max_N_percentage, kmers with >=50% Ns are ignored\n" - logprint(text, start=False, printing=True) - - if filetype not in ["png", "pdf", "svg"]: - text = "Provide valid file type - png, pdf, or svg - given:%s\n" % filetype - logprint(text, start=False, printing=True) - filetype = "png" - - global t1 - - print "\n%s\n\nCreating %s selfdotplot images\n%s\n\n=>" % (50*"=", len(sequences), 28*"-"), - log_txt = "\n%s\n\nCreating %s selfdotplot images\n%s\n\n=>" % (50*"=", len(sequences), 28*"-") - - # preparations for file name - name_graph = "Selfdotplots" - if prefix != None: - if not prefix[-1] == "-": - prefix = prefix + "-" - else: - prefix = "" - suffix = "" - if convert_wobbles: - suffix += "_wobbles" - if substitution_count != 0: - suffix += "_S%d" % substitution_count - if multi: - suffix += "_collage" - - # calculate fig ratios - if not multi: - ncols = 1 - nrows = 1 - figsize_x, figsize_y = calc_fig_ratio(ncols, nrows, plot_size) - - P.cla() # clear any prior graph - if multi: - fig = P.figure(figsize=(figsize_x, figsize_y)) - page_counter = 1 - list_of_png_names = [] - - counter = 0 - for seq_name in sequences: - print seq_name, - log_txt += " " + seq_name - - counter += 1 - if not multi: - P.cla() # clear any prior graph - - # read sequence - seq_record = seq_dict[seq_name] - name_seq = seq_record.id - seq_one = seq_record.seq.upper() - length_seq = len(seq_one) - - # get positions of matches - if substitution_count != 0: - # print "RE" - x_lists, y_lists, x_lists_rc, y_lists_rc = find_match_pos_regex(seq_one, seq_one, wordsize, substitution_count=substitution_count, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, type_nuc=type_nuc, verbose=verbose) - else: - # print "DIAG", - x_lists, y_lists, x_lists_rc, y_lists_rc = find_match_pos_diag(seq_one, seq_one, wordsize, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, type_nuc=type_nuc, verbose=verbose) - - # plotting with matplotlib - ################################# - - # combined plotting - if multi: - # plotting subplot with matplotlib - ax = P.subplot(nrows, ncols, counter) # rows, columns, plotnumber - - # shade annotated regions - if gff_files != None and gff_files != []: - if seq_name in feat_dict.keys(): - features = feat_dict[seq_name] - for item in features: - feat_type, start, stop = item - feat_color, strength, zoom = gff_color_dict[feat_type.lower()] - start = max(0, start - zoom - 0.5) - stop = min(length_seq+1, stop + zoom + 0.5) - width = stop - start - ax.add_patch(patches.Rectangle((start, start), # (x,y) - width, width, # width, height - edgecolor=None, linewidth=line_width+zoom, - fill=True, facecolor=feat_color, - alpha=strength)) - - # collect lines - lines = [] - color_list = [] - for (x_lines, y_lines, col) in [(x_lists_rc, y_lists_rc, line_col_rev), (x_lists, y_lists, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # format axes - P.xlim(0, length_seq+1) - P.ylim(length_seq+1, 0) # rotate y axis (point downwards) - P.xlabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.ylabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - P.title(unicode_name(shorten_name(name_seq, max_len=title_length)), fontsize=label_size, fontweight='bold') - # P.title(unicode_name(name_seq), fontsize=label_size*1.3, fontweight='bold') - - # save figure and reinitiate if page is full - if counter == ncols * nrows: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - P.subplots_adjust(hspace=0.5, wspace=0.5) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' % (prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() - - list_of_png_names.append(fig_name) - - counter = 0 - page_counter += 1 - - fig = P.figure(figsize=(figsize_x, figsize_y)) - - # plotting separate figure files - else: # not multi - - fig = P.figure(figsize=(plot_size, plot_size)) # figure size needs to be a square - ax = P.subplot(1, 1, 1) # rows, columns, plotnumber - - # shade annotated regions - if gff_files != None and gff_files != []: - if seq_name in feat_dict.keys(): - features = feat_dict[seq_name] - for item in features: - feat_type, start, stop = item - feat_color, strength, zoom = gff_color_dict[feat_type.lower()] - start = max(0, start - zoom - 0.5) - stop = min(length_seq+1, stop + zoom + 0.5) - width = stop - start - ax.add_patch(patches.Rectangle((start, start), # (x,y) - width, width, # width, height - edgecolor=None, linewidth=line_width+zoom, - fill=True, facecolor=feat_color, - alpha=strength)) - - # collect lines - lines = [] - number = 0 - color_list = [] - for (x_lines, y_lines, col) in [(x_lists_rc, y_lists_rc, line_col_rev), (x_lists, y_lists, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # format axes - P.xlim(0, length_seq+1) - P.ylim(length_seq+1, 0) # rotate y axis (point downwards) - P.xlabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.ylabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - P.title(unicode_name(shorten_name(name_seq, max_len=title_length)), fontsize=label_size*1.3, fontweight='bold') - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s-%d_%s_wordsize%i%s.%s' %(prefix, name_graph, counter, name_seq, wordsize, suffix, filetype) - P.savefig(fig_name, bbox_inches='tight') - - P.close() - P.cla() # clear any prior graph - - list_of_png_names.append(fig_name) - - if multi and counter >= 1: - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - P.subplots_adjust(hspace=0.5, wspace=0.5) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' %(prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() # clear any prior graph - - list_of_png_names.append(fig_name) - - print "\n\nDrawing selfdotplots done" - log_txt += "\n\nDrawing selfdotplots done" - logprint(log_txt, start=False, printing=False) - - return list_of_png_names - -def pairdotplot(input_fasta, wordsize, prefix=None, plot_size=10, label_size=10, filetype='png', type_nuc=True, convert_wobbles=False, substitution_count=0, alphabetic_sorting=False, max_N_percentage=49, verbose=False, multi=True, ncols=4, nrows=5, length_scaling=True, scale_delim_col="red", title_length=float("Inf")): - """ - pairwise dotplot (all-against-all) - """ - - # read sequences - seq_dict, sequences = read_seq(input_fasta) - if seq_dict == {}: - logprint("\nFailed to load sequences") - return [] - - if alphabetic_sorting: - sequences = sorted(sequences) - - # check if at least two input sequences - if len(sequences) < 2: - text = "\n%s\n\nCreating %d paired dotplot image \n%s\n\n=>" % (50*"=", len(sequences)*(len(sequences)-1)/2, 36*"-") - text += " Please provide at least two sequences for pairdotplot!\n\nTerminating paired dotplot!" - logprint(text, start=False, printing=True) - return - elif len(sequences) == 2 and multi: - text = "\n\nCreating collage output for single pairdotplot!" - text += "\nRecommendation: Change to individual mode by using '--collage_output n'!\n\n" - logprint(text, start=False, printing=True) - - if multi and (ncols == 0 or nrows == 0): - ncols = max(ncols, 1) - nrows = max(nrows, 1) - text = "\n\nPairdotplot Collage: Invalid collage settings - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - if multi and ncols > len(sequences)*(len(sequences)-1): - ncols = len(sequences) - nrows = 1 - text = "\n\nPairdotplot Collage: Few sequences - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - elif multi and ncols*(nrows-1) > len(sequences)*(len(sequences)-1): - nrows = ((len(sequences)-1) // ncols) + 1 - text = "\n\nPairdotplot Collage: Few sequences - correcting number of rows:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - - text = "\n%s\n\nCreating %d paired dotplot image for\n%s\n\n=>" % (50*"=", len(sequences)*(len(sequences)-1)/2, 36*"-") - text += ", ".join(sequences) + "\n" - logprint(text, start=False, printing=True) - - if multi and not (nrows == 1 and ncols == 1) and plot_size <= label_size/2: - label_size = plot_size * 3 // 2 - text = "Reducing label size for better visualization to %d\n" % label_size - logprint(text, start=False, printing=True) - - y_label_rotation = "vertical" - - # check input variables - if convert_wobbles and max_N_percentage > 49: - max_N_percentage=49 - text = "Provide valid max_N_percentage, kmers with >50% are ignored\n" - logprint(text, start=False, printing=True) - - if filetype not in ["png", "pdf", "svg"]: - text = "Provide valid file type - png, pdf, or svg - given: %s\n" % filetype - logprint(text, start=False, printing=True) - filetype = "png" - - # preparations for file name - name_graph = "Pairdotplot" - if prefix != None: - if not prefix[-1] == "-": - prefix = prefix + "-" - else: - prefix = "" - suffix = "" - if convert_wobbles: - suffix += "_wobbles" - if substitution_count != 0: - suffix += "_S%d" % substitution_count - if length_scaling: - suffix += "_scaled" - if multi: - suffix += "_collage" - - - - # calculate fig ratios - if not multi: - ncols = 1 - nrows = 1 - figsize_x, figsize_y = calc_fig_ratio(ncols, nrows, plot_size) - - P.cla() # clear any prior graph - list_of_png_names = [] - if multi: - fig = P.figure(figsize=(figsize_x, figsize_y)) - page_counter = 1 - - # prepare LCS data file - lcs_data_file = open("%sPairdotplot_lcs_data_file%s.txt" % (prefix, suffix.replace("_scaled", "").replace("_collage", "")), 'w') - lcs_data_file.write("\t".join(["#title1", "title2", "len_seq1", "len_seq2", "len_lcs_for", "%_min_seq_len", "len_lcs_rev", "%_min_seq_len"])+"\n") - - counter, seq_counter = 0, 0 - print "Drawing pairwise dotplot...", - log_txt = "Drawing pairwise dotplot..." - if verbose: - seq_text = "" - for idx in range(len(sequences)-1): - if verbose: - print "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]), - seq_text += "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]) - rec_two = seq_dict[sequences[idx]] - name_two = rec_two.id - seq_two = rec_two.seq - len_two = len(seq_two) - - for jdx in range(idx+1, len(sequences)): - rec_one = seq_dict[sequences[jdx]] - name_one = rec_one.id - seq_one = rec_one.seq - len_one = len(seq_one) - - counter += 1 - seq_counter += 1 - if verbose: - print sequences[jdx], - seq_text += " " + sequences[jdx] - elif not seq_counter % 25: - print seq_counter, - log_txt += " " + str(seq_counter) - - # get positions of matches - if substitution_count != 0: - # print "RE" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_regex(seq_one, seq_two, wordsize, substitution_count=substitution_count, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - else: - # print "DIAG" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_diag(seq_one, seq_two, wordsize, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - - # write LCS data file - lcs_data_file.write("\t".join([name_one, name_two, str(len_one), str(len_two), - str(lcs_for), str(round((lcs_for*100./min(len_one, len_two)), 3)), - str(lcs_rev), str(round((lcs_rev*100./min(len_one, len_two)), 3))]) + "\n") - - - # plotting with matplotlib - ################################# - - # combined plotting - if multi: - # plotting subplot with matplotlib - ax = P.subplot(nrows, ncols, counter) # rows, columns, plotnumber - else: - # calculate figure size for separate figures - if len_one >= len_two: - sizing = (plot_size, max(2, (plot_size)*len_two*1./len_one)) - # sizing = (plot_size, min(plot_size, max(2, (plot_size-2)*len_two*1./len_one+2))) - else: - sizing = (max(2, (plot_size)*len_one*1./len_two), plot_size) - # sizing = (min(plot_size, max(2, (plot_size-2)*len_one*1./len_two+2)), plot_size) - fig = P.figure(figsize=(plot_size, plot_size)) - - ax = P.subplot(1, 1, 1) - - # collect lines - lines = [] - color_list = [] - for (x_lines, y_lines, col) in [(x2, y2, line_col_rev), (x1, y1, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # format axes - P.xlabel(unicode_name(shorten_name(name_one, max_len=title_length)) + " [%s]" % aa_bp_unit, fontsize=label_size, fontweight='bold', labelpad=4) - P.ylabel(unicode_name(shorten_name(name_two, max_len=title_length)) + " [%s]" % aa_bp_unit, fontsize=label_size, fontweight='bold', labelpad=4) - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - - if not multi: - if length_scaling: - ax.set_aspect(aspect='equal', adjustable='box', anchor='NW') - P.xlim(0, len_one+1) - P.ylim(len_two+1, 0) # rotate y axis (point downwards) - elif not length_scaling: - P.xlim(0, len_one+1) - P.ylim(len_two+1, 0) # rotate y axis (point downwards) - else: - max_len = max(len_one, len_two) - P.xlim(0, max_len+1) - P.ylim(max_len+1, 0) # rotate y axis (point downwards) - - # plot line deliminating shorter sequence - if max_len != len_one: - ax.plot((len_one+1, len_one+1), (0, len_two), marker="", linestyle="--", color=scale_delim_col, markerfacecolor="r") - if max_len != len_two: - ax.plot((0, len_one), (len_two+1, len_two+1), marker="", linestyle="--", color=scale_delim_col, markerfacecolor="r") - - # evtl. switch x axis position - if x_label_pos_top: - ax.xaxis.tick_top() - ax.xaxis.set_label_position('top') - P.setp(ax.get_xticklabels(), fontsize=label_size*.9) - P.setp(ax.get_yticklabels(), fontsize=label_size*.9) - - # save figure and reinitiate if page is full - if multi and counter == ncols * nrows: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - if x_label_pos_top: - P.subplots_adjust(hspace=.5, wspace=.5, top=0.95) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=.5, wspace=.5, bottom=0.05) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' %(prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() - - list_of_png_names.append(fig_name) - - counter = 0 - page_counter += 1 - - fig = P.figure(figsize=(figsize_x, figsize_y)) - - # plotting separate figure files - elif not multi: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - if y_label_rotation == "horizontal": - if x_label_pos_top: - P.subplots_adjust(hspace=0.02, wspace=0.02, left=0.13, top=0.95) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=0.02, wspace=0.02, left=0.13, bottom=0.05) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=0.02, wspace=0.02) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s-%d_wordsize%i%s.%s' % (prefix, name_graph, counter, wordsize, suffix, filetype) - P.savefig(fig_name) - P.close() - P.cla() - - list_of_png_names.append(fig_name) - fig = P.figure() - - # save figure - if multi and counter >= 1: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - if x_label_pos_top: - P.subplots_adjust(hspace=0.5, wspace=0.5, top=0.95) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=0.5, wspace=0.5, bottom=0.05) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' %(prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() - - list_of_png_names.append(fig_name) - - if not verbose: - print seq_counter, "done" - log_txt += str(seq_counter) + " done" - else: - print "\n%d done" % seq_counter - log_txt += "\n%d done" % seq_counter - logprint(log_txt, start=False, printing=False) - - if verbose: - print - logprint(seq_text, start=False, printing=False) - - return list_of_png_names - -def polydotplot(input_fasta, wordsize, prefix=None, plot_size=10, label_size=10, filetype='png', type_nuc=True, convert_wobbles=False, substitution_count=0, alphabetic_sorting=False, max_N_percentage=49, verbose=False, lcs_shading=True, lcs_shading_ref=0, lcs_shading_interval_len=100, lcs_shading_ori=0, lcs_shading_num=5, spacing=0.04, input_user_matrix_file="", user_matrix_print=True, gff_files=[], gff_color_dict={"others": ("grey", 1, 0)}, title_length=float("Inf"), rotate_labels=False): - """ - all-against-all dotplot - derived from dotplot function - - lcs_shading_refs: - 0 color relative to maximum lcs observed in dataset [default] - 1 color by coverage of shorter sequence (e.g. lcs = 70% of seq1) - lcs_shading_ori - 0 forward only - 1 reverse only - 2 both orientations (in opposite plot) - """ - - # read sequences - seq_dict, sequences = read_seq(input_fasta) - if seq_dict == {}: - logprint("\nFailed to load sequences") - return [] - - if alphabetic_sorting: - sequences = sorted(sequences) - - if len(sequences) == 0: - text = "\n%s\n\nCreating %dx%d polydotplot image\n%s\n\n=>" % (50*"=", len(sequences), len(sequences), 30*"-") - text += " No sequences provided for polydotplot!\n\nTerminating polydotplot!" - logprint(text, start=False, printing=True) - return - elif len(sequences) == 1: - text = "\n\nCreating polydotplot for single sequence!" - text += "\nRecommendation: Use selfdotplot via '--plotting_mode 0'!\n\n" - logprint(text, start=False, printing=True) - - - text = "\n%s\n\nCreating %dx%d polydotplot image\n%s\n\n=>" % (50*"=", len(sequences), len(sequences), 30*"-") - text += " " + " ".join(sequences) + "\n" - logprint(text, start=False, printing=True) - - # check input variables - if convert_wobbles and max_N_percentage > 49: - max_N_percentage=49 - text = "Provide valid max_N_percentage, kmers with >50% are ignored\n" - logprint(text, start=False, printing=True) - - if filetype not in ["png", "pdf", "svg"]: - text = "Provide valid file type - png, pdf, or svg - given: %s\n" % filetype - logprint(text, start=False, printing=True) - filetype = "png" - - if lcs_shading and not type_nuc: - if lcs_shading_ori != 0: - lcs_shading_ori = 0 - text = "Protein shading does not support reverse complementary matching!\n" - logprint(text, start=False, printing=True) - - # read custom shading matrix & match names of sequences to fasta - if input_user_matrix_file != "" and input_user_matrix_file != None: - logprint("Reading user matrix file: %s" % input_user_matrix_file) - # lcs_shading_ori = 2 - custom_dict = read_matrix(input_user_matrix_file) - if custom_dict != {}: - custom_shading = True - custom_similarity_dict = {} - invalid_entries = [] - custom_max = 0 - custom_min = float("Inf") - for key in custom_dict.keys(): - number_key = [] - - # convert number into float - try: - value = float(custom_dict[key]) - if not "." in custom_dict[key]: - value = int(custom_dict[key]) - custom_max = max(custom_max, value) - custom_min = min(custom_min, value) - except: - value = custom_dict[key] - if value == "": - value = None - invalid_entries.append(key) - # match matrix names with sequence names - for item in key: - if item in sequences: - number_key.append(sequences.index(item)) - else: - number_key.append(-1) - # dictionary with tuple of sorted sequence indices as key and number as value - custom_similarity_dict[tuple(sorted(number_key))] = value - if len(invalid_entries) != 0: - text = "No valid number in custom similarity matrix for %d entries: \n\t" % (len(invalid_entries)) - for key in invalid_entries: - text += str(key) + " - " + str(custom_dict[key]) + "; " - logprint(text[:-2]+"\n") - - text = "Custom user matrix given: min %.2f, max %.2f\n" % (custom_min, custom_max) - - # artificially rounding intervals if likely identity/divergence percentages - if 0 <= custom_min < 1 and 0 < custom_max <= 1: - rounding_factor = 5 - multi_factor = 100 - text += " > artificially rounding custom shading intervals: old (%.2f, %.2f) - " % (custom_min, custom_max) - custom_min = max(0, (multi_factor*custom_min // rounding_factor) * (1.*rounding_factor/multi_factor)) - custom_max = min((multi_factor*custom_max // rounding_factor) * (1.*rounding_factor/multi_factor), 1) - text += "new (%.2f, %2f)\n" % (custom_min, custom_max) - - elif 0 <= custom_min < 100 and 0 < custom_max <= 100: - rounding_factor = 5 - text += " > artificially rounding custom shading intervals: old (%.2f, %.2f) - " % (custom_min, custom_max) - custom_min = max(0, (custom_min // rounding_factor) * rounding_factor) - custom_max = min((custom_max // rounding_factor) * rounding_factor, 100) - text += "new (%d, %d)\n" % (custom_min, custom_max) - - logprint(text) - - else: - custom_shading = False - - # read gff annotation data if provided for shading - if gff_files != None and gff_files != []: - text = "\n%s\n\nReading %s GFF annotation files\n%s\n\n=> %s\n" % (50*"=", len(gff_files), 28*"-", ", ".join(gff_files)) - logprint(text, start=False, printing=True) - feat_dict = read_gffs(gff_files, color_dict=gff_color_dict, type_nuc=type_nuc, prefix=prefix, filetype=filetype, verbose=verbose) - - name_graph = "Polydotplot" - suffix = "" - if convert_wobbles: - suffix += "_wobbles" - if substitution_count != 0: - suffix += "_S%d" % substitution_count - if custom_shading: - suffix += "_matrix" - if lcs_shading: - suffix += "_%dshades_ref%d_ori%s" % (lcs_shading_num+1, lcs_shading_ref, lcs_shading_ori) - if "ref2" in suffix and type_nuc: - suffix = suffix.replace("ref2", "%dbp" % lcs_shading_interval_len) - elif "ref2" in suffix: - suffix = suffix.replace("ref2", "%daa" % lcs_shading_interval_len) - - - # name and create output files (names derived from SEQNAME) - if prefix != None and str(prefix) != "": - prefix = str(prefix) + "-" - else: - prefix = "" - - # preparations for background shading - if lcs_shading or custom_shading: - # create color range white to grey - colors = create_color_list(lcs_shading_num+1, color_map=None, logging=True) - colors_2 = create_color_list(lcs_shading_num+1, color_map="OrRd", logging=True) - - if custom_shading: - text = "Custom Matrix Colors: " + ", ".join(colors_2) - - # write lcs lengths to file - lcs_data_file = open("%sPolydotplot_lcs_data_file%s.txt" % (prefix, suffix.replace("_scaled", "").replace("_collage", "")), 'w') - lcs_data_file.write("\t".join(["#title1", "title2", "len_seq1", "len_seq2", "len_lcs_for", "%_min_seq_len", "len_lcs_rev", "%_min_seq_len"])+"\n") - - # compare sequences pairwise - save lcs and line information in dictionary for plotting - data_dict = {} # keys = tuple(idx, jdx), value = x1, y1, x2, y2 (line positions) - lcs_dict = {} # keys = tuple(idx, jdx), value = length of lcs: lcs_len or (lcs_for, lcs_rev) - for_lcs_set = set([]) # keep lengths to calculate max (excluding self comparisons) - rev_lcs_set = set([]) # keep lengths to calculate max (all) - - text = "\nTotal plot count: %d" % (len(sequences)*(len(sequences))) - text += "\nTotal calculations: %d" % (len(sequences)*(len(sequences)+1)/2) - logprint(text, start=False, printing=True) - - print "\nCalculating shared regions and lengths of longest_common_substring...", - log_txt = "\nCalculating shared regions and lengths of longest_common_substring..." - # determine matches and length of lcs by comparing all sequence pairs - if verbose: - seq_text = "" - counter = 0 - for idx in range(len(sequences)): - if verbose: - print "\n%d\t%s vs." % ((counter+1), sequences[idx]), - seq_text += "\n%d\t%s vs." % ((counter+1), sequences[idx]) - rec_two = seq_dict[sequences[idx]] - name_two = rec_two.id - seq_two = rec_two.seq - len_two = len(seq_two) - - for jdx in range(idx, len(sequences)): - rec_one = seq_dict[sequences[jdx]] - name_one = rec_one.id - seq_one = rec_one.seq - len_one = len(seq_one) - - counter += 1 - if verbose: - print sequences[jdx], - seq_text += " " + sequences[jdx] - elif len(sequences) < 5: - print "\t%s (%d %s), %s (%d %s)" % (name_one, len_one, aa_bp_unit, name_two, len_two, aa_bp_unit) - log_txt += "\t%s (%d %s), %s (%d %s)\n" % (name_one, len_one, aa_bp_unit, name_two, len_two, aa_bp_unit) - else: - if not counter % 25: - print counter, - log_txt += str(counter) - - # get positions of matches & length of longest common substring based on match lengths - if substitution_count != 0: - # print "RE" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_regex(seq_one, seq_two, wordsize, substitution_count=substitution_count, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - else: - # print "DIAG" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_diag(seq_one, seq_two, wordsize, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - data_dict[(idx, jdx)] = x1[:], y1[:], x2[:], y2[:] - lcs_dict[idx, jdx] = lcs_for, lcs_rev - - if idx != jdx: - for_lcs_set.add(lcs_for) - rev_lcs_set.add(lcs_rev) - - lcs_data_file.write("\t".join([name_one, name_two, str(len_one), str(len_two), - str(lcs_for), str(round((lcs_for*100./min(len_one, len_two)), 3)), - str(lcs_rev), str(round((lcs_rev*100./min(len_one, len_two)), 3))]) + "\n") - - if not verbose: - print len(sequences)*(len(sequences)+1)/2, " done\n" - log_txt += str(len(sequences)*(len(sequences)+1)/2) + " done\n" - else: - print "\n%d done" % (len(sequences)*(len(sequences)+1)/2) - log_txt += "\n%d done" % (len(sequences)*(len(sequences)+1)/2) - logprint(log_txt, start=False, printing=False) - - if verbose: - logprint ("\n\nlcs_dict\n" + str(lcs_dict)) - if custom_shading: - logprint ("\ncustom_dict\n" + str(custom_dict)) - logprint ("\ncustom_similarity_dict\n\n" + str(custom_similarity_dict)) - - if verbose: - print - logprint(seq_text+"\n", start=False, printing=False) - - if lcs_shading_ref == 2: - color_bins = [] - text = "\nLCS lengh bins: " - for idx in range(lcs_shading_num): - color_bins.append(lcs_shading_interval_len*(idx+1)) - text += " " + str(lcs_shading_interval_len*(idx+1)) - logprint(text, start=False, printing=True) - - # calculate maximum lcs length - if lcs_shading_ori == 0: # forward only - if len(for_lcs_set) != 0: - max_lcs = max(for_lcs_set) - else: - max_lcs = None - elif lcs_shading_ori == 1: # reverse complement only - if len(rev_lcs_set) != 0: - max_lcs = max(rev_lcs_set) - else: - max_lcs = None - else: # both orientations - if len(rev_lcs_set) != 0 and len(for_lcs_set) != 0: - max_lcs = max(max(rev_lcs_set), max(for_lcs_set)) - elif len(rev_lcs_set) != 0: - max_lcs = max(rev_lcs_set) - elif len(for_lcs_set) != 0: - max_lcs = max(for_lcs_set) - else: - max_lcs = None - - if not max_lcs == None: - text = "Maximum LCS: %d %s" % (max_lcs, aa_bp_unit) - logprint(text, start=False, printing=True) - if custom_shading: - text = "Maximum custom value: %d\n" % custom_max - logprint(text, start=False, printing=True) - - # count sequences - ncols = len(sequences); nrows = len(sequences) - - # get sequence lengths to scale plot widths and heights accordingly - size_ratios = [] - for item in sequences: - size_ratios.append(len(seq_dict[item].seq)) - - P.cla() # clear any prior graph - # use GridSpec to resize plots according to sequence length - gs = gridspec.GridSpec(nrows, ncols, - width_ratios=size_ratios, - height_ratios=size_ratios) - fig = P.figure(figsize=(plot_size, plot_size)) - - # determine label orientations - if len(sequences) > 5 or rotate_labels: - x_label_rotation = 45 - y_label_rotation = "horizontal" - if x_label_pos_top: - xhalign = 'left' - xvalign = 'bottom' - else: - xhalign = 'right' - xvalign = 'top' - yhalign = "right" - else: - x_label_rotation = "horizontal" - y_label_rotation = "vertical" - xvalign = "center" - xhalign = "center" - yhalign = "center" - yvalign = 'center' - - print "\nDrawing polydotplot...", - log_txt = "\nDrawing polydotplot..." - - # draw subplots - if verbose: - if lcs_shading and custom_shading: - lcs_text = "\n" + "\t".join(["#Seq1", "Seq2", "LCS for [%s]" %aa_bp_unit, "LCS for [%s]" %aa_bp_unit, "Custom matrix value", "Matrix color index", "LCS color index"]) + "\n" - elif lcs_shading: - lcs_text = "\n" + "\t".join(["#Seq1", "Seq2", "LCS for [%s]" %aa_bp_unit, "LCS for [%s]" %aa_bp_unit, "LCS color index for", "LCS color index rev"]) + "\n" - elif custom_shading: - lcs_text = "\n" + "\t".join(["#Seq1", "Seq2", "Custom matrix value", "Color index for", "Color index rev"]) + "\n" - - if verbose: - seq_text = "" - counter, seq_counter = 0, 0 - for idx in range(len(sequences)): - if verbose: - print "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]), - seq_text += "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]) - rec_two = seq_dict[sequences[idx]] - len_two = len(rec_two.seq) - name_two = rec_two.id - - for jdx in range(idx, len(sequences)): - rec_one = seq_dict[sequences[jdx]] - len_one = len(rec_one.seq) - name_one = rec_one.id - - counter += 1 - seq_counter += 1 - if verbose: - print sequences[jdx], - seq_text += " " + sequences[jdx] - elif not seq_counter % 25: - print seq_counter, - log_txt += str(seq_counter) - - # optional shade background according to length of LCS and/or user matrix - ######################################################################### - - # get interval based on LCS - background_colors = [None, None] - if lcs_shading and (lcs_shading_ref==1 or lcs_shading_ref==2 or max_lcs!=None): # self plot max_lcs_for == None - lcs_len = lcs_dict[(idx, jdx)] - l1 = lcs_len[0] # forward - l2 = lcs_len[1] # reverse complement - - lcs_shading_bool = True - - # calculate shading acc. to chosen option - if lcs_shading_ref == 1: # percentage of shorter sequence - color_idx0 = min(len(colors)-1, l1*lcs_shading_num // min(len_one, len_two)) - color_idx1 = min(len(colors)-1, l2*lcs_shading_num // min(len_one, len_two)) - elif lcs_shading_ref == 2: # by given interval size - color_idx0 = min(len(colors)-1, l1 // lcs_shading_interval_len) - color_idx1 = min(len(colors)-1, l2 // lcs_shading_interval_len) - if color_idx0 >= len(colors): - color_idx0 = len(colors) - if color_idx1 >= len(colors): - color_idx1 = len(colors) - else: # percentage of maximum lcs length - color_idx0 = min(len(colors)-1, l1*lcs_shading_num // max_lcs) - color_idx1 = min(len(colors)-1, l2*lcs_shading_num // max_lcs) - else: - lcs_shading_bool = False - - # get interval based on custom matrix - if custom_shading: - # matrix value - try: - custom_value = custom_similarity_dict[(idx, jdx)] - except: - custom_value = "" - - # bottom left triangle = LCS forward/reverse or best of both - if lcs_shading_bool: - if lcs_shading_ori == 0: # forward - color_idx1 = color_idx0 - elif lcs_shading_ori == 2: # both directions - color_idx1 = max(color_idx0, color_idx1) - - # top right triangle = custom value (not colored if text matrix provided) - if type(custom_value) == int or type(custom_value) == float: - color_idx0 = int((custom_value-custom_min)*lcs_shading_num // (custom_max-custom_min)) - # if string is proviced - else: - color_idx0 = 0 - - # set colors dependent on lcs dependent on orientation - if lcs_shading_bool and not custom_shading: - if idx != jdx: - if lcs_shading_ori == 0: - color_idx1 = color_idx0 - elif lcs_shading_ori == 1: - color_idx0 = color_idx1 - background_colors[0] = colors[color_idx0] - background_colors[1] = colors[color_idx1] - # for selfcomparison, only color reverse complement - elif lcs_shading_ori != 0 and not custom_shading: - background_colors[0] = colors[color_idx1] - # set different colors for shading by LCS + user matrix - elif lcs_shading_bool and custom_shading: - # print colors, background_colors, color_idx0, color_idx1 - background_colors[0] = colors_2[color_idx0] - background_colors[1] = colors[color_idx1] - # set grey color range for user matrix if no LCS shading - elif custom_shading: - background_colors[0] = colors[color_idx0] - background_colors[1] = colors[color_idx0] - - if verbose: - if custom_shading and lcs_shading_bool: - lcs_text += "\t".join([name_one, name_two, str(lcs_len[0]), str(lcs_len[1]), str(custom_value), str(color_idx0), str(color_idx1)]) + "\n" - elif lcs_shading_bool: - lcs_text += "\t".join([name_one, name_two, str(lcs_len[0]), str(lcs_len[1]), str(color_idx0), str(color_idx1)]) + "\n" - elif custom_shading: - lcs_text += "\t".join([name_one, name_two, str(custom_value), str(color_idx0), str(color_idx1)]) + "\n" - - # diagonal (self-dotplots) - if idx == jdx: - # skip positions below diagonal - counter = counter + (counter - 1) // (nrows) # + row_pos - counters = [counter] - # draw both graphs at once (due to symmetry) - else: - col_pos = (counter - 1) % ncols - row_pos = (counter - 1) // (nrows) - counter2 = col_pos * ncols + row_pos + 1 - counters = [counter, counter2] - - if len(counters) == 2: - seq_counter += 1 - if not verbose and not seq_counter % 25: - print seq_counter, - log_txt += str(seq_counter) - - x_lists, y_lists, x_lists_rc, y_lists_rc = data_dict[(idx, jdx)] - - # plot diagram(s) - for kdx in range(len(counters)): - - # shade annotated regions if gff file(s) provided - if idx == jdx and gff_files != None and gff_files != []: - if name_one in feat_dict.keys(): - features = feat_dict[name_one] - for item in features: - feat_type, start, stop = item - feat_color, strength, zoom = gff_color_dict[feat_type.lower()] - start = max(0, start - zoom - 0.5) - stop = min(length_seq+1, stop + zoom + 0.5) - width = stop - start - ax.add_patch(patches.Rectangle((start, start), # (x,y) - width, width, # width, height - edgecolor=None, linewidth=line_width+zoom, - fill=True, facecolor=feat_color, - alpha=strength)) - - # if custom matrix value printed into upper matrix triangle, skip data plotting - # text print in top triangle - if user_matrix_print and custom_shading and kdx==0 and idx!=jdx: - data_plotting = False - # dotplot in bottom triangle - else: - data_plotting = True - - fig_pos = counters[kdx] - # plotting subplot with matplotlib - ax = P.subplot(gs[fig_pos-1]) # rows, columns, plotnumber - - # mirror plot, if plotting below diagonal - if kdx == 0: - l1, l2 = len_one, len_two - n1, n2 = name_one, name_two - x1, y1 = x_lists, y_lists - x2, y2 = x_lists_rc, y_lists_rc - else: - l2, l1 = len_one, len_two - n2, n1 = name_one, name_two - x1, y1 = y_lists, x_lists - x2, y2 = y_lists_rc, x_lists_rc - - if data_plotting: - # collect lines - lines = [] - color_list = [] - for (x_lines, y_lines, col) in [(x2, y2, line_col_rev), (x1, y1, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # plot value provided by customer instead of dotplot - else: - alignment = {'horizontalalignment': 'center', 'verticalalignment': 'center'} - # P.text(0.5, 0.5, custom_value, size='medium', transform=ax.transAxes, **alignment) - P.text(0.5, 0.5, custom_value, size=label_size*1.5, transform=ax.transAxes, **alignment) - # P.text(0.5, 0.5, custom_value, size=label_size*1.5, transform=ax.transAxes, - # horizontalalignment='center', verticalalignment='center', color="black") - - if custom_shading: - # omit diagonal - if idx == jdx: - ax.set_facecolor("white") - # use white background for text fields (top right triangle only [kdx 0]) - elif type(custom_value) != int and type(custom_value) != float and kdx == 0: - ax.set_facecolor("white") - else: - ax.set_facecolor(background_colors[kdx]) - # set background color if lcs shading - elif lcs_shading_bool and background_colors[kdx] != None: - ax.set_facecolor(background_colors[kdx]) - - # set axis limits - P.xlim(0, l1+1) - P.ylim(l2+1, 0) # rotate y axis (point downwards) - - # determine axis positions - if x_label_pos_top: - ax.xaxis.tick_top() - ax.xaxis.set_label_position('top') - x_label_bool = fig_pos <= ncols - x_tick_bool = fig_pos > ncols*(ncols-1) - else: - x_label_bool = fig_pos > ncols*(ncols-1) - x_tick_bool = fig_pos <= ncols - - # x axis labels dependent on plot position/number - if x_label_bool: # x title and labels on top or bottom - P.xlabel(unicode_name(shorten_name(n1, max_len=title_length)), fontsize=label_size, rotation=x_label_rotation, verticalalignment=xvalign, horizontalalignment=xhalign, fontweight='bold', labelpad=8) # axis naming - if not x_label_rotation in ["horizontal", "vertical"]: - P.setp(ax.get_xticklabels(), fontsize=label_size*.9, rotation="vertical") - else: - P.setp(ax.get_xticklabels(), fontsize=label_size*.9, rotation=x_label_rotation) - elif x_tick_bool and x_label_pos_top: # x ticks on bottom row - ax.xaxis.tick_bottom() # ticks without labels on bottom - P.setp(ax.get_xticklabels(), fontsize=label_size, rotation=x_label_rotation, visible=False) - elif x_tick_bool: # x ticks on top row - ax.xaxis.tick_top() # # ticks without labels on top - P.setp(ax.get_xticklabels(), fontsize=label_size, rotation=x_label_rotation, visible=False) # inner diagrams without labelling - else: # no x ticks on internal rows - ax.axes.get_xaxis().set_visible(False) - - # y axis labels dependent on plot position/number - if fig_pos % ncols == 1 or (ncols == 1 and nrows == 1): # y title and labels in 1st column - P.ylabel(unicode_name(shorten_name(n2, max_len=title_length)), fontsize=label_size, rotation=y_label_rotation, verticalalignment=yvalign, horizontalalignment=yhalign, fontweight='bold', labelpad=8) - P.setp(ax.get_yticklabels(), fontsize=label_size*.9) # axis naming - elif fig_pos % ncols == 0: # y ticks in last column - ax.yaxis.tick_right() - P.setp(ax.get_yticklabels(), visible=False) # inner diagrams without labelling - else: - ax.axes.get_yaxis().set_visible(False) - - if not verbose: - print seq_counter, "done" - log_txt += str(seq_counter) + " done" - else: - print "\n%d done" % seq_counter - log_txt += "\n%d done" % seq_counter - logprint(log_txt, start=False, printing=False) - - if verbose: - try: - logprint(lcs_text, start=False, printing=True) - except: - pass - - # finalize layout - margins & spacing between plots - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - # gs.tight_layout(fig, h_pad=.02, w_pad=.02) # less overlapping tick labels, but also disturbingly large spacing - if y_label_rotation == "horizontal": - if x_label_pos_top: - P.subplots_adjust(hspace=spacing, wspace=spacing, left=0.13, top=0.87) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=spacing, wspace=spacing, left=0.13, bottom=0.13) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=spacing, wspace=spacing) # space between rows - def 0.4 - - # save figure and close instance - fig_name = '%s%s_wordsize%i%s.%s' % (prefix, name_graph, wordsize, suffix, filetype) - P.savefig(fig_name) - P.close() - P.cla() - - - # create figure color legend - if lcs_shading: - if lcs_shading_ref == 1: # percentage of shorter sequence - legend_file_name = legend_figure(colors, lcs_shading_num, unit="%", filetype=filetype, prefix=prefix) - elif lcs_shading_ref == 2: # interval sizes - legend_file_name = legend_figure(colors, lcs_shading_num, unit=aa_bp_unit, filetype=filetype, prefix=prefix, bins=color_bins) - else: # relative of maximum lcs - legend_file_name = legend_figure(colors, lcs_shading_num, unit=aa_bp_unit, filetype=filetype, prefix=prefix, max_lcs_len=max_lcs) - - if custom_shading: - custom_prefix = "custom-matrix-" + prefix - legend_file_name_custom = legend_figure(colors_2, lcs_shading_num, unit="%", filetype=filetype, prefix=custom_prefix, max_lcs_len=custom_max, min_lcs_len=custom_min) - - if lcs_shading and custom_shading: - return [fig_name, legend_file_name, legend_file_name_custom] - elif lcs_shading: - return [fig_name, legend_file_name] - elif custom_shading: - return [fig_name, legend_file_name_custom] - else: - return [fig_name] - - -############################### -# Function Call # -############################### - -def main(seq_list, wordsize, modes=[0, 1, 2], prefix=None, plot_size=10, label_size=10, filetype="png", type_nuc=True, convert_wobbles=False, substitution_count=0, rc_option=True, alphabetic_sorting=False, gff=None, multi=True, ncols=1, nrows=1, lcs_shading=True, lcs_shading_num=5, lcs_shading_ref=0, lcs_shading_interval_len=100, lcs_shading_ori=0, gff_color_config_file="", input_user_matrix_file="", user_matrix_print=False, length_scaling=True, title_length=50, spacing=0.04, verbose=False): - - global t1, line_col_rev - - # read gff color config file if provided - if len(input_gff_files) != 0 and input_gff_files != None: - if gff_color_config_file not in ["", None]: - text = "\n%s\n\nReading GFF color configuration file\n%s\n\n=> %s\n" % (50*"=", 28*"-", gff_color_config_file) - logprint(text, start=False, printing=True) - gff_feat_colors = read_gff_color_config(gff_color_config_file) - else: - gff_feat_colors = {} - if gff_color_config_file not in ["", None]: - text = "Please provide GFF annotation files to use configuration file", gff_color_config_file - logprint(text, start=False, printing=True) - - # if color is set to white, reverse complementary matches are skipped - if not rc_option: - line_col_rev = "white" # reverse matches not calculated - elif not type_nuc: - logprint("Reverse complement deactivated for proteins!") - line_col_rev = "white" # reverse matches not calculated - - mode_text = [] - for item in modes: - mode_text.append(str(item)) - text = "%s\n\nRunning plotting modes %s" % (50*"=", ", ".join(mode_text)) - logprint(text, start=False, printing=True) - - - # create dotplots - ########################################## - - # self dotplots - t1 = time.time() - if 0 in modes: - list_of_png_names = selfdotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, multi=multi, ncols=ncols, nrows=nrows, gff_files=gff, gff_color_dict=gff_feat_colors, verbose=verbose) - t1 = time_track(t1) - if list_of_png_names != [] and list_of_png_names != None: - text = "-> Image file(s): %s\n" % ", ".join(list_of_png_names) - else: - text = "No image files were created!\n" - logprint(text, start=False, printing=True) - logprint(50*"=") - - # paired dotplots - if 1 in modes: - if multi: - list_of_png_names = pairdotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, multi=multi, ncols=ncols, nrows=nrows, length_scaling=length_scaling, verbose=verbose) - t1 = time_track(t1) - else: - if not length_scaling: - text = "\nPairwise dotplot with individual output files scaled by sequence length automatically!" - logprint(text, start=False, printing=True) - list_of_png_names = pairdotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, multi=multi, ncols=ncols, nrows=nrows, length_scaling=True, verbose=verbose) - t1 = time_track(t1) - if list_of_png_names != [] and list_of_png_names != None: - text = "-> Image file(s): %s\n" % ", ".join(list_of_png_names) - else: - text = "No image files were created!\n" - logprint(text, start=False, printing=True) - logprint(50*"=") - - # all-against-all dotplot - if 2 in modes: - list_of_png_names = polydotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, lcs_shading=lcs_shading, lcs_shading_num=lcs_shading_num, lcs_shading_ref=lcs_shading_ref, lcs_shading_interval_len=lcs_shading_interval_len, lcs_shading_ori=lcs_shading_ori, input_user_matrix_file=input_user_matrix_file, user_matrix_print=user_matrix_print, spacing=spacing, verbose=verbose) - t1 = time_track(t1) - if list_of_png_names != [] and list_of_png_names != None: - text = "-> Image file(s): %s\n" % ", ".join(list_of_png_names) - else: - text = "No image files were created!\n" - logprint(text, start=False, printing=True) - logprint(50*"=") - - text = "\n" + 50 * "#" + "\n" + 50 * "#" - text += "\n\nThank you for using FlexiDot!\n" - logprint(text, start=False, printing=True) - -# testing mode for debugging -trial_mode = False -# trial_mode = True - -# parameters = check_input(sys.argv) -parameters = check_input(sys.argv, trial_mode=trial_mode) - -# read out parameters -commandline, auto_fas, input_fasta, output_file_prefix, collage_output, m_col, n_row, filetype, type_nuc, input_gff_files, gff_color_config_file, wordsize, plotting_modes, wobble_conversion, substitution_count, rc_option, alphabetic_sorting, lcs_shading, lcs_shading_num, lcs_shading_ref, lcs_shading_interval_len, lcs_shading_ori, input_user_matrix_file, user_matrix_print, plot_size, line_width, line_col_for, line_col_rev, x_label_pos_top, label_size, spacing, length_scaling, title_length, verbose = parameters - -# evtl. overwrite parameters for testing purposes in trial mode -if trial_mode: - # input_user_matrix_file = "AngioSINE-v18-alignment-identities.csv" - input_fasta = ["test-sequences-9-Ns.fas"] - input_fasta = ["Beta_SINEs__select_consensus.fas"] - # input_user_matrix_file = "Beta_SINEs__select_consensus_matrix.txt" - # input_user_matrix_file = "Beta_SINEs__select_consensus_matrix-01.txt" - # input_user_matrix_file = "Beta_SINEs__select_consensus_matrix-comma-str.txt" - # input_user_matrix_file = "Beta_SINEs__select_consensus_matrix-100+.txt" - # user_matrix_print = True - output_file_prefix = "SINEmatrix" - output_file_prefix = "SINEmatrix-NoShading" - plot_size = 10 - plotting_modes = [0,1,2] - plotting_modes = [2] - lcs_shading = False - lcs_shading = True - lcs_shading_ref = 2 - lcs_shading_num = 4 - lcs_shading_ori = 0 - lcs_shading_interval_len = 15 - wordsize = 10 - wordsize = 7 - x_label_pos_top = True - filetype = "pdf" - filetype = "png" - - wobble_conversion = False - wobble_conversion = True - - substitution_count = 0 - - rc_option = True - rc_option = False - label_size = 10 - - verbose = False - verbose = True - -if auto_fas: - path = os.path.dirname(os.path.abspath(__file__)) - files_long = glob.glob(path+"/*.fasta") - files_long.extend(glob.glob(path+"/*.fas")) - files_long.extend(glob.glob(path+"/*.fa")) - files_long.extend(glob.glob(path+"/*.fna")) - input_fasta = [] - for i in files_long: - if not "combined" in i: - filename = i[i.rfind('\\')+1:] - input_fasta.append(filename) - -if trial_mode: - # start logging file - logprint(commandline, start=True, printing=False, prefix=output_file_prefix) - -main(input_fasta, wordsize, modes=plotting_modes, prefix=output_file_prefix, plot_size=plot_size, label_size=label_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=wobble_conversion, substitution_count=substitution_count, rc_option=rc_option, gff=input_gff_files, multi=collage_output, ncols=m_col, nrows=n_row, alphabetic_sorting=alphabetic_sorting, lcs_shading=lcs_shading, lcs_shading_num=lcs_shading_num, lcs_shading_ref=lcs_shading_ref, lcs_shading_interval_len=lcs_shading_interval_len, lcs_shading_ori=lcs_shading_ori, gff_color_config_file=gff_color_config_file, input_user_matrix_file=input_user_matrix_file, user_matrix_print=user_matrix_print, length_scaling=length_scaling, title_length=title_length, spacing=spacing, verbose=verbose) - - diff --git a/code/flexidot_v1.02.py b/code/flexidot_v1.02.py deleted file mode 100644 index 21cb5ae..0000000 --- a/code/flexidot_v1.02.py +++ /dev/null @@ -1,3177 +0,0 @@ -#!/usr/bin/python2.7 -#!/usr/bin/python2.7 -# -*- coding: utf-8 -*- - -""" -FlexiDot: Highly customizable ambiguity-aware dotplots for visual sequence investigation - -Kathrin M. Seibt, Thomas Schmidt and Tony Heitkam -Institute of Botany, TU Dresden, Dresden, 01277, Germany - -(Bioinformatics, 2018, doi 10.1093/bioinformatics/bty395) -""" - - -############################### -# Requirements # -############################### - -# import system modules -import os, glob -import time, datetime -import sys -import shutil, getopt -import unicodedata - -def module_install_command(module_name, upgrade=False): - """ - create installation commands for Python modules and print information - """ - if upgrade: - load_command = "python -m pip install --upgrade %s" % module_name - else: - load_command = "python -m pip install %s" % module_name - - try: - logprint("Installing Python module: %s\n\t%s\n" % (module_name, load_command)) - except: - print "Installing Python module: %s\n\t%s\n" % (module_name, load_command) - - return load_command - -def load_modules(): - """ - load Python modules, if possible - otherwise try to install them - """ - - # make module names global - global cllct, gridspec, patches, rcParams, mplrc, P, Color, SeqIO, np, ccv, mcolors, rgb2hex, regex - - # matplotlib - try: - import matplotlib.collections as cllct - except: - command = module_install_command("matplotlib", upgrade=True) - try: - os.system(command) - print "\n" - import matplotlib.collections as cllct - except: - print "Please install module matplotlib manually" - from matplotlib.colors import colorConverter as ccv - import matplotlib.colors as mcolors - import matplotlib.gridspec as gridspec - import matplotlib.patches as patches - import pylab as P - - # specify matplotlib font settings - from matplotlib import rc as mplrc - mplrc('pdf', fonttype=42, compression=0) - from matplotlib import rcParams - rcParams['font.family'] = 'sans-serif' - rcParams['font.sans-serif'] = ['Helvetica', 'Verdana', 'Tahoma', ] - - # colour for color gradient palette - try: - from colour import Color - except: - command = module_install_command("colour") - try: - os.system(command) - print "\n" - from colour import Color - except: - print "Please install module colour manually" - - # color converter - try: - from colormap import rgb2hex - except: - command = module_install_command("colormap") - # additional module easydev.tools required by colormap - command2 = module_install_command("easydev") - try: - os.system(command) - os.system(command2) - print "\n" - from colormap import rgb2hex - except: - print "Please install module colormap manually" - - # biopython - try: - from Bio import SeqIO - except: - command = module_install_command("biopython") - try: - os.system(command) - print "\n" - from Bio import SeqIO - except: - print "Please install module biopython manually" - - # numpy - try: - import numpy as np - except: - command = module_install_command("numpy") - try: - os.system(command) - print "\n" - import numpy as np - except: - print "Please install module numpy manually" - - # regex for pattern matching - try: - import regex - except: - command = module_install_command("regex") - try: - os.system(command) - print "\n" - import regex - except: - print "Please install module regex manually" - -load_modules() - - -############################### -# Usage & Input # -############################### - -def usage(): - """ - usage and help - """ - - print """\n\n FLEXIDOT - ------------------------------------------------------------------- - - Version: - 1.02 - - Citation: - Kathrin M. Seibt, Thomas Schmidt, Tony Heitkam (2018) - "FlexiDot: Highly customizable ambiguity-aware dotplots for visual sequence investigation" - Bioinformatics, doi: 10.1093/bioinformatics/bty395 - - - General usage: - $ python flexidot.py -a [ARGUMENTS] - $ python flexidot.py -i [ARGUMENTS] - - - ARGUMENTS - ------------------------------------------------------------------- - - - INPUT/OUTPUT OPTIONS... required are [-a] OR [-i] - - -a, --auto_fas Imports all fasta files from current directory (*.fasta, *.fas, *.fa, *.fna) - -i is not needed, if -a is activated - [inactive by default] - - -i, --in_file Input fasta file (fasta file name or comma-separated file list) - > Provide multiple files: Recall -i or provide comma-separated file names - - -o, --output_file_prefix File prefix to be added to the generated filenames [default = NONE] - - -c, --collage_output Multiple dotplots are combined in a collage - Y or 1 = ON [default] - N or 0 = OFF - - -m, --m_col Number of columns per page [default = 4] (only if --collage_output is ON) - - -n, --n_row Number of rows per page [default = 5] (only if --collage_output is ON) - - -f, --filetype Output file format - 0 = PNG [default] - 1 = PDF - 2 = SVG - - -s, --alphabetic_sorting Sort sequences alphabetically according to titles - Y or 1 = ON - N or 0 = OFF [default] - - - CALCULATION PARAMETERS... - - -k, --wordsize Wordsize (kmer length) for dotplot comparison [default = 7] - - -p, --plotting_mode Mode of FlexiDot dotplotting - 0 = self [default] - 1 = paired - 2 = poly (matrix with all-against-all dotplots) - > Run multiple plotting modes: Recall -p or provide comma-separated numbers - - -t, --type_nuc Type of residue is nucleotide - Y or 1 = nucleotide [default] - N or 0 = amino acid - - -w, --wobble_conversion Ambiguity handling for relaxed matching - Y or 1 = ON - N or 0 = OFF [default] - - -S, --substitution_count Number of substitutions (mismatches) allowed per window for relaxed matching - [default = 0] - - -r, --rc_option Find reverse complementary matches (only if type_nuc=y) - Y or 1 = ON [default] - N or 0 = OFF - - - GRAPHIC FORMATTING... - - -A, --line_width Line width [default = 1] - - -B, --line_col_for Line color [default = black] - - -C, --line_col_rev Reverse line color [default = green] - - -D, --x_label_pos Position of the X-label - Y or 1 = top [default] - N or 0 = bottom - - -E, --label_size Font size [default = 10] - - -F, --spacing Spacing between all-against-all dotplots (only if --plotting_mode=2) - [default = 0.04] - - -P, --plot_size Plotsize [default = 10] - - -L, --length_scaling Scale plot size for pairwise comparison (only if --plotting_mode=1) - Y or 1 = Scaling ON (axes scaled according to sequence length) - N or 0 = Scaling OFF (squared plots) [default] - - -T, --title_length Limit title length for self dotplot comparison - Use last characters of the title name (instead of the first): add an "E" (end), e.g. -T 20E - [default = 20, the first 20 characters] - - - GFF SHADING (for -p/--plotting_mode=0 only)... - - -g, --input_gff_files GFF3 file used for markup in self-dotplots - (provide multiple files: Recall -g or provide comma-separated file names) - - -G, --gff_color_config_file Tab-delimited config file for custom gff shading - column 1: feature type - column 2: color - column 3: alpha - column 4: zoom factor (for small regions) - - - LCS SHADING OPTIONS (for -p/--plotting_mode=2 only)... - - -x, --lcs_shading Shade subdotplot based on the length of the longest common substring (LCS) - Y or 1 = ON - N or 0 = OFF [default] - - -X, --lcs_shading_num Number of shading intervals (hues) for LCS (-x) and user matrix shading (-u) - [default = 5] - - -y, --lcs_shading_ref Reference for LCS shading - 0 = maximal LCS length [default] - 1 = maximally possible length (length of shorter sequence in pairwise comparison) - 2 = given interval sizes - DNA [default 100 bp] or proteins [default 10 aa] - see -Y - - -Y, --lcs_shading_interval_len Length of intervals for LCS shading (only if --lcs_shading_ref=2) - [default for nucleotides = 50; default for amino acids = 10] - - -z, --lcs_shading_ori Shade subdotplots according to LCS on - 0 = forward [default], - 1 = reverse, or - 2 = both strands (forward shading above diagonal, reverse shading on diagonal and below; - if using --input_user_matrix_file, best LCS is used below diagonal) - - - CUSTOM USER MATRIX SHADING OPTIONS (for -p/--plotting_mode=2 only)... - - -u, --input_user_matrix_file Shading above diagonal according to values in matrix file specified by the user - (tab-delimited or comma-separated matrix with sequence name in column 1 and numbers in columns 2-n - e.g. identity matrix from multiple sequence alignment - strings are ignored) - - -U, --user_matrix_print Display provided matrix entries in the fields above diagonal of all-against-all dotplot - Y or 1 = ON - N or 0 = OFF [default] - - - OTHERS... - - -h, --help Help screen - - -v, --verbose Verbose - - - - - """ - -def check_input(argv, trial_mode=False): - """ - commandline argument parsing - """ - - global log_txt, aa_bp_unit - - # helpers for argument parsing - ###################################### - - arguments = ["-a", "--auto_fas", "a", "auto_fas", - "-i", "--input_fasta", "i:", "input_fasta=", - "-o", "--output_file_prefix", "o:", "output_file_prefix=", - "-c", "--collage_output", "c:", "collage_output=", - "-m", "--m_col", "m:", "m_col=", - "-n", "--n_row", "n:", "n_row=", - "-f", "--filetype", "f:", "filetype=", - "-t", "--type_nuc", "t:", "type_nuc=", - "-g", "--input_gff_files", "g:", "input_gff_files", - "-G", "--gff_color_config_file", "G:", "gff_color_config_file", - "-k", "--wordsize", "k:", "wordsize=", - "-p", "--plotting_mode", "p:", "plotting_mode=", - "-w", "--wobble_conversion", "w:", "wobble_conversion=", - "-S", "--substitution_count", "S:", "substitution_count=", - "-r", "--rc_option", "r:", "rc_option=", - "-s", "--alphabetic_sorting", "s:", "alphabetic_sorting=", - "-x", "--lcs_shading", "x:", "lcs_shading=", - "-X", "--lcs_shading_num", "X:", "lcs_shading_num=", - "-y", "--lcs_shading_ref", "y:", "lcs_shading_ref=", - "-Y", "--lcs_shading_interval_len", "Y:", "lcs_shading_interval_len=", - "-z", "--lcs_shading_ori", "z:", "lcs_shading_ori=", - "-u", "--input_user_matrix_file", "u:", "input_user_matrix_file=", - "-U", "--user_matrix_print", "U:", "user_matrix_print=", - "-P", "--plot_size", "P:", "plot_size=", - "-A", "--line_width", "A:", "line_width=", - "-B", "--line_col_for", "B:", "line_col_for=", - "-C", "--line_col_rev", "C:", "line_col_rev=", - "-D", "--x_label_pos", "D:", "x_label_pos=", - "-E", "--label_size", "E:", "label_size=", - "-F", "--spacing", "F:", "spacing=", - "-L", "--length_scaling", "L:", "length_scaling=", - "-T", "--title_length", "T:", "title_length=", - "-h", "--help", "h", "help", - "-v", "--verbose", "v", "verbose"] - - arguments_sysargv = tuple(arguments[0::4] + arguments[1::4]) - arguments_opts = "".join(arguments[2::4]) - arguments_args = arguments[3::4] - - - # setting defaults - ###################################### - - auto_fas = False # 0 - input_fasta = [] - output_file_prefix = None - collage_output = True # 1 - m_col = 4 - n_row = 5 - filetype = 0 - type_nuc = True - input_gff_files = [] - gff_color_config_file = "" - - wordsize = 7 - plotting_modes = [0] - wobble_conversion = False # 0 - substitution_count = 0 - rc_option = True # 1 - alphabetic_sorting = False # 0 - - lcs_shading = False # 0 - lcs_shading_num = 4 - lcs_shading_ref = 0 - lcs_shading_interval_len = 50 # interval default changes to "10" for amino acids [type_nuc = n] - lcs_shading_ori = 0 - - input_user_matrix_file = "" - user_matrix_print = False - - plot_size = 10 - line_width = 1 - line_col_for = "black" - line_col_rev = "#009243" - x_label_pos = True # 0 - label_size = 10 - spacing = 0.04 - length_scaling = False # 0 - title_length = 20 #float("Inf") - title_selectpos = "B" # B (begin), E (end) - - aa_bp_unit = "bp" - - verbose = False # 0 - - filetype_dict = {0: "png", 1: "pdf", 2: "svg"} - lcs_shading_ref_dict = {0: "maximal LCS length", 1: "maximally possible length", 2: "given interval sizes"} - plotting_mode_dict = {0: "self", 1: "paired", 2: "all-against-all"} - lcs_shading_ori_dict = {0: "forward", 1: "reverse complement", 2: "both"} - - # return default parameters for testing purposes - if trial_mode: - print "ATTENTION: YOU ARE IN THE TRIAL MODE!!!\n\n" - - commandline = "trial_mode\n" - - parameters = [commandline, auto_fas, input_fasta, output_file_prefix, collage_output, m_col, n_row, filetype_dict[filetype], type_nuc, input_gff_files, gff_color_config_file, wordsize, plotting_modes, wobble_conversion, substitution_count, rc_option, alphabetic_sorting, lcs_shading, lcs_shading_num, lcs_shading_ref, lcs_shading_interval_len, lcs_shading_ori, input_user_matrix_file, user_matrix_print, plot_size, line_width, line_col_for, line_col_rev, x_label_pos, label_size, spacing, length_scaling, title_length, verbose] - return parameters - - - # read arguments - ###################################### - - commandline = "" - for arg in sys.argv: - commandline += arg + " " - - log_txt = "\n...reading input arguments..." - print log_txt - - if len(sys.argv) < 2: - print "\nERROR: More arguments are needed. Exit..." - log_txt += "\nERROR: More arguments are needed. Exit..." - usage() - sys.exit() - - elif sys.argv[1] not in arguments_sysargv: - print "\nINPUT ERROR: Input argument %s unknown. Please check the help screen." % sys.argv[1] - log_txt += "\nINPUT ERROR: Input argument %s unknown. Please check the help screen." % sys.argv[1] - # usage() - sys.exit() - - try: - opts, args = getopt.getopt(sys.argv[1:], arguments_opts, arguments_args) - - except getopt.GetoptError: - print "\nINPUT ERROR (getopt): Input argument %s unknown. Please check the help screen." % sys.argv[1:] - log_txt += "\nINPUT ERROR (getopt): Input argument %s unknown. Please check the help screen." % sys.argv[1:] - # usage() - sys.exit() - - for opt, arg in opts: - - if opt in ("-h", "--help"): - print "...fetch help screen" - log_txt += "\n...fetch help screen" - usage(), sys.exit() - - if opt in ("-v", "--verbose"): - print "...verbose output" - log_txt += "\n...verbose output" - verbose = True - - elif opt in ("-i", "--input_fasta"): - if "," in arg: - arg_list = arg.split(",") - for temp_file in arg_list: - if not os.path.exists(str(temp_file)): - message = "\nERROR: fasta_file '%s' was not found!" % str(temp_file) - sys.exit(message) - else: - input_fasta.append(str(temp_file)) - print "fasta file #%i: %s" % (len(input_fasta), str(temp_file)) - log_txt += "\nfasta file #%i: %s" % (len(input_fasta), str(temp_file)) - else: - if not os.path.exists(str(arg)): - message = "\nERROR: fasta_file '%s' was not found!" % str(arg) - log_txt += message - sys.exit(message) - else: - input_fasta.append(str(arg)) - print "fasta file #%i: %s" % (len(input_fasta), str(arg)) - log_txt += "\nfasta file #%i: %s" % (len(input_fasta), str(arg)) - - - elif opt in ("-a", "--auto_fas"): - auto_fas = True - - - # multiple gff files: reads them into a list - elif opt in ("-g", "--input_gff_files"): - - # append gff file only if existing - if "," in arg: - arg_list = arg.split(",") - for temp_file in arg_list: - if not os.path.exists(str(temp_file)): - message = "\nERROR: gff_file '%s' was not found!" % str(temp_file) - print message - log_txt += message - print " -->Running FlexiDot without this gff file!" - log_txt += "\n -->Running FlexiDot without this gff file!" - else: - print "GFF file #%i: %s" %(len(input_gff_files), str(temp_file)) - log_txt += "\nGFF file #%i: %s" %(len(input_gff_files), str(temp_file)) - input_gff_files.append(str(temp_file)) - else: - if not os.path.exists(str(arg)): - message = "\nERROR: gff_file '%s' was not found!" % str(arg) - print message - log_txt += message - print " -->Running FlexiDot without this gff file!" - log_txt += "\n -->Running FlexiDot without this gff file!" - else: - input_gff_files.append(str(arg)) - print "GFF file #%i: %s" %(len(input_gff_files), str(arg)) - log_txt += "\nGFF file #%i: %s" %(len(input_gff_files), str(arg)) - - - elif opt in ("-G", "--gff_color_config_file"): - if not os.path.exists(str(arg)): - message = "\nERROR: gff_color_config_file '%s' was not found!" % str(arg) - print message + "\n -->Running FlexiDot with default gff coloring specification!" - log_txt += message + "\n -->Running FlexiDot with default gff coloring specification!" - else: - gff_color_config_file = str(arg) - - - elif opt in ("-u", "--input_user_matrix_file"): - if not os.path.exists(str(arg)): - message = "\nERROR: input_user_matrix_file '%s' was not found!" % str(arg) - print message + "\n -->Running FlexiDot without input_user_matrix_file %s!" % arg - log_txt += message + "\n -->Running FlexiDot withdefault matrix shading file!" - else: - input_user_matrix_file = str(arg) - - elif opt in ("-U", "--user_matrix_print"): - user_matrix_print = check_bools(str(arg), default=user_matrix_print) - - elif opt in ("-o", "--output_file_prefix"): - output_file_prefix = arg - - elif opt in ("-c", "--collage_output"): - collage_output = check_bools(str(arg), default=collage_output) - - elif opt in ("-m", "--m_col"): - try: m_col = int(arg) - except: - print "m_col - invalid argument - using default value" - log_txt += "\nm_col - invalid argument - using default value" - - elif opt in ("-n", "--n_row"): - try: n_row = int(arg) - except: - print "n_row - invalid argument - using default value" - log_txt += "\nn_row - invalid argument - using default value" - - elif opt in ("-f", "--filetype"): - if 0 <= int(arg) <= 2: - filetype = int(arg) - else: - print "\nERROR: Please provide valid filetype argument. %s is out of range. It will be set to -f 0 [default]." %(filetype) - log_txt += "\nERROR: Please provide valid filetype argument. %s is out of range. It will be set to -f 0 [default]." %(filetype) - - elif opt in ("-t", "--type_nuc"): - type_nuc = check_bools(str(arg), default=type_nuc) - - if type_nuc == False: - # interval default changed for amino acids - lcs_shading_interval_len = 10 - aa_bp_unit = "aa" - - elif opt in ("-k", "--wordsize"): - try: wordsize = int(arg) - except: - print "wordsize - invalid argument - using default value" - log_txt += "\nwordsize - invalid argument - using default value" - - elif opt in ("-p", "--plotting_mode"): - if "," in arg: - temp_modes = arg.split(",") - for item in temp_modes: - if item in ["0","1","2"]: - plotting_modes.append(int(item)) - elif arg in ["0","1","2"]: - plotting_modes = [int(arg)] - else: - print "Please provide valid plotting_modes argument - e.g. 1 or 0,1,2 - using default [0]" - log_txt += "\nPlease provide valid plotting_modes argument - e.g. 1 or 0,1,2 - using default [0]" - - elif opt in ("-w", "--wobble_conversion"): - wobble_conversion = check_bools(str(arg), default=wobble_conversion) - - elif opt in ("-S", "--substitution_count"): - try: substitution_count = int(arg) - except: - print "substitution_count - invalid argument - using default value" - log_txt += "\nsubstitution_count - invalid argument - using default value" - - elif opt in ("-r", "--rc_option"): - rc_option = check_bools(str(arg), default=rc_option) - - elif opt in ("-s", "--alphabetic_sorting"): - alphabetic_sorting = check_bools(str(arg), default=alphabetic_sorting) - - elif opt in ("-x", "--lcs_shading"): - lcs_shading = check_bools(str(arg), default=lcs_shading) - - elif opt in ("-X", "--lcs_shading_num"): - try: lcs_shading_num = int(arg) - 1 - except: - print "lcs_shading_num - invalid argument - using default value" - log_txt += "\nlcs_shading_num - invalid argument - using default value" - - elif opt in ("-y", "--lcs_shading_ref"): - try: - if 0 <= int(arg) <= 2: - lcs_shading_ref = int(arg) - else: - print "\nERROR: lcs_shading_ref %s out of range. It will be set to -y 0 [default]." %(lcs_shading_ref) - log_txt += "\nERROR: lcs_shading_ref %s out of range. It will be set to -y 0 [default]." %(lcs_shading_ref) - except: - print "lcs_shading_ref - invalid argument - using default value" - log_txt += "\nlcs_shading_ref - invalid argument - using default value" - - elif opt in ("-Y", "--lcs_shading_interval_len"): - try: lcs_shading_interval_len = int(arg) - except: - print "lcs_shading_interval_len - invalid argument - using default value" - log_txt += "\nlcs_shading_interval_len - invalid argument - using default value" - - elif opt in ("-z", "--lcs_shading_ori"): - if 0 <= int(arg) <= 2: - lcs_shading_ori = int(arg) - else: - print "\nERROR: Please provide valid lcs_shading_ori argument. %s is out of range. It will be set to -z 0 [default]." %(lcs_shading_ori) - log_txt += "\nERROR: Please provide valid lcs_shading_ori argument. %s is out of range. It will be set to -z 0 [default]." %(lcs_shading_ori) - - elif opt in ("-P", "--plot_size"): - try: plot_size = float(arg) - except: - print "plot_size - invalid argument - using default value" - log_txt += "\nplot_size - invalid argument - using default value" - - - elif opt in ("-A", "--line_width"): - try: line_width = float(arg) - except: - print "line_width - invalid argument - using default value" - log_txt += "\nline_width - invalid argument - using default value" - - elif opt in ("-B", "--line_col_for"): - if mcolors.is_color_like(arg): - line_col_for = arg - else: - print "line_col_for - invalid argument - using default value" - log_txt += "\nline_col_for - invalid argument - using default value" - - elif opt in ("-C", "--line_col_rev"): - if mcolors.is_color_like(arg): - line_col_rev = arg - else: - print "line_col_rev - invalid argument - using default value" - log_txt += "\nline_col_rev - invalid argument - using default value" - - elif opt in ("-D", "--x_label_pos"): - x_label_pos = check_bools(str(arg), default=x_label_pos) - - elif opt in ("-E", "--label_size"): - try: label_size = float(arg) - except: - print "label_size - invalid argument - using default value" - log_txt += "\nlabel_size - invalid argument - using default value" - - elif opt in ("-F", "--spacing"): - try: spacing = float(arg) - except: - print "spacing - invalid argument - using default value" - log_txt += "\nspacing - invalid argument - using default value" - - elif opt in ("-L", "--length_scaling"): - length_scaling = check_bools(str(arg), default=length_scaling) - - elif opt in ("-T", "--title_length"): - try: title_length = int(arg) - except: - try: - title_length = int(str(arg)[:-1]) - title_selectpos = arg[-1].upper() # B (beginning), E (end) - except: - print "title_length - invalid argument - using default value" - log_txt += "\ntitle_length - invalid argument - using default value" - - print "test", title_length, title_selectpos - - # start logging file - logprint(commandline, start=True, printing=False, prefix=output_file_prefix) - logprint(log_txt, start=False, printing=False) - - - # print chosen arguments - ###################################### - - text = "\n%s\n" % (70 * "-") - text += "\n" + "INPUT/OUTPUT OPTIONS...\n" - text += "\n" + "Input fasta file: " + ", ".join(input_fasta) - text += "\n" + "Automatic fasta collection from current directory: " + str(auto_fas) - text += "\n" + "Collage output: " + str(collage_output) - text += "\n" + "Number of columns per page: " + str(m_col) - text += "\n" + "Number of rows per page: " + str(n_row) - text += "\n" + "File format: " + filetype_dict[filetype] - text += "\n" + "Residue type is nucleotide: " + str(type_nuc) - - text += "\n" + "\n\nCALCULATION PARAMETERS...\n" - text += "\n" + "Wordsize: " + str(wordsize) - text += "\n" + "Plotting mode: " + str(plotting_modes).replace("[", "").replace("]", "") + "\n" + 51 * " " - for item in plotting_modes: - text += plotting_mode_dict[item] + " " - text += "\n" + "Ambiguity handling: " + str(wobble_conversion) - text += "\n" + "Reverse complement scanning: " + str(rc_option) - text += "\n" + "Alphabetic sorting: " + str(alphabetic_sorting) - - if 0 in plotting_modes and input_gff_files != []: - text += "\n" + "Input gff files: " + ", ".join(input_gff_files) - if gff_color_config_file != "": - text += "\n" + "GFF color config file: " + gff_color_config_file - text += "\n" + "Prefix for output files: " + str(output_file_prefix) - - if 2 in plotting_modes: - text += "\n" + "\n\nLCS SHADING OPTIONS (plotting_mode 'all-against-all' only)...\n" - text += "\n" + "LCS shading: " + str(lcs_shading) - text += "\n" + "LCS shading interval number: " + str(lcs_shading_num + 1) - text += "\n" + "LCS shading reference: " + lcs_shading_ref_dict[lcs_shading_ref] - if lcs_shading_ref == 2: - text += "\n" + "LCS shading interval size [%s]: " % (aa_bp_unit) + str(lcs_shading_interval_len) - text += "\n" + "LCS shading orientation: " + lcs_shading_ori_dict[lcs_shading_ori] - if input_user_matrix_file != "": - text += "\n" + "Custom user shading matrix file: " + input_user_matrix_file - text += "\n" + "Print user matrix values (instead of dotplot): " + str(user_matrix_print) - - text += "\n" + "\n\nGRAPHIC FORMATTING...\n" - text += "\n" + "Plot size: " + str(plot_size) - text += "\n" + "Line width: " + str(line_width) - text += "\n" + "Line color: " + line_col_for - text += "\n" + "Reverse line color: " + line_col_rev - text += "\n" + "X label position: " + str(x_label_pos) - text += "\n" + "Label size: " + str(label_size) - text += "\n" + "Spacing: " + str(spacing) - text += "\n" + "Title length (limit number of characters): " + str(title_length) - if title_selectpos == "E": - text += "the last %i characters are printed." %int(title_length) - else: - text += "the first %i characters are printed." %int(title_length) - - text += "\n" + "Length scaling: " + str(length_scaling) - text += "\n%s\n" % (70 * "-") - logprint(text) - - - # collect settings - parameters = [commandline, auto_fas, input_fasta, output_file_prefix, collage_output, m_col, n_row, filetype_dict[filetype], type_nuc, input_gff_files, gff_color_config_file, wordsize, plotting_modes, wobble_conversion, substitution_count, rc_option, alphabetic_sorting, lcs_shading, lcs_shading_num, lcs_shading_ref, lcs_shading_interval_len, lcs_shading_ori, input_user_matrix_file, user_matrix_print, plot_size, line_width, line_col_for, line_col_rev, x_label_pos, label_size, spacing, length_scaling, title_length, title_selectpos, verbose] - - return parameters - - -############################### -# Helper Functions # -############################### - -def alphabets(type_nuc=True): - """ - provide ambiguity code for sequences - """ - - nucleotide_alphabet = ["A", "C", "G", "T"] - - nucleotide_alphabet_full = ["A", "C", "G", "T", "N", "B", "D", "H", - "V", "Y", "R", "W", "S", "K", "M"] - - nucleotide_ambiguity_code = {"N": ["A", "C", "G", "T"], # any - "B": ["C", "G", "T"], # not A - "D": ["A", "G", "T"], # not C - "H": ["A", "C", "T"], # not G - "V": ["A", "C", "G"], # not T - "Y": ["C", "T"], # pyrimidine - "R": ["A", "G"], # purine - "W": ["A", "T"], # weak - "S": ["C", "G"], # strong - "K": ["G", "T"], # keto - "M": ["A", "C"]} # amino - - nucleotide_match_dict = {"N": "[ACGTNBDHVYRWSKM]", # any - "B": "[CGTNBDHVYRWSKM]", # not A - "D": "[AGTNBDHVYRWSKM]", # not C - "H": "[ACTNBDHVYRWSKM]", # not G - "V": "[ACGNBDHVYRWSKM]", # not T - "K": "[GTNBDHVYRWSK]", # keto - not A,C,M - "M": "[ACNBDHVYRWSM]", # amino - not G,T,K - "W": "[ATNBDHVYRWKM]", # weak - not C,G,S - "S": "[CGNBDHVYRSKM]", # strong - not A,G,W - "Y": "[CTNBDHVYWSKM]", # pyrimidine - not A,G,R - "R": "[AGNBDHVRWSKM]", # purine - not C,T,Y - "A": "[ANDHVRWM]", - "C": "[CNBHVYSM]", - "G": "[GNBDVRSK]", - "T": "[TNBDHYWK]"} - - # nucleotide_match_dict = {"N": ".", # any - # "B": "[^A]", # not A - # "D": "[^C]", # not C - # "H": "[^G]", # not G - # "V": "[^T]", # not T - # "K": "[^ACM]", # keto - not A,C,M - # "M": "[^GTK]", # amino - not G,T,K - # "W": "[^CGS]", # weak - not C,G,S - # "S": "[^AGW]", # strong - not A,G,W - # "Y": "[^AGR]", # pyrimidine - not A,G,R - # "R": "[^CTY]", # purine - not C,T,Y - # "A": "[ANDHVRWM]", - # "C": "[CNBHVYSM]", - # "G": "[GNBDVRSK]", - # "T": "[TNBDHYWK]"} - - aminoacid_alphabet = ["A", "R", "N", "D", "C", "E", "Q", "G", - "H", "I", "L", "K", "M", "F", "P", "S", - "T", "W", "Y", "V", "U", "O", "*"] - - aminoacid_alphabet_full = ["A", "R", "N", "D", "C", "E", "Q", "G", - "H", "I", "L", "K", "M", "F", "P", "S", - "T", "W", "Y", "V", "U", "O", "*", "J", - "Z", "B", "X"] - - aminoacid_ambiguity_code = {"J": ["I", "L"], - "Z": ["Q", "E"], - "B": ["N", "D"], - "X": ["A", "R", "N", "D", "C", "E", "Q", "G", - "H", "I", "L", "K", "M", "F", "P", "S", - "T", "W", "Y", "V", "U", "O", "*"]} # any - - aminoacid_match_dict = {"J": "[ILJ]", - "Z": "[QEZ]", - "B": "[NDB]", - # "X": ".", - "X": "[ARNDCEQGHILKMFPSTWYVUO*XBZJ]", - "A": "[AX]", - "R": "[RX]", - "N": "[NXB]", - "D": "[DXB]", - "C": "[CX]", - "E": "[EXZ]", - "Q": "[QXZ]", - "G": "[GX]", - "H": "[HX]", - "I": "[IXJ]", - "L": "[LXJ]", - "K": "[KX]", - "M": "[MX]", - "F": "[FX]", - "P": "[PX]", - "S": "[SX]", - "T": "[TX]", - "W": "[WX]", - "Y": "[YX]", - "V": "[VX]", - "U": "[UX]", - "O": "[OX]", - "*": "[*X]"} - - aa_only = set(['E', 'F', 'I', 'J', 'L', 'O', 'Q', 'P', 'U', 'X', 'Z', '*']) - # return nucleotide_alphabet, nucleotide_alphabet_full, nucleotide_ambiguity_code, aminoacid_alphabet, aminoacid_alphabet_full, aminoacid_ambiguity_code, aa_only - - if type_nuc: - return nucleotide_alphabet, nucleotide_alphabet_full, nucleotide_ambiguity_code, nucleotide_match_dict - else: - return aminoacid_alphabet, aminoacid_alphabet_full, aminoacid_ambiguity_code, aminoacid_match_dict - -def logprint(text, start=False, printing=True, prefix=""): - """ - log output to log_file and optionally print - """ - - # define log file name and open file - global log_file_name - if start and trial_mode: - log_file_name = "log_file.txt" - if prefix != "" and prefix != None: - if not prefix.endswith("-"): - prefix = prefix + "-" - log_file_name = prefix + log_file_name - log_file = open(log_file_name, 'w') - log_file.write("Date: %s\n\n" % str(datetime.datetime.now())) - elif start: - date = datetime.date.today() - time = str(datetime.datetime.now()).split(" ")[1].split(".")[0].replace(":", "-") - log_file_name = "%s_%s_log_file.txt" % (date, time) - if prefix != "" and prefix != None: - if not prefix.endswith("-"): - prefix = prefix + "-" - log_file_name = prefix + log_file_name - log_file = open(log_file_name, 'w') - log_file.write("Date: %s\n\n" % str(datetime.datetime.now())) - else: - log_file = open(log_file_name, 'a') - - # write log (and print) - log_file.write(text + "\n") - if printing: - print text - log_file.close() - -def time_track(starting_time, show=True): - """ - calculate time passed since last time measurement - """ - now = time.time() - delta = now - starting_time - if show: - text = "\n\t %s seconds\n" % str(delta) - logprint(text, start=False, printing=True) - return now - -def calc_fig_ratio(ncols, nrows, plot_size, verbose=False): - """ - calculate size ratio for given number of columns (ncols) and rows (nrows) - with plot_size as maximum width and length - """ - ratio = ncols*1./nrows - if verbose: - text = " ".join([ncols, nrows, ratio]) - logprint(text, start=False, printing=True) - if ncols >= nrows: - figsize_x = plot_size - figsize_y = plot_size / ratio - else: - figsize_x = plot_size * ratio - figsize_y = plot_size - return figsize_x, figsize_y - -def shorten_name(seq_name, max_len=20, title_selectpos="B"): #, delim="_"): - """ - shorten sequence names (for diagram titles) - """ - - if len(seq_name) <= max_len: - return seq_name - - # take last characters - if title_selectpos == "E": - name = seq_name[len(seq_name)-max_len:] - - # takefirst characters - else: - name = seq_name[:max_len] - - - """# keep first and last part if multiple parts separated by delimiter (e.g. species_prefix + sequence_id) - if delim in seq_name: - if seq_name.count(delim) >= 2: - name = "%s..." % delim.join(seq_name.split(delim)[:1]) + seq_name.split(delim)[-1] # .replace("_000", "-") - else: - name = seq_name[:((max_len-2)//2)] + "..." + seq_name[((max_len-2)//2):] - - if len(name) > max_len: - name = name[:((max_len-2)//2)] + "..." + name[((max_len-2)//2):] - else: - name = seq_name[:((max_len-2)//2)] + "..." + seq_name[((max_len-2)//2):] - """ - - return name - -def unicode_name(name): - """ - replace non-ascii characters in string (e.g. for use in matplotlib) - """ - unicode_string = eval('u"%s"' % name) - return unicodedata.normalize('NFKD', unicode_string).encode('ascii','ignore') - -def check_bools(arg, update_log_txt = True, default=None): - """ - converts commandline arguments into boolean - """ - - - # convert valid arguments - if str(arg).lower() == "y" or str(arg) == "1": - return True - elif str(arg).lower() == "n" or str(arg) == "0": - return False - - # use default in case of invalid argument - else: - if update_log_txt: - global log_txt - log_txt += "using default for " + str(arg) - else: - try: - logprint("using default for " + str(arg)) - except: - print "using default for " + str(arg) - return default - -def create_color_list(number, color_map=None, logging=False, max_grey="#595959"): - """ - create color list with given number of entries - grey by default, matplotlib color_map can be provided - """ - - try: - # create pylab colormap - cmap = eval("P.cm." + color_map) - # get descrete color list from pylab - cmaplist = [cmap(i) for i in range(cmap.N)] # extract colors from map - # determine positions for number of colors required - steps = (len(cmaplist)-1)/(number) - numbers = range(0, len(cmaplist), steps) - - # extract color and convert to hex code - colors = [] - for idx in numbers[:-1]: - rgb_color = cmaplist[idx] - col = rgb2hex(rgb_color[0]*255, rgb_color[1]*255, rgb_color[2]*255) - colors.append(col) - - # grey - except: - if not color_map == None: - logprint("Invalid color_map (%s) provided! - Examples: jet, Blues, OrRd, bwr,..." % color_map) - logprint("See https://matplotlib.org/users/colormaps.html\n") - old_max_grey = "#373737" - old_max_grey = "#444444" - colors = list(Color("#FFFFFF").range_to(Color(max_grey), number)) # grey - for idx in range(len(colors)): - colors[idx] = str(colors[idx]).replace("Color ", "") - if "#" in colors[idx] and len(colors[idx]) != 7: - # print colors[idx] - colors[idx] = colors[idx] + colors[idx][-(7-len(colors[idx])):] - - text = "%d Colors: %s" % (len(colors), ", ".join(colors)) - if logging: logprint(text, start=False, printing=True) - - if len(colors) < number: - logprint("\nError in color range definition! %d colors missing\n" % (number - len(colors))) - - return colors - - -############################### -# File Handling # -############################### - -def read_seq(input_fasta, verbose=False): - """ - read fasta sequences from (all) file(s) - """ - - # check if file provided - if input_fasta == [] or input_fasta == "": - text = "Attention: No valid file names provided: >%s<" % input_fasta - logprint(text, start=False, printing=True) - return {}, [] - - # combine sequence files, if required - if type(input_fasta) == list: - # concatenate fasta files - if len(input_fasta) > 1: - if verbose: - print "concatenating fastas...", - text = "concatenating fastas..." - input_fasta_combi = concatenate_files(input_fasta) - if verbose: - print "done" - text += "done" - logprint(text, start=False, printing=False) - else: - input_fasta_combi = input_fasta[0] - else: - input_fasta_combi = input_fasta - - # read sequences - if verbose: - print "reading fasta...", - text = "reading fasta...", - try: - seq_dict = SeqIO.index(input_fasta_combi, "fasta") - except ValueError: - logprint("Error reading fasta sequences - please check input files, e.g. for duplicate names!") - return {}, [] - except: - logprint("Error reading fasta sequences - please check input files!") - return {}, [] - - if verbose: - print "done" - text += "done" - logprint(text, start=False, printing=False) - - for seq in seq_dict: - if "-" in seq_dict[seq].seq: - # ungapped = seq_dict[seq].seq.ungap("-") # cannot be assigned back to sequence record - text = "\nSequences degapped prior Analysis!!!" - logprint(text, start=False, printing=True) - return read_seq(degap_fasta(input_fasta), verbose=verbose) - - # get ordered sequence names - sequences = [] - for item in SeqIO.parse(input_fasta_combi, "fasta"): - sequences.append(item.id) - return seq_dict, sequences - -def read_gff_color_config(gff_color_config_file=""): - """ - define coloring options for gff-based color shading of self-dotplots - """ - - # default aestetics for annotation shading (e.g. if no user config file is provided) - # dictionary with feature_type as key and tuple(color, transparency, zoom) as value - gff_feat_colors = {"orf": ("#b41a31", 0.2, 0), - "orf_rev": ("#ff773b", 0.3, 0), - "gene": ("#b41a31", 0.2, 0), - "cds": ("darkorange", 0.2, 0), - "exon": ("orange", 0.2, 0), - "intron": ("lightgrey", 0.2, 0), - "utr": ("lightblue", 0.2, 0), - "repeat_region": ("green", 0.3, 0), - "repeat": ("green", 0.3, 0), - "tandem_repeat": ("red", 0.3, 0), - "transposable_element": ("blue", 0.3, 0), - "ltr_retrotransposon": ("#cccccc", 0.5, 0), - "ltr-retro": ("#cccccc", 0.5, 0), - "long_terminal_repeat": ("#2dd0f0", 0.75, 2), - "ltr": ("#2dd0f0", 0.75, 2), - "pbs": ("purple", 0.75, 2), - "ppt": ("#17805a", 0.5, 2), - "target_site_duplication": ("red", 0.75, 2), - "misc_feature": ("grey", 0.3, 0), - "misc_feat": ("grey", 0.3, 0), - "misc": ("grey", 0.3, 0), - "others": ("grey", 0.5, 0)} - if gff_color_config_file in ["", None] or not os.path.exists(str(gff_color_config_file)): - return gff_feat_colors - - text = "Updating GFF color configuration with custom specifications\n" - logprint(text, start=False, printing=True) - - # read custom gff_color_config_file - in_file = open(gff_color_config_file, 'rb') - overwritten = set([]) - for line in in_file: - if not line.startswith("#") and len(line.strip().split("\t")) >= 4: - data = line.strip().split("\t") - feat = data[0].lower() - color = data[1].lower() - - # check, if settings are valid - if not mcolors.is_color_like(color): - color = "grey" - text = "Invalid color specified for %s: %s - default grey" % (data[0], data[1]) - logprint(text) - try: - alpha = float(data[2]) - except: - alpha = 0.75 - text = "Invalid alpha specified for %s: %s - default 0.75" % (data[0], data[2]) - logprint(text) - try: - zoom = float(data[3]) - except: - zoom = 0 - text = "Invalid zoom specified for %s: %s - default 0" % (data[0], data[3]) - logprint(text) - - # track changes of predefined settings - if feat in gff_feat_colors.keys(): - overwritten.add(data[0].lower()) - - gff_feat_colors[feat] = (color, alpha, zoom) - in_file.close() - - # default coloring for unknown annotations - if not "others" in gff_feat_colors.keys(): - gff_feat_colors["others"] = ("grey", 0.5, 0) - - if verbose: - # print configuration - text = "\n\nGFF color specification:\n%s\n" % (60 * ".") - for item in sorted(gff_feat_colors.keys()): - text += "%-30s\t%-10s\t%-5s\t%s\n" % (item, str(gff_feat_colors[item][0]), str(gff_feat_colors[item][1]), str(gff_feat_colors[item][2])) - logprint (text, printing=True) - - # print overwritting feature type specifications - if len(overwritten) != 0: - text = "%d feature type specifications overwritten:" % len(overwritten) - text += "\n\t"+ ", ".join(overwritten) + "\n" - logprint(text, start=False, printing=True) - - text = "GFF color specification updated acc. to %s\n\t%s\n\n" % (gff_color_config_file, ", ".join(gff_feat_colors)) - logprint(text, start=False, printing=True) - - return gff_feat_colors - -def read_gffs(input_gff_files, color_dict={"others": ("grey", 1, 0)}, type_nuc=True, prefix="", filetype='png', verbose=False): - """ - create feature dictionary from input_gff - sequence name as key and (feature type, start, stop) as value - """ - if type(input_gff_files) != list: - input_gff_files = [input_gff_files] - - # create dictionary with seq_name as key and (type, start and stop) as value - unknown_feats = set([]) - used_feats = set([]) - feat_dict = {} - for input_gff in input_gff_files: - text = "...reading " + input_gff - logprint(text, start=False, printing=True) - - in_file = open(input_gff, 'rb') - for line in in_file: - if not line.startswith("#") and line.strip() != "": - data = line.strip().split("\t") - feat_type = data[2].lower() - if data[6] == "-": - feat_type += "_rev" - if not feat_type.lower() in color_dict.keys(): - if feat_type.lower().replace("_rev", "") in color_dict.keys(): - feat_type = feat_type.replace("_rev", "") - else: - unknown_feats.add(feat_type) - feat_type = "others" - used_feats.add(feat_type) - if not data[0] in feat_dict.keys(): - feat_dict[data[0]] = [(feat_type, int(data[3]), int(data[4]))] # feature type, start, stop - else: - feat_dict[data[0]].append((feat_type, int(data[3]), int(data[4]))) # feature type, start, stop - if verbose: - text = "\nAnnotations for: %s\n" % ", ".join(feat_dict.keys()[:10]) - if len(feat_dict.keys()) > 10: - text = text[:-1] + ", ...\n" - logprint(text, start=False, printing=True) - in_file.close() - - # print feature types without specific shading settings - if len(unknown_feats) != 0: - text = "Missing shading specification for %d feature type(s):\n\t%s\n" % (len(unknown_feats), ", ".join(sorted(unknown_feats))) - logprint(text, start=False, printing=True) - - # create color legend - colors, alphas = [], [] - for item in sorted(used_feats): - colors.append(color_dict[item][0]) - alphas.append(color_dict[item][1]) - legend_figure(colors=colors, lcs_shading_num=len(used_feats), type_nuc=type_nuc, bins=sorted(used_feats), alphas=alphas, gff_legend=True, prefix=prefix, filetype=filetype) - - # print settings - text = "GFF Feature Types: %s\nGFF Colors: %s" % (", ".join(sorted(used_feats)), ", ".join(sorted(colors))) - logprint(text, start=False, printing=True) - - return feat_dict - -def read_matrix(matrix_file_name, delim="\t", symmetric=True, recursion=False, verbose=False): - input_file = open(matrix_file_name, 'rb') - - # read sequence names from first column - names = [] - for line in input_file: - if not line.startswith("#") and not line.startswith(delim) and delim in line: - names.append(line.strip().split(delim)[0]) - logprint("Delimiter '%s': %d names - %s\n" % (delim, len(names), ", ".join(names))) - - # check if names were found - otherwise try another delimiter - if names == [] and not recursion: - if delim == "\t": - new_delim = "," - else: - new_delim = "\t" - logprint("\nMatrix file not containing data delimited by '%s' - trying to read matrix with delimiter '%s'" % (delim.replace("\t", "\\t"), new_delim)) - info_dict = read_matrix(matrix_file_name, delim=new_delim, symmetric=symmetric, recursion=True, verbose=verbose) - return info_dict - elif names == []: - logprint("Empty matrix file with alternative delimiter!") - return info_dict - input_file.close() - - input_file = open(matrix_file_name, 'rb') - # read matrix entries as values in dictionary with tuple(names) as key - info_dict = {} - contradictory_entries = [] - for line in input_file: - if not line.startswith("#") and not line.startswith(delim) and delim in line: - data = line.strip().split(delim) - for idx in range(len(data[1:])): - # print tuple(sorted([data[0], names[idx]])), data[idx+1] - if symmetric: - key = tuple(sorted([names[idx], data[0]])) - else: - key = tuple(names[idx], data[0]) - if key in info_dict.keys(): - if symmetric and info_dict[key] != data[idx+1] and data[idx+1] not in ["", "-"] and info_dict[key] not in ["", "-"]: - contradictory_entries.append(key) - info_dict[key] = data[idx+1] - input_file.close() - - if len(contradictory_entries) != 0: - try: - logprint("\nContradictory entries in matrix file %s:\n\t%s" % (matrix_file_name, ", ".join(contradictory_entries))) - except: - log_txt = "\nContradictory entries in matrix file %s:\n\t" % (matrix_file_name) - for item in contradictory_entries: - log_txt += str(item).replace("'", "") + ", " - log_txt = log_txt[:-2] - logprint(log_txt) - logprint("Using value from bottom left triangle!") - if verbose: - logprint("\nMatrix information for Sequences named: " % ", ".join(names)) - - return info_dict - -def concatenate_files(file_list, combi_filename="temp_combined.fasta", verbose=False): - """ - concatenate content of all files in file_list into a combined file named combi_filename - """ - out_file = open(combi_filename, 'w') - text = "" - for item in file_list: - if verbose: - text += item + " " - print item, - # read in_file linewise and write to out_file - in_file = open(item, 'rb') - for line in in_file: - out_file.write(line.strip()+"\n") - in_file.close() - out_file.close() - if verbose: - logprint(text, start=False, printing=False) - return combi_filename - -def degap_fasta(input_fasta): - """ - remove gaps from fasta - new degapped sequence file created - """ - - # degap all sequence files - output_fastas = [] - if type(input_fasta) != list: - input_fasta = list(input_fasta) - for input_fas in input_fasta: - output_fas = input_fas[:input_fas.rfind(".")] + "_degapped.fas" - in_file = open(input_fas, 'rb') - out_file = open(output_fas, 'w') - for line in in_file: - if line.startswith(">"): - out_file.write(line.strip()+"\n") - else: - out_file.write(line.strip().replace("-", "")+"\n") - out_file.close() - in_file.close() - output_fastas.append(output_fas) - return output_fastas - -def legend_figure(colors, lcs_shading_num, type_nuc=True, unit="%", filetype="png", max_lcs_len=None, min_lcs_len=0, bins=[], alphas=[], gff_legend=False, prefix="", verbose=False): - """ - create figure color legend - """ - max_legend_length_row = 8 - max_legend_length_col = 4 - - # define output file - if filetype not in ["png", "pdf", "svg"]: - text = "Provide valid file type - png, pdf, or svg" - logprint(text, start=False, printing=True) - filetype="png" - - # check if length of information fit - if not gff_legend and ((bins != [] and len(colors) != lcs_shading_num+1) or (bins != [] and len(colors) != len(bins)+1)): - if bins != [] and len(colors) != lcs_shading_num+1: - text = "**Attention**\nlcs_shading_num (%d) does not match number of colors (%d)!\n"% (lcs_shading_num, len(bins)) - elif bins != [] and len(colors) != len(bins)+1: - text = "**Attention**\nnumber of LCS length bins (%d) does not match number of colors (%d)!\n" % (len(colors), len(bins)) - logprint(text, start=False, printing=True) - elif gff_legend and len(bins) != len(colors): - text = "**Attention**\nnumber of GFF Feature Types (%d) does not match number of colors (%d)!\n" % (len(colors), len(bins)) - logprint(text, start=False, printing=True) - - # set alpha values to opaque if none are provided - if alphas == []: - for item in colors: - alphas.append(1) - - # legend data points - data_points = range(len(colors)) - if not gff_legend: - - # specify intervals, if max_lcs_len provided - if max_lcs_len != None: - multi_factor = 100 # one digit - if max_lcs_len <= 1: - multi_factor = 1000 # two digits - # len_interval_size = (max_lcs_len-min_lcs_len) * multi_factor *1. // lcs_shading_num * (1./ multi_factor) - len_interval_size = (max_lcs_len-min_lcs_len) * 1. / lcs_shading_num - len_pos = [float("%.2f" % (min_lcs_len))] - # calculate interval positions - for idx in range(lcs_shading_num): - len_pos.append(float("%.2f" % (len_pos[-1] + len_interval_size))) - - if prefix.startswith("custom-matrix") and (0 <= max_lcs_len <= 100 and 0 <= min_lcs_len <= 100): - unit = "%" - elif prefix.startswith("custom-matrix"): - unit = "" - - text = "\n%d Legend intervals from %.2f to %.2f: \n\t%s - number: %d, step: %.2f, unit: %s\n" % (lcs_shading_num+1, min_lcs_len, max_lcs_len, str(len_pos), len(len_pos), len_interval_size, unit) - logprint(text, start=False, printing=True) - pos = len_pos - interval_size = len_interval_size - else: - # generate legend labels acc. to standard interval notation - interval_size = 100 // lcs_shading_num - pos = range(interval_size, 101+interval_size, interval_size) - - if bins != []: # labels provided - legend_labels = bins[:] - legend_labels.append("max") - legend_labels_lengths = [] - for item in bins: - legend_labels_lengths.append("[%d %s, %d %s)" % (item - min(bins), unit, item, unit)) - if len(bins) == len(colors) - 1: - legend_labels_lengths.append("[%d %s, %s]" % (max(bins), unit, u"\u221E")) # infinite - - else: - legend_labels = [] - legend_labels_lengths = [] - for idx in range(len(pos)): - num = pos[idx] - legend_labels.append("[%d%%, %d%%)" % (num - interval_size, num)) - if max_lcs_len != None: - num = len_pos[idx] - # as int or float - if num == int(num) and int(len_interval_size) == len_interval_size: - legend_labels_lengths.append("[%d %s, %d %s)" % (num, unit, num + len_interval_size, unit)) - else: - legend_labels_lengths.append("[%.2f %s, %.2f %s)" % (num, unit, num + len_interval_size, unit)) - legend_labels[-1] = "100" + unit - if max_lcs_len != None: - if num == int(num) and int(len_interval_size) == len_interval_size: - legend_labels_lengths[-1] = "%d %s" % (max_lcs_len, unit) - else: - legend_labels_lengths[-1] = "%.2f %s" % (max_lcs_len, unit) - - # set labels and choose file name - if gff_legend: - label_text = bins[:] - edge_col = None - legend_file_name = "Selfdotplot_GFF_Shading_Legend_n%d." % lcs_shading_num + filetype - elif max_lcs_len != None: - label_text = legend_labels_lengths[:] - edge_col = "black" - legend_file_name = "Polydotplot_LCS_Shading_Legend_max%d%s_n%d." % (max_lcs_len, unit, lcs_shading_num) + filetype - elif bins != []: - label_text = legend_labels_lengths[:] - edge_col = "black" - legend_file_name = "Polydotplot_LCS_Shading_Legend_%d%s_n%d." % (bins[0], unit, lcs_shading_num) + filetype - else: - label_text = legend_labels[:] - edge_col = "black" - legend_file_name = "Polydotplot_LCS_Shading_Legend_%%len_n%d." % lcs_shading_num + filetype - - if prefix != None and prefix != "": - if not prefix.endswith("-"): - prefix = prefix + "-" - legend_type = "LCS" - if prefix.startswith("custom-matrix"): - prefix = prefix.replace("custom-matrix", "")[1:] - legend_type = "CustomMatrix" - legend_file_name = prefix + legend_file_name.replace("LCS", legend_type) - - # plot legend figure - fig, ax = P.subplots(3, 1, figsize=(len(colors)*2, len(colors)*2)) - for idx in range(len(colors)): - ax[0].bar(data_points[idx]+1, data_points[idx]+1, color=colors[idx], label=label_text[idx], - alpha=alphas[idx], edgecolor=edge_col) - ax[1].bar(data_points[idx]+1, 0, color=colors[idx], label=label_text[idx], - alpha=alphas[idx], edgecolor=edge_col) - ax[2].bar(data_points[idx]+1, 0, color=colors[idx], label=label_text[idx], - alpha=alphas[idx], edgecolor=edge_col) - ax[1].set_ylim(0,1) - ax[2].set_ylim(0,1) - ax[1].legend(ncol=((len(colors)-1)//max_legend_length_row)+1, framealpha=1) # vertical legend - col_num = len(colors) - if len(colors) > max_legend_length_col: - remainder = 0 - if len(colors) % max_legend_length_col != 0: - remainder = 1 - row_num = len(colors) // max_legend_length_col + remainder - remainder = 0 - if len(colors) % row_num != 0: - remainder = 1 - col_num = len(colors) // row_num + remainder - ax[2].legend(ncol=col_num, framealpha=1) # horizontal legend - - P.savefig(legend_file_name) - - return legend_file_name - - -############################### -# Analysis Functions # -############################### - -def wobble_replacement(sequence, general_ambiguity_code, verbose=False): - """ - get all degenerated sequences for sequence with ambiguous residues - (only residues considered that are keys in wobble_dictionary) - """ - - # get positions of ambiguous residues - wobble_pos = [] - for idx in range(len(sequence)): - letter = sequence[idx] - if letter in general_ambiguity_code.keys(): - wobble_pos.append(idx) - - if verbose: - text = "\t%d wobbles" % len(wobble_pos) - logprint(text, start=False, printing=True) - - # replace one wobble through each iteration by all possible residues - # repeat if still wobbles in new kmers - kmer_variants = [sequence] - while True: - if verbose: - text = "\t\t%d kmer variants" % len(kmer_variants) - logprint(text, start=False, printing=True) - temp_kmers = set([]) - for kmer in kmer_variants: - for idx in wobble_pos: - letter = kmer[idx] - if letter in general_ambiguity_code.keys(): - for base in general_ambiguity_code[kmer[idx]]: - newkmer = kmer[:idx] + base + kmer[idx+1:] - temp_kmers.add(newkmer) - wobble = False - for kmer in temp_kmers: - for idx in range(len(kmer)): - letter = kmer[idx] - if letter in general_ambiguity_code.keys(): - wobble = True - break - if wobble: - break - kmer_variants = set(list(temp_kmers)[:]) - if not wobble: - break - - return kmer_variants - -def split_diagonals(data, stepsize=1): - """ - split array if point difference exceeds stepsize - data = sorted list of numbers - """ - return np.split(data, np.where(np.diff(data) != stepsize)[0]+1) - -def longest_common_substring(s1, s2): - m = [[0] * (1 + len(s2)) for i in xrange(1 + len(s1))] - longest, x_longest = 0, 0 - for x in xrange(1, 1 + len(s1)): - for y in xrange(1, 1 + len(s2)): - if s1[x - 1] == s2[y - 1]: - m[x][y] = m[x - 1][y - 1] + 1 - if m[x][y] > longest: - longest = m[x][y] - x_longest = x - else: - m[x][y] = 0 - return longest - -def lcs_from_x_values(x_values): - """ - calculate length of longest common substring based on nested list of numbers - """ - if len(x_values) == 0: - return 0 - # get lengths of each subarray data - lengths = np.array([len(i) for i in x_values]) - return max(lengths) - - -############################### -# Matching Functions # -############################### - -def find_match_pos_diag(seq1, seq2, wordsize, report_lcs=False, rc_option=True, convert_wobbles=False, max_N_percentage=49, type_nuc=True, verbose=False): - """ - find all matching positions with matches >= wordsize - convert matching points into lines of the length of the match - (+ optional handling of ambiguities) - """ - global t1 # timer - - # look for Ns in DNA or Xs in proeins (minimum word size) - if type_nuc == True: - any_residue = "N" - else: - any_residue = "X" - - # read sequences - seq_one = seq1.upper(); len_one = len(seq_one) - seq_two = seq2.upper(); len_two = len(seq_two) - - # set ambiguity code for wobble replacement - general_ambiguity_code = alphabets(type_nuc)[2] # nucleotide_ambiguity_code or aminoacid_ambiguity_code - - # forward - ################################# - kmer_pos_dict_one = {}; kmer_pos_dict_two = {} # dictionaries for both sequences - - # reverse complement - ################################# - kmer_pos_dict_three = {}; kmer_pos_dict_four = {} # dictionaries for both sequences - - # create dictionaries with kmers (wordsize) and there position(s) in the sequence - if rc_option: - data_list = [(str(seq_one), kmer_pos_dict_one), - (str(seq_two), kmer_pos_dict_two), - (str(seq_one), kmer_pos_dict_three), - (str(seq_two.reverse_complement()), kmer_pos_dict_four)] - else: - data_list = [(str(seq_one), kmer_pos_dict_one), - (str(seq_two), kmer_pos_dict_two)] - for (seq, kmer_pos_dict) in data_list: - for i in range(len(seq)-wordsize+1): - kmer = seq[i:i+wordsize] - # discard kmer, if too many Ns included - if kmer.count(any_residue)*100./wordsize <= max_N_percentage: - if not convert_wobbles: - try: - kmer_pos_dict[kmer].append(i) - except KeyError: - kmer_pos_dict[kmer] = [i] - else: - wobbles = False - for item in general_ambiguity_code.keys(): - if item in kmer: - wobbles = True - break - if not wobbles: - try: - kmer_pos_dict[kmer].append(i) - except KeyError: - kmer_pos_dict[kmer] = [i] - else: - kmer_variants = wobble_replacement(kmer, general_ambiguity_code) - for new_kmer in kmer_variants: - # print "\t", new_kmer - try: - kmer_pos_dict[new_kmer].append(i) - except KeyError: - kmer_pos_dict[new_kmer] = [i] - - # find kmers shared between both sequences - matches_for = set(kmer_pos_dict_one).intersection(kmer_pos_dict_two) # forward - matches_rc = set(kmer_pos_dict_three).intersection(kmer_pos_dict_four) # reverse complement - - if verbose: - text = "[matches: %i for; %.i rc]" % (len(matches_for), len(matches_rc)) - logprint(text, start=False, printing=True) - - # create lists of x and y co-ordinates for scatter plot - # keep all coordinates of all shared kmers (may match multiple times) - diag_dict_for = {} - diag_dict_rc = {} - for (match_list, pos_dict1, pos_dict2, diag_dict) in [(matches_for, kmer_pos_dict_one, kmer_pos_dict_two, diag_dict_for), - (matches_rc, kmer_pos_dict_three, kmer_pos_dict_four, diag_dict_rc)]: - for kmer in match_list: - for i in pos_dict1[kmer]: - for j in pos_dict2[kmer]: - diag = i-j - points = set(range(i+1, i+wordsize+1)) - if not diag in diag_dict.keys(): - diag_dict[diag] = points - else: - diag_dict[diag].update(points) - - # convert coordinate points to line start and stop positions - x1 = [] # x values reverse - y1 = [] # y values forward - for diag in diag_dict_for.keys(): - x_values = np.array(sorted(diag_dict_for[diag])) - x1.extend(split_diagonals(x_values)) - y_values = split_diagonals(x_values - diag) - y1.extend(y_values) - - x2 = [] # x values rc - y2 = [] # y values rc - if rc_option: - for diag in diag_dict_rc.keys(): - factor = len_two + diag + 1 - x_values = np.array(sorted(diag_dict_rc[diag])) - x2.extend(split_diagonals(x_values)) - y_values = split_diagonals(factor - x_values, -1) - y2.extend(y_values) - - if verbose: - t1 = time_track(t1) - - if not report_lcs: - return np.array(x1), np.array(y1), np.array(x2), np.array(y2) - else: - # get length of longest common substring based on match lengths - lcs_for = lcs_from_x_values(x1) - lcs_rev = lcs_from_x_values(x2) - return np.array(x1), np.array(y1), np.array(x2), np.array(y2), lcs_for, lcs_rev - -def find_match_pos_regex(seq1, seq2, wordsize, substitution_count=0, report_lcs=False, rc_option=True, convert_wobbles=False, max_N_percentage=49, type_nuc=True, verbose=False): - """ - find all matching positions with matches >= wordsize via regular expression search - fuzzy matching - allow up to substitution_count substitutions - convert matching points into lines of the length of the match - (+ optional handling of ambiguities) - """ - global t1 # timer - - # read sequences - seq_one = seq1.upper(); len_one = len(seq_one) - seq_two = seq2.upper(); len_two = len(seq_two) - - # set ambiguity code for wobble replacement - general_ambiguity_code = alphabets(type_nuc)[2] # nucleotide_ambiguity_code or aminoacid_ambiguity_code - ambiguity_match_dict = alphabets(type_nuc)[3] - - ambiq_residues = "[%s]" % "".join(general_ambiguity_code.keys()) - - # look for Ns in DNA or Xs in proeins (minimum word size) - if type_nuc == True: - any_residue = "N" - else: - any_residue = "X" - - # check for wobble presence - if not (regex.search(ambiq_residues, str(seq_one)) == None and regex.search(ambiq_residues, str(seq_two)) == None): - wobble_found = True - else: - wobble_found = False - - # dictionary for matches - diag_dict_for = {} - diag_dict_rc = {} - counter = [0, 0] - - # one-way matching - if rc_option: - data_list = [(str(seq_one), str(seq_two), diag_dict_for, 0), - (str(seq_one), str(seq_two.reverse_complement()), diag_dict_rc, 1)] - else: - data_list = [(str(seq_one), str(seq_two), diag_dict_for, 0)] - - for seq_query, seq_target, diag_dict, counter_pos in data_list: - # split query sequence into kmers - if not rc_option and counter_pos == 1: - break - - for idx in range(len(str(seq_query))-wordsize+1): - kmer = str(seq_query)[idx:idx+wordsize] - - # skip excessive N/X stretches (big black areas) - if kmer.count(any_residue)*100./wordsize <= max_N_percentage: - # convert kmer to regular expression for wobble_matching - if convert_wobbles and wobble_found: - kmer_string = "" - # replace each residue with matching residues or wobbles - for jdx in range(len(kmer)): - kmer_string += ambiguity_match_dict[kmer[jdx]] - else: - kmer_string = kmer - - # convert to regular expression tolerating substitution errors - if type(substitution_count) == int and substitution_count != 0: - kmer_string = "(%s){s<=%d}" % (kmer_string, substitution_count) - - # search for regular expression in target sequence - kdx = 0 - start = True - if regex.search(kmer_string, seq_target[kdx:]) != None: - counter[counter_pos] += 1 - while regex.search(kmer_string, seq_target[kdx:]) != None: - # search for regular expression pattern in target sequence - result = regex.search(kmer_string, seq_target[kdx:]) - - kmer2 = seq_target[kdx:][result.start():result.end()] - - # skip excessive N/X stretches (big black areas) - if kmer2.count(any_residue)*100./wordsize <= max_N_percentage: - diag = idx-(kdx+result.start()) - points = set(range(idx+1, idx+wordsize+1)) - if not diag in diag_dict.keys(): - diag_dict[diag] = points - else: - diag_dict[diag].update(points) - - kdx += result.start() + 1 - if kdx >= len(seq_target): - break - elif regex.search(kmer_string, seq_target[kdx:]) != None: - counter[counter_pos] += 1 - - if verbose: - text = "%5.i \tforward matches" % counter[0] - text += "\n%5.i \treverse complementary matches" % counter[1] - logprint(text, start=False, printing=True) - - # convert coordinate points to line start and stop positions - x1 = [] # x values reverse - y1 = [] # y values forward - for diag in diag_dict_for.keys(): - x_values = np.array(sorted(diag_dict_for[diag])) - x1.extend(split_diagonals(x_values)) - y_values = split_diagonals(x_values - diag) - y1.extend(y_values) - - x2 = [] # x values rc - y2 = [] # y values rc - if rc_option: - for diag in diag_dict_rc.keys(): - factor = len_two + diag + 1 - x_values = np.array(sorted(diag_dict_rc[diag])) - x2.extend(split_diagonals(x_values)) - y_values = split_diagonals(factor - x_values, -1) - y2.extend(y_values) - - if verbose: - t1 = time_track(t1) - - if not report_lcs: - return np.array(x1), np.array(y1), np.array(x2), np.array(y2) - else: - # get length of longest common substring based on match lengths - lcs_for = lcs_from_x_values(x1) - lcs_rev = lcs_from_x_values(x2) - return np.array(x1), np.array(y1), np.array(x2), np.array(y2), lcs_for, lcs_rev - - -############################### -# Dot Plot Functions # -############################### - -def selfdotplot(input_fasta, wordsize, prefix=None, plot_size=10, label_size=10, filetype='png', type_nuc=True, convert_wobbles=False, substitution_count=0, alphabetic_sorting=False, max_N_percentage=49, verbose=False, multi=True, ncols=4, nrows=5, gff_files=[], gff_color_dict={"others": ("grey", 1, 0)}, title_length=float("Inf"), title_selectpos="B"): - """ - self-against-self dotplot - partially from biopython cookbook - """ - - # read sequences - seq_dict, sequences = read_seq(input_fasta) - if seq_dict == {}: - logprint("\nFailed to load sequences") - return [] - - if alphabetic_sorting: - sequences = sorted(sequences) - - # check if at least one input sequence - if len(sequences) == 0: - text = "\n%s\n\nCreating %s selfdotplot images\n%s\n\n=>" % (50*"=", len(sequences), 28*"-") - text += " No sequences provided for selfdotplot!\n\nTerminating polydotplot!" - logprint(text, start=False, printing=True) - return - elif len(sequences) == 1 and multi: - text = "\n\nCreating collage output for single selfdotplot!" - text += "\nRecommendation: Change to individual mode by using '--collage_output n'!\n\n" - logprint(text, start=False, printing=True) - - if multi and (ncols == 0 or nrows == 0): - ncols = max(ncols, 1) - nrows = max(nrows, 1) - text = "\n\nSelfdotplot Collage: Invalid collage - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - if multi and ncols > len(sequences): - ncols = len(sequences) - nrows = 1 - text = "\n\nSelfdotplot Collage: Few sequences - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - elif multi and ncols*(nrows-1) > len(sequences): - nrows = ((len(sequences)-1) // ncols) + 1 - text = "\n\nSelfdotplot Collage: Few sequences - correcting number of rows:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - if multi and not (nrows == 1 and ncols == 1) and plot_size <= label_size/2: - label_size = plot_size * 3 // 2 - text = "Reducing label size for better visualization to %d\n" % label_size - logprint(text, start=False, printing=True) - - # read gff annotation data if provided for shading - if gff_files != None and gff_files != []: - text = "\n%s\n\nReading %s GFF annotation files\n%s\n\n=> %s\n" % (50*"=", len(gff_files), 28*"-", ", ".join(gff_files)) - logprint(text, start=False, printing=True) - feat_dict = read_gffs(gff_files, color_dict=gff_color_dict, type_nuc=type_nuc, prefix=prefix, filetype=filetype, verbose=verbose) - - # check input variables - if convert_wobbles and max_N_percentage > 49: - max_N_percentage=49 - text = "Provide valid max_N_percentage, kmers with >=50% Ns are ignored\n" - logprint(text, start=False, printing=True) - - if filetype not in ["png", "pdf", "svg"]: - text = "Provide valid file type - png, pdf, or svg - given:%s\n" % filetype - logprint(text, start=False, printing=True) - filetype = "png" - - global t1 - - print "\n%s\n\nCreating %s selfdotplot images\n%s\n\n=>" % (50*"=", len(sequences), 28*"-"), - log_txt = "\n%s\n\nCreating %s selfdotplot images\n%s\n\n=>" % (50*"=", len(sequences), 28*"-") - - # preparations for file name - name_graph = "Selfdotplots" - if prefix != None: - if not prefix[-1] == "-": - prefix = prefix + "-" - else: - prefix = "" - suffix = "" - if convert_wobbles: - suffix += "_wobbles" - if substitution_count != 0: - suffix += "_S%d" % substitution_count - if multi: - suffix += "_collage" - - # calculate fig ratios - if not multi: - ncols = 1 - nrows = 1 - figsize_x, figsize_y = calc_fig_ratio(ncols, nrows, plot_size) - - P.cla() # clear any prior graph - if multi: - fig = P.figure(figsize=(figsize_x, figsize_y)) - page_counter = 1 - list_of_png_names = [] - - counter = 0 - for seq_name in sequences: - print seq_name, - log_txt += " " + seq_name - - counter += 1 - if not multi: - P.cla() # clear any prior graph - - # read sequence - seq_record = seq_dict[seq_name] - name_seq = seq_record.id - seq_one = seq_record.seq.upper() - length_seq = len(seq_one) - - # get positions of matches - if substitution_count != 0: - # print "RE" - x_lists, y_lists, x_lists_rc, y_lists_rc = find_match_pos_regex(seq_one, seq_one, wordsize, substitution_count=substitution_count, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, type_nuc=type_nuc, verbose=verbose) - else: - # print "DIAG", - x_lists, y_lists, x_lists_rc, y_lists_rc = find_match_pos_diag(seq_one, seq_one, wordsize, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, type_nuc=type_nuc, verbose=verbose) - - # plotting with matplotlib - ################################# - - # combined plotting - if multi: - # plotting subplot with matplotlib - ax = P.subplot(nrows, ncols, counter) # rows, columns, plotnumber - - # shade annotated regions - if gff_files != None and gff_files != []: - if seq_name in feat_dict.keys(): - features = feat_dict[seq_name] - for item in features: - feat_type, start, stop = item - feat_color, strength, zoom = gff_color_dict[feat_type.lower()] - start = max(0, start - zoom - 0.5) - stop = min(length_seq+1, stop + zoom + 0.5) - width = stop - start - ax.add_patch(patches.Rectangle((start, start), # (x,y) - width, width, # width, height - edgecolor=None, linewidth=line_width+zoom, - fill=True, facecolor=feat_color, - alpha=strength)) - - # collect lines - lines = [] - color_list = [] - for (x_lines, y_lines, col) in [(x_lists_rc, y_lists_rc, line_col_rev), (x_lists, y_lists, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # format axes - P.xlim(0, length_seq+1) - P.ylim(length_seq+1, 0) # rotate y axis (point downwards) - P.xlabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.ylabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - P.title(unicode_name(shorten_name(name_seq, max_len=title_length, title_selectpos=title_selectpos)), fontsize=label_size, fontweight='bold') - # P.title(unicode_name(name_seq), fontsize=label_size*1.3, fontweight='bold') - - # save figure and reinitiate if page is full - if counter == ncols * nrows: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - P.subplots_adjust(hspace=0.5, wspace=0.5) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' % (prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() - - list_of_png_names.append(fig_name) - - counter = 0 - page_counter += 1 - - fig = P.figure(figsize=(figsize_x, figsize_y)) - - # plotting separate figure files - else: # not multi - - fig = P.figure(figsize=(plot_size, plot_size)) # figure size needs to be a square - ax = P.subplot(1, 1, 1) # rows, columns, plotnumber - - # shade annotated regions - if gff_files != None and gff_files != []: - if seq_name in feat_dict.keys(): - features = feat_dict[seq_name] - for item in features: - feat_type, start, stop = item - feat_color, strength, zoom = gff_color_dict[feat_type.lower()] - start = max(0, start - zoom - 0.5) - stop = min(length_seq+1, stop + zoom + 0.5) - width = stop - start - ax.add_patch(patches.Rectangle((start, start), # (x,y) - width, width, # width, height - edgecolor=None, linewidth=line_width+zoom, - fill=True, facecolor=feat_color, - alpha=strength)) - - # collect lines - lines = [] - number = 0 - color_list = [] - for (x_lines, y_lines, col) in [(x_lists_rc, y_lists_rc, line_col_rev), (x_lists, y_lists, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # format axes - P.xlim(0, length_seq+1) - P.ylim(length_seq+1, 0) # rotate y axis (point downwards) - P.xlabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.ylabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - P.title(unicode_name(shorten_name(name_seq, max_len=title_length, title_selectpos=title_selectpos)), fontsize=label_size*1.3, fontweight='bold') - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s-%d_%s_wordsize%i%s.%s' %(prefix, name_graph, counter, name_seq, wordsize, suffix, filetype) - P.savefig(fig_name, bbox_inches='tight') - - P.close() - P.cla() # clear any prior graph - - list_of_png_names.append(fig_name) - - if multi and counter >= 1: - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - P.subplots_adjust(hspace=0.5, wspace=0.5) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' %(prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() # clear any prior graph - - list_of_png_names.append(fig_name) - - print "\n\nDrawing selfdotplots done" - log_txt += "\n\nDrawing selfdotplots done" - logprint(log_txt, start=False, printing=False) - - return list_of_png_names - -def pairdotplot(input_fasta, wordsize, prefix=None, plot_size=10, label_size=10, filetype='png', type_nuc=True, convert_wobbles=False, substitution_count=0, alphabetic_sorting=False, max_N_percentage=49, verbose=False, multi=True, ncols=4, nrows=5, length_scaling=True, scale_delim_col="red", title_length=float("Inf"), title_selectpos="B"): - """ - pairwise dotplot (all-against-all) - """ - - # read sequences - seq_dict, sequences = read_seq(input_fasta) - if seq_dict == {}: - logprint("\nFailed to load sequences") - return [] - - if alphabetic_sorting: - sequences = sorted(sequences) - - # check if at least two input sequences - if len(sequences) < 2: - text = "\n%s\n\nCreating %d paired dotplot image \n%s\n\n=>" % (50*"=", len(sequences)*(len(sequences)-1)/2, 36*"-") - text += " Please provide at least two sequences for pairdotplot!\n\nTerminating paired dotplot!" - logprint(text, start=False, printing=True) - return - elif len(sequences) == 2 and multi: - text = "\n\nCreating collage output for single pairdotplot!" - text += "\nRecommendation: Change to individual mode by using '--collage_output n'!\n\n" - logprint(text, start=False, printing=True) - - if multi and (ncols == 0 or nrows == 0): - ncols = max(ncols, 1) - nrows = max(nrows, 1) - text = "\n\nPairdotplot Collage: Invalid collage settings - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - if multi and ncols > len(sequences)*(len(sequences)-1): - ncols = len(sequences) - nrows = 1 - text = "\n\nPairdotplot Collage: Few sequences - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - elif multi and ncols*(nrows-1) > len(sequences)*(len(sequences)-1): - nrows = ((len(sequences)-1) // ncols) + 1 - text = "\n\nPairdotplot Collage: Few sequences - correcting number of rows:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - - text = "\n%s\n\nCreating %d paired dotplot image for\n%s\n\n=>" % (50*"=", len(sequences)*(len(sequences)-1)/2, 36*"-") - text += ", ".join(sequences) + "\n" - logprint(text, start=False, printing=True) - - if multi and not (nrows == 1 and ncols == 1) and plot_size <= label_size/2: - label_size = plot_size * 3 // 2 - text = "Reducing label size for better visualization to %d\n" % label_size - logprint(text, start=False, printing=True) - - y_label_rotation = "vertical" - - # check input variables - if convert_wobbles and max_N_percentage > 49: - max_N_percentage=49 - text = "Provide valid max_N_percentage, kmers with >50% are ignored\n" - logprint(text, start=False, printing=True) - - if filetype not in ["png", "pdf", "svg"]: - text = "Provide valid file type - png, pdf, or svg - given: %s\n" % filetype - logprint(text, start=False, printing=True) - filetype = "png" - - # preparations for file name - name_graph = "Pairdotplot" - if prefix != None: - if not prefix[-1] == "-": - prefix = prefix + "-" - else: - prefix = "" - suffix = "" - if convert_wobbles: - suffix += "_wobbles" - if substitution_count != 0: - suffix += "_S%d" % substitution_count - if length_scaling: - suffix += "_scaled" - if multi: - suffix += "_collage" - - - - # calculate fig ratios - if not multi: - ncols = 1 - nrows = 1 - figsize_x, figsize_y = calc_fig_ratio(ncols, nrows, plot_size) - - P.cla() # clear any prior graph - list_of_png_names = [] - if multi: - fig = P.figure(figsize=(figsize_x, figsize_y)) - page_counter = 1 - - # prepare LCS data file - lcs_data_file = open("%sPairdotplot_lcs_data_file%s.txt" % (prefix, suffix.replace("_scaled", "").replace("_collage", "")), 'w') - lcs_data_file.write("\t".join(["#title1", "title2", "len_seq1", "len_seq2", "len_lcs_for", "%_min_seq_len", "len_lcs_rev", "%_min_seq_len"])+"\n") - - counter, seq_counter = 0, 0 - print "Drawing pairwise dotplot...", - log_txt = "Drawing pairwise dotplot..." - if verbose: - seq_text = "" - for idx in range(len(sequences)-1): - if verbose: - print "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]), - seq_text += "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]) - rec_two = seq_dict[sequences[idx]] - name_two = rec_two.id - seq_two = rec_two.seq - len_two = len(seq_two) - - for jdx in range(idx+1, len(sequences)): - rec_one = seq_dict[sequences[jdx]] - name_one = rec_one.id - seq_one = rec_one.seq - len_one = len(seq_one) - - counter += 1 - seq_counter += 1 - if verbose: - print sequences[jdx], - seq_text += " " + sequences[jdx] - elif not seq_counter % 25: - print seq_counter, - log_txt += " " + str(seq_counter) - - # get positions of matches - if substitution_count != 0: - # print "RE" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_regex(seq_one, seq_two, wordsize, substitution_count=substitution_count, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - else: - # print "DIAG" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_diag(seq_one, seq_two, wordsize, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - - # write LCS data file - lcs_data_file.write("\t".join([name_one, name_two, str(len_one), str(len_two), - str(lcs_for), str(round((lcs_for*100./min(len_one, len_two)), 3)), - str(lcs_rev), str(round((lcs_rev*100./min(len_one, len_two)), 3))]) + "\n") - - - # plotting with matplotlib - ################################# - - # combined plotting - if multi: - # plotting subplot with matplotlib - ax = P.subplot(nrows, ncols, counter) # rows, columns, plotnumber - else: - # calculate figure size for separate figures - if len_one >= len_two: - sizing = (plot_size, max(2, (plot_size)*len_two*1./len_one)) - # sizing = (plot_size, min(plot_size, max(2, (plot_size-2)*len_two*1./len_one+2))) - else: - sizing = (max(2, (plot_size)*len_one*1./len_two), plot_size) - # sizing = (min(plot_size, max(2, (plot_size-2)*len_one*1./len_two+2)), plot_size) - fig = P.figure(figsize=(plot_size, plot_size)) - - ax = P.subplot(1, 1, 1) - - # collect lines - lines = [] - color_list = [] - for (x_lines, y_lines, col) in [(x2, y2, line_col_rev), (x1, y1, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # format axes - P.xlabel(unicode_name(shorten_name(name_one, max_len=title_length, title_selectpos=title_selectpos)) + " [%s]" % aa_bp_unit, fontsize=label_size, fontweight='bold', labelpad=4) - P.ylabel(unicode_name(shorten_name(name_two, max_len=title_length, title_selectpos=title_selectpos)) + " [%s]" % aa_bp_unit, fontsize=label_size, fontweight='bold', labelpad=4) - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - - if not multi: - if length_scaling: - ax.set_aspect(aspect='equal', adjustable='box', anchor='NW') - P.xlim(0, len_one+1) - P.ylim(len_two+1, 0) # rotate y axis (point downwards) - elif not length_scaling: - P.xlim(0, len_one+1) - P.ylim(len_two+1, 0) # rotate y axis (point downwards) - else: - max_len = max(len_one, len_two) - P.xlim(0, max_len+1) - P.ylim(max_len+1, 0) # rotate y axis (point downwards) - - # plot line deliminating shorter sequence - if max_len != len_one: - ax.plot((len_one+1, len_one+1), (0, len_two), marker="", linestyle="--", color=scale_delim_col, markerfacecolor="r") - if max_len != len_two: - ax.plot((0, len_one), (len_two+1, len_two+1), marker="", linestyle="--", color=scale_delim_col, markerfacecolor="r") - - # evtl. switch x axis position - if x_label_pos_top: - ax.xaxis.tick_top() - ax.xaxis.set_label_position('top') - P.setp(ax.get_xticklabels(), fontsize=label_size*.9) - P.setp(ax.get_yticklabels(), fontsize=label_size*.9) - - # save figure and reinitiate if page is full - if multi and counter == ncols * nrows: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - if x_label_pos_top: - P.subplots_adjust(hspace=.5, wspace=.5, top=0.95) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=.5, wspace=.5, bottom=0.05) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' %(prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() - - list_of_png_names.append(fig_name) - - counter = 0 - page_counter += 1 - - fig = P.figure(figsize=(figsize_x, figsize_y)) - - # plotting separate figure files - elif not multi: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - if y_label_rotation == "horizontal": - if x_label_pos_top: - P.subplots_adjust(hspace=0.02, wspace=0.02, left=0.13, top=0.95) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=0.02, wspace=0.02, left=0.13, bottom=0.05) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=0.02, wspace=0.02) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s-%d_wordsize%i%s.%s' % (prefix, name_graph, counter, wordsize, suffix, filetype) - P.savefig(fig_name) - P.close() - P.cla() - - list_of_png_names.append(fig_name) - fig = P.figure() - - # save figure - if multi and counter >= 1: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - if x_label_pos_top: - P.subplots_adjust(hspace=0.5, wspace=0.5, top=0.95) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=0.5, wspace=0.5, bottom=0.05) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' %(prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() - - list_of_png_names.append(fig_name) - - if not verbose: - print seq_counter, "done" - log_txt += str(seq_counter) + " done" - else: - print "\n%d done" % seq_counter - log_txt += "\n%d done" % seq_counter - logprint(log_txt, start=False, printing=False) - - if verbose: - print - logprint(seq_text, start=False, printing=False) - - return list_of_png_names - -def polydotplot(input_fasta, wordsize, prefix=None, plot_size=10, label_size=10, filetype='png', type_nuc=True, convert_wobbles=False, substitution_count=0, alphabetic_sorting=False, max_N_percentage=49, verbose=False, lcs_shading=True, lcs_shading_ref=0, lcs_shading_interval_len=100, lcs_shading_ori=0, lcs_shading_num=5, spacing=0.04, input_user_matrix_file="", user_matrix_print=True, gff_files=[], gff_color_dict={"others": ("grey", 1, 0)}, title_length=float("Inf"), title_selectpos="B", rotate_labels=False): - """ - all-against-all dotplot - derived from dotplot function - - lcs_shading_refs: - 0 color relative to maximum lcs observed in dataset [default] - 1 color by coverage of shorter sequence (e.g. lcs = 70% of seq1) - lcs_shading_ori - 0 forward only - 1 reverse only - 2 both orientations (in opposite plot) - """ - - # read sequences - seq_dict, sequences = read_seq(input_fasta) - if seq_dict == {}: - logprint("\nFailed to load sequences") - return [] - - if alphabetic_sorting: - sequences = sorted(sequences) - - if len(sequences) == 0: - text = "\n%s\n\nCreating %dx%d polydotplot image\n%s\n\n=>" % (50*"=", len(sequences), len(sequences), 30*"-") - text += " No sequences provided for polydotplot!\n\nTerminating polydotplot!" - logprint(text, start=False, printing=True) - return - elif len(sequences) == 1: - text = "\n\nCreating polydotplot for single sequence!" - text += "\nRecommendation: Use selfdotplot via '--plotting_mode 0'!\n\n" - logprint(text, start=False, printing=True) - - - text = "\n%s\n\nCreating %dx%d polydotplot image\n%s\n\n=>" % (50*"=", len(sequences), len(sequences), 30*"-") - text += " " + " ".join(sequences) + "\n" - logprint(text, start=False, printing=True) - - # check input variables - if convert_wobbles and max_N_percentage > 49: - max_N_percentage=49 - text = "Provide valid max_N_percentage, kmers with >50% are ignored\n" - logprint(text, start=False, printing=True) - - if filetype not in ["png", "pdf", "svg"]: - text = "Provide valid file type - png, pdf, or svg - given: %s\n" % filetype - logprint(text, start=False, printing=True) - filetype = "png" - - if lcs_shading and not type_nuc: - if lcs_shading_ori != 0: - lcs_shading_ori = 0 - text = "Protein shading does not support reverse complementary matching!\n" - logprint(text, start=False, printing=True) - - # read custom shading matrix & match names of sequences to fasta - if input_user_matrix_file != "" and input_user_matrix_file != None: - logprint("Reading user matrix file: %s" % input_user_matrix_file) - # lcs_shading_ori = 2 - custom_dict = read_matrix(input_user_matrix_file) - if custom_dict != {}: - custom_shading = True - custom_similarity_dict = {} - invalid_entries = [] - custom_max = 0 - custom_min = float("Inf") - for key in custom_dict.keys(): - number_key = [] - - # convert number into float - try: - value = float(custom_dict[key]) - if not "." in custom_dict[key]: - value = int(custom_dict[key]) - custom_max = max(custom_max, value) - custom_min = min(custom_min, value) - except: - value = custom_dict[key] - if value == "": - value = None - invalid_entries.append(key) - # match matrix names with sequence names - for item in key: - if item in sequences: - number_key.append(sequences.index(item)) - else: - number_key.append(-1) - # dictionary with tuple of sorted sequence indices as key and number as value - custom_similarity_dict[tuple(sorted(number_key))] = value - if len(invalid_entries) != 0: - text = "No valid number in custom similarity matrix for %d entries: \n\t" % (len(invalid_entries)) - for key in invalid_entries: - text += str(key) + " - " + str(custom_dict[key]) + "; " - logprint(text[:-2]+"\n") - - text = "Custom user matrix given: min %.2f, max %.2f\n" % (custom_min, custom_max) - - # artificially rounding intervals if likely identity/divergence percentages - if 0 <= custom_min < 1 and 0 < custom_max <= 1: - rounding_factor = 5 - multi_factor = 100 - text += " > artificially rounding custom shading intervals: old (%.2f, %.2f) - " % (custom_min, custom_max) - custom_min = max(0, (multi_factor*custom_min // rounding_factor) * (1.*rounding_factor/multi_factor)) - custom_max = min((multi_factor*custom_max // rounding_factor) * (1.*rounding_factor/multi_factor), 1) - text += "new (%.2f, %2f)\n" % (custom_min, custom_max) - - elif 0 <= custom_min < 100 and 0 < custom_max <= 100: - rounding_factor = 5 - text += " > artificially rounding custom shading intervals: old (%.2f, %.2f) - " % (custom_min, custom_max) - custom_min = max(0, (custom_min // rounding_factor) * rounding_factor) - custom_max = min((custom_max // rounding_factor) * rounding_factor, 100) - text += "new (%d, %d)\n" % (custom_min, custom_max) - - logprint(text) - - else: - custom_shading = False - - # read gff annotation data if provided for shading - if gff_files != None and gff_files != []: - text = "\n%s\n\nReading %s GFF annotation files\n%s\n\n=> %s\n" % (50*"=", len(gff_files), 28*"-", ", ".join(gff_files)) - logprint(text, start=False, printing=True) - feat_dict = read_gffs(gff_files, color_dict=gff_color_dict, type_nuc=type_nuc, prefix=prefix, filetype=filetype, verbose=verbose) - - name_graph = "Polydotplot" - suffix = "" - if convert_wobbles: - suffix += "_wobbles" - if substitution_count != 0: - suffix += "_S%d" % substitution_count - if custom_shading: - suffix += "_matrix" - if lcs_shading: - suffix += "_%dshades_ref%d_ori%s" % (lcs_shading_num+1, lcs_shading_ref, lcs_shading_ori) - if "ref2" in suffix and type_nuc: - suffix = suffix.replace("ref2", "%dbp" % lcs_shading_interval_len) - elif "ref2" in suffix: - suffix = suffix.replace("ref2", "%daa" % lcs_shading_interval_len) - - - # name and create output files (names derived from SEQNAME) - if prefix != None and str(prefix) != "": - prefix = str(prefix) + "-" - else: - prefix = "" - - # preparations for background shading - if lcs_shading or custom_shading: - # create color range white to grey - colors = create_color_list(lcs_shading_num+1, color_map=None, logging=True) - colors_2 = create_color_list(lcs_shading_num+1, color_map="OrRd", logging=True) - - if custom_shading: - text = "Custom Matrix Colors: " + ", ".join(colors_2) - - # write lcs lengths to file - lcs_data_file = open("%sPolydotplot_lcs_data_file%s.txt" % (prefix, suffix.replace("_scaled", "").replace("_collage", "")), 'w') - lcs_data_file.write("\t".join(["#title1", "title2", "len_seq1", "len_seq2", "len_lcs_for", "%_min_seq_len", "len_lcs_rev", "%_min_seq_len"])+"\n") - - # compare sequences pairwise - save lcs and line information in dictionary for plotting - data_dict = {} # keys = tuple(idx, jdx), value = x1, y1, x2, y2 (line positions) - lcs_dict = {} # keys = tuple(idx, jdx), value = length of lcs: lcs_len or (lcs_for, lcs_rev) - for_lcs_set = set([]) # keep lengths to calculate max (excluding self comparisons) - rev_lcs_set = set([]) # keep lengths to calculate max (all) - - text = "\nTotal plot count: %d" % (len(sequences)*(len(sequences))) - text += "\nTotal calculations: %d" % (len(sequences)*(len(sequences)+1)/2) - logprint(text, start=False, printing=True) - - print "\nCalculating shared regions and lengths of longest_common_substring...", - log_txt = "\nCalculating shared regions and lengths of longest_common_substring..." - # determine matches and length of lcs by comparing all sequence pairs - if verbose: - seq_text = "" - counter = 0 - for idx in range(len(sequences)): - if verbose: - print "\n%d\t%s vs." % ((counter+1), sequences[idx]), - seq_text += "\n%d\t%s vs." % ((counter+1), sequences[idx]) - rec_two = seq_dict[sequences[idx]] - name_two = rec_two.id - seq_two = rec_two.seq - len_two = len(seq_two) - - for jdx in range(idx, len(sequences)): - rec_one = seq_dict[sequences[jdx]] - name_one = rec_one.id - seq_one = rec_one.seq - len_one = len(seq_one) - - counter += 1 - if verbose: - print sequences[jdx], - seq_text += " " + sequences[jdx] - elif len(sequences) < 5: - print "\t%s (%d %s), %s (%d %s)" % (name_one, len_one, aa_bp_unit, name_two, len_two, aa_bp_unit) - log_txt += "\t%s (%d %s), %s (%d %s)\n" % (name_one, len_one, aa_bp_unit, name_two, len_two, aa_bp_unit) - else: - if not counter % 25: - print counter, - log_txt += str(counter) - - # get positions of matches & length of longest common substring based on match lengths - if substitution_count != 0: - # print "RE" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_regex(seq_one, seq_two, wordsize, substitution_count=substitution_count, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - else: - # print "DIAG" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_diag(seq_one, seq_two, wordsize, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - data_dict[(idx, jdx)] = x1[:], y1[:], x2[:], y2[:] - lcs_dict[idx, jdx] = lcs_for, lcs_rev - - if idx != jdx: - for_lcs_set.add(lcs_for) - rev_lcs_set.add(lcs_rev) - - lcs_data_file.write("\t".join([name_one, name_two, str(len_one), str(len_two), - str(lcs_for), str(round((lcs_for*100./min(len_one, len_two)), 3)), - str(lcs_rev), str(round((lcs_rev*100./min(len_one, len_two)), 3))]) + "\n") - - if not verbose: - print len(sequences)*(len(sequences)+1)/2, " done\n" - log_txt += str(len(sequences)*(len(sequences)+1)/2) + " done\n" - else: - print "\n%d done" % (len(sequences)*(len(sequences)+1)/2) - log_txt += "\n%d done" % (len(sequences)*(len(sequences)+1)/2) - logprint(log_txt, start=False, printing=False) - - if verbose: - logprint ("\n\nlcs_dict\n" + str(lcs_dict)) - if custom_shading: - logprint ("\ncustom_dict\n" + str(custom_dict)) - logprint ("\ncustom_similarity_dict\n\n" + str(custom_similarity_dict)) - - if verbose: - print - logprint(seq_text+"\n", start=False, printing=False) - - if lcs_shading_ref == 2: - color_bins = [] - text = "\nLCS lengh bins: " - for idx in range(lcs_shading_num): - color_bins.append(lcs_shading_interval_len*(idx+1)) - text += " " + str(lcs_shading_interval_len*(idx+1)) - logprint(text, start=False, printing=True) - - # calculate maximum lcs length - if lcs_shading_ori == 0: # forward only - if len(for_lcs_set) != 0: - max_lcs = max(for_lcs_set) - else: - max_lcs = None - elif lcs_shading_ori == 1: # reverse complement only - if len(rev_lcs_set) != 0: - max_lcs = max(rev_lcs_set) - else: - max_lcs = None - else: # both orientations - if len(rev_lcs_set) != 0 and len(for_lcs_set) != 0: - max_lcs = max(max(rev_lcs_set), max(for_lcs_set)) - elif len(rev_lcs_set) != 0: - max_lcs = max(rev_lcs_set) - elif len(for_lcs_set) != 0: - max_lcs = max(for_lcs_set) - else: - max_lcs = None - - if not max_lcs == None: - text = "Maximum LCS: %d %s" % (max_lcs, aa_bp_unit) - logprint(text, start=False, printing=True) - if custom_shading: - text = "Maximum custom value: %d\n" % custom_max - logprint(text, start=False, printing=True) - - # count sequences - ncols = len(sequences); nrows = len(sequences) - - # get sequence lengths to scale plot widths and heights accordingly - size_ratios = [] - for item in sequences: - size_ratios.append(len(seq_dict[item].seq)) - - P.cla() # clear any prior graph - # use GridSpec to resize plots according to sequence length - gs = gridspec.GridSpec(nrows, ncols, - width_ratios=size_ratios, - height_ratios=size_ratios) - fig = P.figure(figsize=(plot_size, plot_size)) - - # determine label orientations - if len(sequences) > 5 or rotate_labels: - x_label_rotation = 45 - y_label_rotation = "horizontal" - if x_label_pos_top: - xhalign = 'left' - xvalign = 'bottom' - else: - xhalign = 'right' - xvalign = 'top' - yhalign = "right" - else: - x_label_rotation = "horizontal" - y_label_rotation = "vertical" - xvalign = "center" - xhalign = "center" - yhalign = "center" - yvalign = 'center' - - print "\nDrawing polydotplot...", - log_txt = "\nDrawing polydotplot..." - - # draw subplots - if verbose: - if lcs_shading and custom_shading: - lcs_text = "\n" + "\t".join(["#Seq1", "Seq2", "LCS for [%s]" %aa_bp_unit, "LCS for [%s]" %aa_bp_unit, "Custom matrix value", "Matrix color index", "LCS color index"]) + "\n" - elif lcs_shading: - lcs_text = "\n" + "\t".join(["#Seq1", "Seq2", "LCS for [%s]" %aa_bp_unit, "LCS for [%s]" %aa_bp_unit, "LCS color index for", "LCS color index rev"]) + "\n" - elif custom_shading: - lcs_text = "\n" + "\t".join(["#Seq1", "Seq2", "Custom matrix value", "Color index for", "Color index rev"]) + "\n" - - if verbose: - seq_text = "" - counter, seq_counter = 0, 0 - for idx in range(len(sequences)): - if verbose: - print "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]), - seq_text += "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]) - rec_two = seq_dict[sequences[idx]] - len_two = len(rec_two.seq) - name_two = rec_two.id - - for jdx in range(idx, len(sequences)): - rec_one = seq_dict[sequences[jdx]] - len_one = len(rec_one.seq) - name_one = rec_one.id - - counter += 1 - seq_counter += 1 - if verbose: - print sequences[jdx], - seq_text += " " + sequences[jdx] - elif not seq_counter % 25: - print seq_counter, - log_txt += str(seq_counter) - - # optional shade background according to length of LCS and/or user matrix - ######################################################################### - - # get interval based on LCS - background_colors = [None, None] - if lcs_shading and (lcs_shading_ref==1 or lcs_shading_ref==2 or max_lcs!=None): # self plot max_lcs_for == None - lcs_len = lcs_dict[(idx, jdx)] - l1 = lcs_len[0] # forward - l2 = lcs_len[1] # reverse complement - - lcs_shading_bool = True - - # calculate shading acc. to chosen option - if lcs_shading_ref == 1: # percentage of shorter sequence - color_idx0 = min(len(colors)-1, l1*lcs_shading_num // min(len_one, len_two)) - color_idx1 = min(len(colors)-1, l2*lcs_shading_num // min(len_one, len_two)) - elif lcs_shading_ref == 2: # by given interval size - color_idx0 = min(len(colors)-1, l1 // lcs_shading_interval_len) - color_idx1 = min(len(colors)-1, l2 // lcs_shading_interval_len) - if color_idx0 >= len(colors): - color_idx0 = len(colors) - if color_idx1 >= len(colors): - color_idx1 = len(colors) - else: # percentage of maximum lcs length - color_idx0 = min(len(colors)-1, l1*lcs_shading_num // max_lcs) - color_idx1 = min(len(colors)-1, l2*lcs_shading_num // max_lcs) - else: - lcs_shading_bool = False - - # get interval based on custom matrix - if custom_shading: - # matrix value - try: - custom_value = custom_similarity_dict[(idx, jdx)] - except: - custom_value = "" - - # bottom left triangle = LCS forward/reverse or best of both - if lcs_shading_bool: - if lcs_shading_ori == 0: # forward - color_idx1 = color_idx0 - elif lcs_shading_ori == 2: # both directions - color_idx1 = max(color_idx0, color_idx1) - - # top right triangle = custom value (not colored if text matrix provided) - if type(custom_value) == int or type(custom_value) == float: - color_idx0 = int((custom_value-custom_min)*lcs_shading_num // (custom_max-custom_min)) - # if string is proviced - else: - color_idx0 = 0 - - # set colors dependent on lcs dependent on orientation - if lcs_shading_bool and not custom_shading: - if idx != jdx: - if lcs_shading_ori == 0: - color_idx1 = color_idx0 - elif lcs_shading_ori == 1: - color_idx0 = color_idx1 - background_colors[0] = colors[color_idx0] - background_colors[1] = colors[color_idx1] - # for selfcomparison, only color reverse complement - elif lcs_shading_ori != 0 and not custom_shading: - background_colors[0] = colors[color_idx1] - # set different colors for shading by LCS + user matrix - elif lcs_shading_bool and custom_shading: - # print colors, background_colors, color_idx0, color_idx1 - background_colors[0] = colors_2[color_idx0] - background_colors[1] = colors[color_idx1] - # set grey color range for user matrix if no LCS shading - elif custom_shading: - background_colors[0] = colors[color_idx0] - background_colors[1] = colors[color_idx0] - - if verbose: - if custom_shading and lcs_shading_bool: - lcs_text += "\t".join([name_one, name_two, str(lcs_len[0]), str(lcs_len[1]), str(custom_value), str(color_idx0), str(color_idx1)]) + "\n" - elif lcs_shading_bool: - lcs_text += "\t".join([name_one, name_two, str(lcs_len[0]), str(lcs_len[1]), str(color_idx0), str(color_idx1)]) + "\n" - elif custom_shading: - lcs_text += "\t".join([name_one, name_two, str(custom_value), str(color_idx0), str(color_idx1)]) + "\n" - - # diagonal (self-dotplots) - if idx == jdx: - # skip positions below diagonal - counter = counter + (counter - 1) // (nrows) # + row_pos - counters = [counter] - # draw both graphs at once (due to symmetry) - else: - col_pos = (counter - 1) % ncols - row_pos = (counter - 1) // (nrows) - counter2 = col_pos * ncols + row_pos + 1 - counters = [counter, counter2] - - if len(counters) == 2: - seq_counter += 1 - if not verbose and not seq_counter % 25: - print seq_counter, - log_txt += str(seq_counter) - - x_lists, y_lists, x_lists_rc, y_lists_rc = data_dict[(idx, jdx)] - - # plot diagram(s) - for kdx in range(len(counters)): - - # shade annotated regions if gff file(s) provided - if idx == jdx and gff_files != None and gff_files != []: - if name_one in feat_dict.keys(): - features = feat_dict[name_one] - for item in features: - feat_type, start, stop = item - feat_color, strength, zoom = gff_color_dict[feat_type.lower()] - start = max(0, start - zoom - 0.5) - stop = min(length_seq+1, stop + zoom + 0.5) - width = stop - start - ax.add_patch(patches.Rectangle((start, start), # (x,y) - width, width, # width, height - edgecolor=None, linewidth=line_width+zoom, - fill=True, facecolor=feat_color, - alpha=strength)) - - # if custom matrix value printed into upper matrix triangle, skip data plotting - # text print in top triangle - if user_matrix_print and custom_shading and kdx==0 and idx!=jdx: - data_plotting = False - # dotplot in bottom triangle - else: - data_plotting = True - - fig_pos = counters[kdx] - # plotting subplot with matplotlib - ax = P.subplot(gs[fig_pos-1]) # rows, columns, plotnumber - - # mirror plot, if plotting below diagonal - if kdx == 0: - l1, l2 = len_one, len_two - n1, n2 = name_one, name_two - x1, y1 = x_lists, y_lists - x2, y2 = x_lists_rc, y_lists_rc - else: - l2, l1 = len_one, len_two - n2, n1 = name_one, name_two - x1, y1 = y_lists, x_lists - x2, y2 = y_lists_rc, x_lists_rc - - if data_plotting: - # collect lines - lines = [] - color_list = [] - for (x_lines, y_lines, col) in [(x2, y2, line_col_rev), (x1, y1, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # plot value provided by customer instead of dotplot - else: - alignment = {'horizontalalignment': 'center', 'verticalalignment': 'center'} - # P.text(0.5, 0.5, custom_value, size='medium', transform=ax.transAxes, **alignment) - P.text(0.5, 0.5, custom_value, size=label_size*1.5, transform=ax.transAxes, **alignment) - # P.text(0.5, 0.5, custom_value, size=label_size*1.5, transform=ax.transAxes, - # horizontalalignment='center', verticalalignment='center', color="black") - - if custom_shading: - # omit diagonal - if idx == jdx: - ax.set_facecolor("white") - # use white background for text fields (top right triangle only [kdx 0]) - elif type(custom_value) != int and type(custom_value) != float and kdx == 0: - ax.set_facecolor("white") - else: - ax.set_facecolor(background_colors[kdx]) - # set background color if lcs shading - elif lcs_shading_bool and background_colors[kdx] != None: - ax.set_facecolor(background_colors[kdx]) - - # set axis limits - P.xlim(0, l1+1) - P.ylim(l2+1, 0) # rotate y axis (point downwards) - - # determine axis positions - if x_label_pos_top: - ax.xaxis.tick_top() - ax.xaxis.set_label_position('top') - x_label_bool = fig_pos <= ncols - x_tick_bool = fig_pos > ncols*(ncols-1) - else: - x_label_bool = fig_pos > ncols*(ncols-1) - x_tick_bool = fig_pos <= ncols - - # x axis labels dependent on plot position/number - if x_label_bool: # x title and labels on top or bottom - P.xlabel(unicode_name(shorten_name(n1, max_len=title_length, title_selectpos=title_selectpos)), fontsize=label_size, rotation=x_label_rotation, verticalalignment=xvalign, horizontalalignment=xhalign, fontweight='bold', labelpad=8) # axis naming - if not x_label_rotation in ["horizontal", "vertical"]: - P.setp(ax.get_xticklabels(), fontsize=label_size*.9, rotation="vertical") - else: - P.setp(ax.get_xticklabels(), fontsize=label_size*.9, rotation=x_label_rotation) - elif x_tick_bool and x_label_pos_top: # x ticks on bottom row - ax.xaxis.tick_bottom() # ticks without labels on bottom - P.setp(ax.get_xticklabels(), fontsize=label_size, rotation=x_label_rotation, visible=False) - elif x_tick_bool: # x ticks on top row - ax.xaxis.tick_top() # # ticks without labels on top - P.setp(ax.get_xticklabels(), fontsize=label_size, rotation=x_label_rotation, visible=False) # inner diagrams without labelling - else: # no x ticks on internal rows - ax.axes.get_xaxis().set_visible(False) - - # y axis labels dependent on plot position/number - if fig_pos % ncols == 1 or (ncols == 1 and nrows == 1): # y title and labels in 1st column - P.ylabel(unicode_name(shorten_name(n2, max_len=title_length, title_selectpos=title_selectpos)), fontsize=label_size, rotation=y_label_rotation, verticalalignment=yvalign, horizontalalignment=yhalign, fontweight='bold', labelpad=8) - P.setp(ax.get_yticklabels(), fontsize=label_size*.9) # axis naming - elif fig_pos % ncols == 0: # y ticks in last column - ax.yaxis.tick_right() - P.setp(ax.get_yticklabels(), visible=False) # inner diagrams without labelling - else: - ax.axes.get_yaxis().set_visible(False) - - if not verbose: - print seq_counter, "done" - log_txt += str(seq_counter) + " done" - else: - print "\n%d done" % seq_counter - log_txt += "\n%d done" % seq_counter - logprint(log_txt, start=False, printing=False) - - if verbose: - try: - logprint(lcs_text, start=False, printing=True) - except: - pass - - # finalize layout - margins & spacing between plots - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - # gs.tight_layout(fig, h_pad=.02, w_pad=.02) # less overlapping tick labels, but also disturbingly large spacing - if y_label_rotation == "horizontal": - if x_label_pos_top: - P.subplots_adjust(hspace=spacing, wspace=spacing, left=0.13, top=0.87) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=spacing, wspace=spacing, left=0.13, bottom=0.13) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=spacing, wspace=spacing) # space between rows - def 0.4 - - # save figure and close instance - fig_name = '%s%s_wordsize%i%s.%s' % (prefix, name_graph, wordsize, suffix, filetype) - P.savefig(fig_name) - P.close() - P.cla() - - - # create figure color legend - if lcs_shading: - if lcs_shading_ref == 1: # percentage of shorter sequence - legend_file_name = legend_figure(colors, lcs_shading_num, unit="%", filetype=filetype, prefix=prefix) - elif lcs_shading_ref == 2: # interval sizes - legend_file_name = legend_figure(colors, lcs_shading_num, unit=aa_bp_unit, filetype=filetype, prefix=prefix, bins=color_bins) - else: # relative of maximum lcs - legend_file_name = legend_figure(colors, lcs_shading_num, unit=aa_bp_unit, filetype=filetype, prefix=prefix, max_lcs_len=max_lcs) - - if custom_shading: - custom_prefix = "custom-matrix-" + prefix - legend_file_name_custom = legend_figure(colors_2, lcs_shading_num, unit="%", filetype=filetype, prefix=custom_prefix, max_lcs_len=custom_max, min_lcs_len=custom_min) - - if lcs_shading and custom_shading: - return [fig_name, legend_file_name, legend_file_name_custom] - elif lcs_shading: - return [fig_name, legend_file_name] - elif custom_shading: - return [fig_name, legend_file_name_custom] - else: - return [fig_name] - - -############################### -# Function Call # -############################### - -def main(seq_list, wordsize, modes=[0, 1, 2], prefix=None, plot_size=10, label_size=10, filetype="png", type_nuc=True, convert_wobbles=False, substitution_count=0, rc_option=True, alphabetic_sorting=False, gff=None, multi=True, ncols=1, nrows=1, lcs_shading=True, lcs_shading_num=5, lcs_shading_ref=0, lcs_shading_interval_len=100, lcs_shading_ori=0, gff_color_config_file="", input_user_matrix_file="", user_matrix_print=False, length_scaling=True, title_length=50, title_selectpos="B", spacing=0.04, verbose=False): - - global t1, line_col_rev - - # read gff color config file if provided - if len(input_gff_files) != 0 and input_gff_files != None: - if gff_color_config_file not in ["", None]: - text = "\n%s\n\nReading GFF color configuration file\n%s\n\n=> %s\n" % (50*"=", 28*"-", gff_color_config_file) - logprint(text, start=False, printing=True) - gff_feat_colors = read_gff_color_config(gff_color_config_file) - else: - gff_feat_colors = {} - if gff_color_config_file not in ["", None]: - text = "Please provide GFF annotation files to use configuration file", gff_color_config_file - logprint(text, start=False, printing=True) - - # if color is set to white, reverse complementary matches are skipped - if not rc_option: - line_col_rev = "white" # reverse matches not calculated - elif not type_nuc: - logprint("Reverse complement deactivated for proteins!") - line_col_rev = "white" # reverse matches not calculated - - mode_text = [] - for item in modes: - mode_text.append(str(item)) - text = "%s\n\nRunning plotting modes %s" % (50*"=", ", ".join(mode_text)) - logprint(text, start=False, printing=True) - - - # create dotplots - ########################################## - - # self dotplots - t1 = time.time() - if 0 in modes: - list_of_png_names = selfdotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, title_selectpos=title_selectpos, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, multi=multi, ncols=ncols, nrows=nrows, gff_files=gff, gff_color_dict=gff_feat_colors, verbose=verbose) - t1 = time_track(t1) - if list_of_png_names != [] and list_of_png_names != None: - text = "-> Image file(s): %s\n" % ", ".join(list_of_png_names) - else: - text = "No image files were created!\n" - logprint(text, start=False, printing=True) - logprint(50*"=") - - # paired dotplots - if 1 in modes: - if multi: - list_of_png_names = pairdotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, title_selectpos=title_selectpos, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, multi=multi, ncols=ncols, nrows=nrows, length_scaling=length_scaling, verbose=verbose) - t1 = time_track(t1) - else: - if not length_scaling: - text = "\nPairwise dotplot with individual output files scaled by sequence length automatically!" - logprint(text, start=False, printing=True) - list_of_png_names = pairdotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, title_selectpos=title_selectpos, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, multi=multi, ncols=ncols, nrows=nrows, length_scaling=True, verbose=verbose) - t1 = time_track(t1) - if list_of_png_names != [] and list_of_png_names != None: - text = "-> Image file(s): %s\n" % ", ".join(list_of_png_names) - else: - text = "No image files were created!\n" - logprint(text, start=False, printing=True) - logprint(50*"=") - - # all-against-all dotplot - if 2 in modes: - list_of_png_names = polydotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, title_selectpos=title_selectpos, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, lcs_shading=lcs_shading, lcs_shading_num=lcs_shading_num, lcs_shading_ref=lcs_shading_ref, lcs_shading_interval_len=lcs_shading_interval_len, lcs_shading_ori=lcs_shading_ori, input_user_matrix_file=input_user_matrix_file, user_matrix_print=user_matrix_print, spacing=spacing, verbose=verbose) - t1 = time_track(t1) - if list_of_png_names != [] and list_of_png_names != None: - text = "-> Image file(s): %s\n" % ", ".join(list_of_png_names) - else: - text = "No image files were created!\n" - logprint(text, start=False, printing=True) - logprint(50*"=") - - text = "\n" + 50 * "#" + "\n" + 50 * "#" - text += "\n\nThank you for using FlexiDot!\n" - logprint(text, start=False, printing=True) - -# testing mode for debugging -trial_mode = False -# trial_mode = True - -# parameters = check_input(sys.argv) -parameters = check_input(sys.argv, trial_mode=trial_mode) - -# read out parameters -commandline, auto_fas, input_fasta, output_file_prefix, collage_output, m_col, n_row, filetype, type_nuc, input_gff_files, gff_color_config_file, wordsize, plotting_modes, wobble_conversion, substitution_count, rc_option, alphabetic_sorting, lcs_shading, lcs_shading_num, lcs_shading_ref, lcs_shading_interval_len, lcs_shading_ori, input_user_matrix_file, user_matrix_print, plot_size, line_width, line_col_for, line_col_rev, x_label_pos_top, label_size, spacing, length_scaling, title_length, title_selectpos, verbose = parameters - -# evtl. overwrite parameters for testing purposes in trial mode -if trial_mode: - # input_user_matrix_file = "AngioSINE-v18-alignment-identities.csv" - input_fasta = ["test-sequences-9-Ns.fas"] - input_fasta = ["Beta_SINEs__select_consensus.fas"] - # input_user_matrix_file = "Beta_SINEs__select_consensus_matrix.txt" - # input_user_matrix_file = "Beta_SINEs__select_consensus_matrix-01.txt" - # input_user_matrix_file = "Beta_SINEs__select_consensus_matrix-comma-str.txt" - # input_user_matrix_file = "Beta_SINEs__select_consensus_matrix-100+.txt" - # user_matrix_print = True - output_file_prefix = "SINEmatrix" - output_file_prefix = "SINEmatrix-NoShading" - plot_size = 10 - plotting_modes = [0,1,2] - plotting_modes = [2] - lcs_shading = False - lcs_shading = True - lcs_shading_ref = 2 - lcs_shading_num = 4 - lcs_shading_ori = 0 - lcs_shading_interval_len = 15 - wordsize = 10 - wordsize = 7 - x_label_pos_top = True - filetype = "pdf" - filetype = "png" - - wobble_conversion = False - wobble_conversion = True - - substitution_count = 0 - - rc_option = True - rc_option = False - label_size = 10 - - verbose = False - verbose = True - -if auto_fas: - path = os.path.dirname(os.path.abspath(__file__)) - files_long = glob.glob(path+"/*.fasta") - files_long.extend(glob.glob(path+"/*.fas")) - files_long.extend(glob.glob(path+"/*.fa")) - files_long.extend(glob.glob(path+"/*.fna")) - input_fasta = [] - for i in files_long: - if not "combined" in i: - filename = i[i.rfind('\\')+1:] - input_fasta.append(filename) - -if trial_mode: - # start logging file - logprint(commandline, start=True, printing=False, prefix=output_file_prefix) - -main(input_fasta, wordsize, modes=plotting_modes, prefix=output_file_prefix, plot_size=plot_size, label_size=label_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=wobble_conversion, substitution_count=substitution_count, rc_option=rc_option, gff=input_gff_files, multi=collage_output, ncols=m_col, nrows=n_row, alphabetic_sorting=alphabetic_sorting, lcs_shading=lcs_shading, lcs_shading_num=lcs_shading_num, lcs_shading_ref=lcs_shading_ref, lcs_shading_interval_len=lcs_shading_interval_len, lcs_shading_ori=lcs_shading_ori, gff_color_config_file=gff_color_config_file, input_user_matrix_file=input_user_matrix_file, user_matrix_print=user_matrix_print, length_scaling=length_scaling, title_length=title_length, title_selectpos=title_selectpos, spacing=spacing, verbose=verbose) - - diff --git a/code/flexidot_v1.03.py b/code/flexidot_v1.03.py deleted file mode 100644 index 867ce99..0000000 --- a/code/flexidot_v1.03.py +++ /dev/null @@ -1,3161 +0,0 @@ -#!/usr/bin/python2.7 -# -*- coding: utf-8 -*- - -""" -FlexiDot: Highly customizable ambiguity-aware dotplots for visual sequence investigation - -Kathrin M. Seibt, Thomas Schmidt and Tony Heitkam -Institute of Botany, TU Dresden, Dresden, 01277, Germany - -(Bioinformatics, 2018, doi 10.1093/bioinformatics/bty395) -""" - - -############################### -# Requirements # -############################### - -# import system modules -import os, glob -import time, datetime -import sys -import shutil, getopt -import unicodedata - -def module_install_command(module_name, upgrade=False): - """ - create installation commands for Python modules and print information - """ - if upgrade: - load_command = "python -m pip install --upgrade %s" % module_name - else: - load_command = "python -m pip install %s" % module_name - - try: - logprint("Installing Python module: %s\n\t%s\n" % (module_name, load_command)) - except: - print "Installing Python module: %s\n\t%s\n" % (module_name, load_command) - - return load_command - -def load_modules(): - """ - load Python modules, if possible - otherwise try to install them - """ - - # make module names global - global cllct, gridspec, patches, rcParams, mplrc, P, Color, SeqIO, np, ccv, mcolors, rgb2hex, regex - - # matplotlib - try: - import matplotlib.collections as cllct - except: - command = module_install_command("matplotlib", upgrade=True) - try: - os.system(command) - print "\n" - import matplotlib.collections as cllct - except: - print "Please install module matplotlib manually" - from matplotlib.colors import colorConverter as ccv - import matplotlib.colors as mcolors - import matplotlib.gridspec as gridspec - import matplotlib.patches as patches - import pylab as P - - # specify matplotlib font settings - from matplotlib import rc as mplrc - mplrc('pdf', fonttype=42, compression=0) - from matplotlib import rcParams - rcParams['font.family'] = 'sans-serif' - rcParams['font.sans-serif'] = ['Helvetica', 'Verdana', 'Tahoma', ] - - # colour for color gradient palette - try: - from colour import Color - except: - command = module_install_command("colour") - try: - os.system(command) - print "\n" - from colour import Color - except: - print "Please install module colour manually" - - # color converter - try: - from colormap import rgb2hex - except: - command = module_install_command("colormap") - # additional module easydev.tools required by colormap - command2 = module_install_command("easydev") - try: - os.system(command) - os.system(command2) - print "\n" - from colormap import rgb2hex - except: - print "Please install module colormap manually" - - # biopython - try: - from Bio import SeqIO - except: - command = module_install_command("biopython") - try: - os.system(command) - print "\n" - from Bio import SeqIO - except: - print "Please install module biopython manually" - - # numpy - try: - import numpy as np - except: - command = module_install_command("numpy") - try: - os.system(command) - print "\n" - import numpy as np - except: - print "Please install module numpy manually" - - # regex for pattern matching - try: - import regex - except: - command = module_install_command("regex") - try: - os.system(command) - print "\n" - import regex - except: - print "Please install module regex manually" - -load_modules() - - -############################### -# Usage & Input # -############################### - -def usage(): - """ - usage and help - """ - - print """\n\n FLEXIDOT - ------------------------------------------------------------------- - - Version: - 1.03 - - Citation: - Kathrin M. Seibt, Thomas Schmidt, Tony Heitkam (2018) - "FlexiDot: Highly customizable ambiguity-aware dotplots for visual sequence investigation" - Bioinformatics, doi: 10.1093/bioinformatics/bty395 - - - General usage: - $ python flexidot.py -a [ARGUMENTS] - $ python flexidot.py -i [ARGUMENTS] - - - ARGUMENTS - ------------------------------------------------------------------- - - - INPUT/OUTPUT OPTIONS... required are [-a] OR [-i] - - -a, --auto_fas Imports all fasta files from current directory (*.fasta, *.fas, *.fa, *.fna) - -i is not needed, if -a is activated - [inactive by default] - - -i, --in_file Input fasta file (fasta file name or comma-separated file list) - > Provide multiple files: Recall -i or provide comma-separated file names - - -o, --output_file_prefix File prefix to be added to the generated filenames [default = NONE] - - -c, --collage_output Multiple dotplots are combined in a collage - Y or 1 = ON [default] - N or 0 = OFF - - -m, --m_col Number of columns per page [default = 4] (only if --collage_output is ON) - - -n, --n_row Number of rows per page [default = 5] (only if --collage_output is ON) - - -f, --filetype Output file format - 0 = PNG [default] - 1 = PDF - 2 = SVG - - -s, --alphabetic_sorting Sort sequences alphabetically according to titles - Y or 1 = ON - N or 0 = OFF [default] - - - CALCULATION PARAMETERS... - - -k, --wordsize Wordsize (kmer length) for dotplot comparison [default = 7] - - -p, --plotting_mode Mode of FlexiDot dotplotting - 0 = self [default] - 1 = paired - 2 = poly (matrix with all-against-all dotplots) - > Run multiple plotting modes: Recall -p or provide comma-separated numbers - - -t, --type_nuc Type of residue is nucleotide - Y or 1 = nucleotide [default] - N or 0 = amino acid - - -w, --wobble_conversion Ambiguity handling for relaxed matching - Y or 1 = ON - N or 0 = OFF [default] - - -S, --substitution_count Number of substitutions (mismatches) allowed per window for relaxed matching - [default = 0] - - -r, --rc_option Find reverse complementary matches (only if type_nuc=y) - Y or 1 = ON [default] - N or 0 = OFF - - - GRAPHIC FORMATTING... - - -A, --line_width Line width [default = 1] - - -B, --line_col_for Line color [default = black] - - -C, --line_col_rev Reverse line color [default = green] - - -D, --x_label_pos Position of the X-label - Y or 1 = top [default] - N or 0 = bottom - - -E, --label_size Font size [default = 10] - - -F, --spacing Spacing between all-against-all dotplots (only if --plotting_mode=2) - [default = 0.04] - - -P, --plot_size Plotsize [default = 10] - - -L, --length_scaling Scale plot size for pairwise comparison (only if --plotting_mode=1) - Y or 1 = Scaling ON (axes scaled according to sequence length) - N or 0 = Scaling OFF (squared plots) [default] - - -T, --title_length Limit title length for dotplot comparisons - [default = 20] - Position of selection can be specified by appending a letter (e.g. -T 20E) - B = beginning [default] - E = end - - - GFF SHADING (for -p/--plotting_mode=0,2 only)... - - -g, --input_gff_files GFF3 file used for markup in self-dotplots - (provide multiple files: Recall -g or provide comma-separated file names) - - -G, --gff_color_config_file Tab-delimited config file for custom gff shading - column 1: feature type - column 2: color - column 3: alpha - column 4: zoom factor (for small regions) - - - LCS SHADING OPTIONS (for -p/--plotting_mode=2 only)... - - -x, --lcs_shading Shade subdotplot based on the length of the longest common substring (LCS) - Y or 1 = ON - N or 0 = OFF [default] - - -X, --lcs_shading_num Number of shading intervals (hues) for LCS (-x) and user matrix shading (-u) - [default = 5] - - -y, --lcs_shading_ref Reference for LCS shading - 0 = maximal LCS length [default] - 1 = maximally possible length (length of shorter sequence in pairwise comparison) - 2 = given interval sizes - DNA [default 100 bp] or proteins [default 10 aa] - see -Y - - -Y, --lcs_shading_interval_len Length of intervals for LCS shading (only if --lcs_shading_ref=2) - [default for nucleotides = 50; default for amino acids = 10] - - -z, --lcs_shading_ori Shade subdotplots according to LCS on - 0 = forward [default], - 1 = reverse, or - 2 = both strands (forward shading above diagonal, reverse shading on diagonal and below; - if using --input_user_matrix_file, best LCS is used below diagonal) - - - CUSTOM USER MATRIX SHADING OPTIONS (for -p/--plotting_mode=2 only)... - - -u, --input_user_matrix_file Shading above diagonal according to values in matrix file specified by the user - (tab-delimited or comma-separated matrix with sequence name in column 1 and numbers in columns 2-n - e.g. identity matrix from multiple sequence alignment - strings are ignored) - - -U, --user_matrix_print Display provided matrix entries in the fields above diagonal of all-against-all dotplot - Y or 1 = ON - N or 0 = OFF [default] - - - OTHERS... - - -h, --help Help screen - - -v, --verbose Verbose - - - - - """ - -def check_input(argv, trial_mode=False): - """ - commandline argument parsing - """ - - global log_txt, aa_bp_unit - - # helpers for argument parsing - ###################################### - - arguments = ["-a", "--auto_fas", "a", "auto_fas", - "-i", "--input_fasta", "i:", "input_fasta=", - "-o", "--output_file_prefix", "o:", "output_file_prefix=", - "-c", "--collage_output", "c:", "collage_output=", - "-m", "--m_col", "m:", "m_col=", - "-n", "--n_row", "n:", "n_row=", - "-f", "--filetype", "f:", "filetype=", - "-t", "--type_nuc", "t:", "type_nuc=", - "-g", "--input_gff_files", "g:", "input_gff_files", - "-G", "--gff_color_config_file", "G:", "gff_color_config_file", - "-k", "--wordsize", "k:", "wordsize=", - "-p", "--plotting_mode", "p:", "plotting_mode=", - "-w", "--wobble_conversion", "w:", "wobble_conversion=", - "-S", "--substitution_count", "S:", "substitution_count=", - "-r", "--rc_option", "r:", "rc_option=", - "-s", "--alphabetic_sorting", "s:", "alphabetic_sorting=", - "-x", "--lcs_shading", "x:", "lcs_shading=", - "-X", "--lcs_shading_num", "X:", "lcs_shading_num=", - "-y", "--lcs_shading_ref", "y:", "lcs_shading_ref=", - "-Y", "--lcs_shading_interval_len", "Y:", "lcs_shading_interval_len=", - "-z", "--lcs_shading_ori", "z:", "lcs_shading_ori=", - "-u", "--input_user_matrix_file", "u:", "input_user_matrix_file=", - "-U", "--user_matrix_print", "U:", "user_matrix_print=", - "-P", "--plot_size", "P:", "plot_size=", - "-A", "--line_width", "A:", "line_width=", - "-B", "--line_col_for", "B:", "line_col_for=", - "-C", "--line_col_rev", "C:", "line_col_rev=", - "-D", "--x_label_pos", "D:", "x_label_pos=", - "-E", "--label_size", "E:", "label_size=", - "-F", "--spacing", "F:", "spacing=", - "-L", "--length_scaling", "L:", "length_scaling=", - "-T", "--title_length", "T:", "title_length=", - "-h", "--help", "h", "help", - "-v", "--verbose", "v", "verbose"] - - arguments_sysargv = tuple(arguments[0::4] + arguments[1::4]) - arguments_opts = "".join(arguments[2::4]) - arguments_args = arguments[3::4] - - - # setting defaults - ###################################### - - auto_fas = False # 0 - input_fasta = [] - output_file_prefix = None - collage_output = True # 1 - m_col = 4 - n_row = 5 - filetype = 0 - type_nuc = True - input_gff_files = [] - gff_color_config_file = "" - - wordsize = 7 - plotting_modes = [0] - wobble_conversion = False # 0 - substitution_count = 0 - rc_option = True # 1 - alphabetic_sorting = False # 0 - - lcs_shading = False # 0 - lcs_shading_num = 4 - lcs_shading_ref = 0 - lcs_shading_interval_len = 50 # interval default changes to "10" for amino acids [type_nuc = n] - lcs_shading_ori = 0 - - input_user_matrix_file = "" - user_matrix_print = False - - plot_size = 10 - line_width = 1 - line_col_for = "black" - line_col_rev = "#009243" - x_label_pos = True # 0 - label_size = 10 - spacing = 0.04 - length_scaling = False # 0 - title_length = 20 # float("Inf") - title_clip_pos = "B" # B (begin), E (end) - max_N_percentage = 49 # fixed value, no user input - - aa_bp_unit = "bp" - - verbose = False # 0 - - filetype_dict = {0: "png", 1: "pdf", 2: "svg"} - lcs_shading_ref_dict = {0: "maximal LCS length", 1: "maximally possible length", 2: "given interval sizes"} - plotting_mode_dict = {0: "self", 1: "paired", 2: "all-against-all"} - lcs_shading_ori_dict = {0: "forward", 1: "reverse complement", 2: "both"} - - # return default parameters for testing purposes - if trial_mode: - print "ATTENTION: YOU ARE IN THE TRIAL MODE!!!\n\n" - - commandline = "trial_mode\n" - - parameters = [commandline, auto_fas, input_fasta, output_file_prefix, collage_output, m_col, n_row, filetype_dict[filetype], type_nuc, input_gff_files, gff_color_config_file, wordsize, plotting_modes, wobble_conversion, substitution_count, rc_option, alphabetic_sorting, lcs_shading, lcs_shading_num, lcs_shading_ref, lcs_shading_interval_len, lcs_shading_ori, input_user_matrix_file, user_matrix_print, plot_size, line_width, line_col_for, line_col_rev, x_label_pos, label_size, spacing, length_scaling, title_length, title_clip_pos, max_N_percentage, verbose] - return parameters - - - # read arguments - ###################################### - - commandline = "" - for arg in sys.argv: - commandline += arg + " " - - log_txt = "\n...reading input arguments..." - print log_txt - - if len(sys.argv) < 2: - print "\nERROR: More arguments are needed. Exit..." - log_txt += "\nERROR: More arguments are needed. Exit..." - usage() - sys.exit() - - elif sys.argv[1] not in arguments_sysargv: - print "\nINPUT ERROR: Input argument %s unknown. Please check the help screen." % sys.argv[1] - log_txt += "\nINPUT ERROR: Input argument %s unknown. Please check the help screen." % sys.argv[1] - # usage() - sys.exit() - - try: - opts, args = getopt.getopt(sys.argv[1:], arguments_opts, arguments_args) - - except getopt.GetoptError: - print "\nINPUT ERROR (getopt): Input argument %s unknown. Please check the help screen." % sys.argv[1:] - log_txt += "\nINPUT ERROR (getopt): Input argument %s unknown. Please check the help screen." % sys.argv[1:] - # usage() - sys.exit() - - for opt, arg in opts: - - if opt in ("-h", "--help"): - print "...fetch help screen" - log_txt += "\n...fetch help screen" - usage(), sys.exit() - - if opt in ("-v", "--verbose"): - print "...verbose output" - log_txt += "\n...verbose output" - verbose = True - - elif opt in ("-i", "--input_fasta"): - if "," in arg: - arg_list = arg.split(",") - for temp_file in arg_list: - if not os.path.exists(str(temp_file)): - message = "\nERROR: fasta_file '%s' was not found!" % str(temp_file) - sys.exit(message) - else: - input_fasta.append(str(temp_file)) - print "fasta file #%i: %s" % (len(input_fasta), str(temp_file)) - log_txt += "\nfasta file #%i: %s" % (len(input_fasta), str(temp_file)) - else: - if not os.path.exists(str(arg)): - message = "\nERROR: fasta_file '%s' was not found!" % str(arg) - log_txt += message - sys.exit(message) - else: - input_fasta.append(str(arg)) - print "fasta file #%i: %s" % (len(input_fasta), str(arg)) - log_txt += "\nfasta file #%i: %s" % (len(input_fasta), str(arg)) - - - elif opt in ("-a", "--auto_fas"): - auto_fas = True - - - # multiple gff files: reads them into a list - elif opt in ("-g", "--input_gff_files"): - - # append gff file only if existing - if "," in arg: - arg_list = arg.split(",") - for temp_file in arg_list: - if not os.path.exists(str(temp_file)): - message = "\nERROR: gff_file '%s' was not found!" % str(temp_file) - print message - log_txt += message - print " -->Running FlexiDot without this gff file!" - log_txt += "\n -->Running FlexiDot without this gff file!" - else: - print "GFF file #%i: %s" %(len(input_gff_files), str(temp_file)) - log_txt += "\nGFF file #%i: %s" %(len(input_gff_files), str(temp_file)) - input_gff_files.append(str(temp_file)) - else: - if not os.path.exists(str(arg)): - message = "\nERROR: gff_file '%s' was not found!" % str(arg) - print message - log_txt += message - print " -->Running FlexiDot without this gff file!" - log_txt += "\n -->Running FlexiDot without this gff file!" - else: - input_gff_files.append(str(arg)) - print "GFF file #%i: %s" %(len(input_gff_files), str(arg)) - log_txt += "\nGFF file #%i: %s" %(len(input_gff_files), str(arg)) - - - elif opt in ("-G", "--gff_color_config_file"): - if not os.path.exists(str(arg)): - message = "\nERROR: gff_color_config_file '%s' was not found!" % str(arg) - print message + "\n -->Running FlexiDot with default gff coloring specification!" - log_txt += message + "\n -->Running FlexiDot with default gff coloring specification!" - else: - gff_color_config_file = str(arg) - - - elif opt in ("-u", "--input_user_matrix_file"): - if not os.path.exists(str(arg)): - message = "\nERROR: input_user_matrix_file '%s' was not found!" % str(arg) - print message + "\n -->Running FlexiDot without input_user_matrix_file %s!" % arg - log_txt += message + "\n -->Running FlexiDot withdefault matrix shading file!" - else: - input_user_matrix_file = str(arg) - - elif opt in ("-U", "--user_matrix_print"): - user_matrix_print = check_bools(str(arg), default=user_matrix_print) - - elif opt in ("-o", "--output_file_prefix"): - output_file_prefix = arg - - elif opt in ("-c", "--collage_output"): - collage_output = check_bools(str(arg), default=collage_output) - - elif opt in ("-m", "--m_col"): - try: m_col = int(arg) - except: - print "m_col - invalid argument - using default value" - log_txt += "\nm_col - invalid argument - using default value" - - elif opt in ("-n", "--n_row"): - try: n_row = int(arg) - except: - print "n_row - invalid argument - using default value" - log_txt += "\nn_row - invalid argument - using default value" - - elif opt in ("-f", "--filetype"): - if 0 <= int(arg) <= 2: - filetype = int(arg) - else: - print "\nERROR: Please provide valid filetype argument. %s is out of range. It will be set to -f 0 [default]." %(filetype) - log_txt += "\nERROR: Please provide valid filetype argument. %s is out of range. It will be set to -f 0 [default]." %(filetype) - - elif opt in ("-t", "--type_nuc"): - type_nuc = check_bools(str(arg), default=type_nuc) - - if type_nuc == False: - # interval default changed for amino acids - lcs_shading_interval_len = 10 - aa_bp_unit = "aa" - - elif opt in ("-k", "--wordsize"): - try: wordsize = int(arg) - except: - print "wordsize - invalid argument - using default value" - log_txt += "\nwordsize - invalid argument - using default value" - - elif opt in ("-p", "--plotting_mode"): - if "," in arg: - temp_modes = arg.split(",") - for item in temp_modes: - if item in ["0","1","2"]: - plotting_modes.append(int(item)) - elif arg in ["0","1","2"]: - plotting_modes = [int(arg)] - else: - print "Please provide valid plotting_modes argument - e.g. 1 or 0,1,2 - using default [0]" - log_txt += "\nPlease provide valid plotting_modes argument - e.g. 1 or 0,1,2 - using default [0]" - - elif opt in ("-w", "--wobble_conversion"): - wobble_conversion = check_bools(str(arg), default=wobble_conversion) - - elif opt in ("-S", "--substitution_count"): - try: substitution_count = int(arg) - except: - print "substitution_count - invalid argument - using default value" - log_txt += "\nsubstitution_count - invalid argument - using default value" - - elif opt in ("-r", "--rc_option"): - rc_option = check_bools(str(arg), default=rc_option) - - elif opt in ("-s", "--alphabetic_sorting"): - alphabetic_sorting = check_bools(str(arg), default=alphabetic_sorting) - - elif opt in ("-x", "--lcs_shading"): - lcs_shading = check_bools(str(arg), default=lcs_shading) - - elif opt in ("-X", "--lcs_shading_num"): - try: lcs_shading_num = int(arg) - 1 - except: - print "lcs_shading_num - invalid argument - using default value" - log_txt += "\nlcs_shading_num - invalid argument - using default value" - - elif opt in ("-y", "--lcs_shading_ref"): - try: - if 0 <= int(arg) <= 2: - lcs_shading_ref = int(arg) - else: - print "\nERROR: lcs_shading_ref %s out of range. It will be set to -y 0 [default]." %(lcs_shading_ref) - log_txt += "\nERROR: lcs_shading_ref %s out of range. It will be set to -y 0 [default]." %(lcs_shading_ref) - except: - print "lcs_shading_ref - invalid argument - using default value" - log_txt += "\nlcs_shading_ref - invalid argument - using default value" - - elif opt in ("-Y", "--lcs_shading_interval_len"): - try: lcs_shading_interval_len = int(arg) - except: - print "lcs_shading_interval_len - invalid argument - using default value" - log_txt += "\nlcs_shading_interval_len - invalid argument - using default value" - - elif opt in ("-z", "--lcs_shading_ori"): - if 0 <= int(arg) <= 2: - lcs_shading_ori = int(arg) - else: - print "\nERROR: Please provide valid lcs_shading_ori argument. %s is out of range. It will be set to -z 0 [default]." %(lcs_shading_ori) - log_txt += "\nERROR: Please provide valid lcs_shading_ori argument. %s is out of range. It will be set to -z 0 [default]." %(lcs_shading_ori) - - elif opt in ("-P", "--plot_size"): - try: plot_size = float(arg) - except: - print "plot_size - invalid argument - using default value" - log_txt += "\nplot_size - invalid argument - using default value" - - - elif opt in ("-A", "--line_width"): - try: line_width = float(arg) - except: - print "line_width - invalid argument - using default value" - log_txt += "\nline_width - invalid argument - using default value" - - elif opt in ("-B", "--line_col_for"): - if mcolors.is_color_like(arg): - line_col_for = arg - else: - print "line_col_for - invalid argument - using default value" - log_txt += "\nline_col_for - invalid argument - using default value" - - elif opt in ("-C", "--line_col_rev"): - if mcolors.is_color_like(arg): - line_col_rev = arg - else: - print "line_col_rev - invalid argument - using default value" - log_txt += "\nline_col_rev - invalid argument - using default value" - - elif opt in ("-D", "--x_label_pos"): - x_label_pos = check_bools(str(arg), default=x_label_pos) - - elif opt in ("-E", "--label_size"): - try: label_size = float(arg) - except: - print "label_size - invalid argument - using default value" - log_txt += "\nlabel_size - invalid argument - using default value" - - elif opt in ("-F", "--spacing"): - try: spacing = float(arg) - except: - print "spacing - invalid argument - using default value" - log_txt += "\nspacing - invalid argument - using default value" - - elif opt in ("-L", "--length_scaling"): - length_scaling = check_bools(str(arg), default=length_scaling) - - elif opt in ("-T", "--title_length"): - try: title_length = int(arg) - except: - try: - title_length = int(str(arg)[:-1]) - if arg[-1].upper() in ["B", "E"]: # B (beginning), E (end) - title_clip_pos = arg[-1].upper() - else: - print "title_length position information invalid - using default value" - log_txt += "\ntitle_length position information invalid - using default value" - except: - print "title_length - invalid argument - using default value" - log_txt += "\ntitle_length - invalid argument - using default value" - - # start logging file - logprint(commandline, start=True, printing=False, prefix=output_file_prefix) - logprint(log_txt, start=False, printing=False) - - - # print chosen arguments - ###################################### - - text = "\n%s\n" % (70 * "-") - text += "\n" + "INPUT/OUTPUT OPTIONS...\n" - text += "\n" + "Input fasta file: " + ", ".join(input_fasta) - text += "\n" + "Automatic fasta collection from current directory: " + str(auto_fas) - text += "\n" + "Collage output: " + str(collage_output) - text += "\n" + "Number of columns per page: " + str(m_col) - text += "\n" + "Number of rows per page: " + str(n_row) - text += "\n" + "File format: " + filetype_dict[filetype] - text += "\n" + "Residue type is nucleotide: " + str(type_nuc) - - text += "\n" + "\n\nCALCULATION PARAMETERS...\n" - text += "\n" + "Wordsize: " + str(wordsize) - text += "\n" + "Plotting mode: " + str(plotting_modes).replace("[", "").replace("]", "") + "\n" + 51 * " " - for item in plotting_modes: - text += plotting_mode_dict[item] + " " - text += "\n" + "Ambiguity handling: " + str(wobble_conversion) - text += "\n" + "Reverse complement scanning: " + str(rc_option) - text += "\n" + "Alphabetic sorting: " + str(alphabetic_sorting) - - if 0 in plotting_modes and input_gff_files != []: - text += "\n" + "Input gff files: " + ", ".join(input_gff_files) - if gff_color_config_file != "": - text += "\n" + "GFF color config file: " + gff_color_config_file - text += "\n" + "Prefix for output files: " + str(output_file_prefix) - - if 2 in plotting_modes: - text += "\n" + "\n\nLCS SHADING OPTIONS (plotting_mode 'all-against-all' only)...\n" - text += "\n" + "LCS shading: " + str(lcs_shading) - text += "\n" + "LCS shading interval number: " + str(lcs_shading_num + 1) - text += "\n" + "LCS shading reference: " + lcs_shading_ref_dict[lcs_shading_ref] - if lcs_shading_ref == 2: - text += "\n" + "LCS shading interval size [%s]: " % (aa_bp_unit) + str(lcs_shading_interval_len) - text += "\n" + "LCS shading orientation: " + lcs_shading_ori_dict[lcs_shading_ori] - if input_user_matrix_file != "": - text += "\n" + "Custom user shading matrix file: " + input_user_matrix_file - text += "\n" + "Print user matrix values (instead of dotplot): " + str(user_matrix_print) - - text += "\n" + "\n\nGRAPHIC FORMATTING...\n" - text += "\n" + "Plot size: " + str(plot_size) - text += "\n" + "Line width: " + str(line_width) - text += "\n" + "Line color: " + line_col_for - text += "\n" + "Reverse line color: " + line_col_rev - text += "\n" + "X label position: " + str(x_label_pos) - text += "\n" + "Label size: " + str(label_size) - text += "\n" + "Spacing: " + str(spacing) - if title_clip_pos == "E": - text += "\n" + "Title length (limit number of characters): " + "last" + str(title_length) + "characters" - else: - text += "\n" + "Title length (limit number of characters): " + "first" + str(title_length) + "characters" - text += "\n" + "Length scaling: " + str(length_scaling) - text += "\n%s\n" % (70 * "-") - logprint(text) - - - # collect settings - parameters = [commandline, auto_fas, input_fasta, output_file_prefix, collage_output, m_col, n_row, filetype_dict[filetype], type_nuc, input_gff_files, gff_color_config_file, wordsize, plotting_modes, wobble_conversion, substitution_count, rc_option, alphabetic_sorting, lcs_shading, lcs_shading_num, lcs_shading_ref, lcs_shading_interval_len, lcs_shading_ori, input_user_matrix_file, user_matrix_print, plot_size, line_width, line_col_for, line_col_rev, x_label_pos, label_size, spacing, length_scaling, title_length, title_clip_pos, max_N_percentage, verbose] - - return parameters - - -############################### -# Helper Functions # -############################### - -def alphabets(type_nuc=True): - """ - provide ambiguity code for sequences - """ - - nucleotide_alphabet = ["A", "C", "G", "T"] - - nucleotide_alphabet_full = ["A", "C", "G", "T", "N", "B", "D", "H", - "V", "Y", "R", "W", "S", "K", "M"] - - nucleotide_ambiguity_code = {"N": ["A", "C", "G", "T"], # any - "B": ["C", "G", "T"], # not A - "D": ["A", "G", "T"], # not C - "H": ["A", "C", "T"], # not G - "V": ["A", "C", "G"], # not T - "Y": ["C", "T"], # pyrimidine - "R": ["A", "G"], # purine - "W": ["A", "T"], # weak - "S": ["C", "G"], # strong - "K": ["G", "T"], # keto - "M": ["A", "C"]} # amino - - nucleotide_match_dict = {"N": "[ACGTNBDHVYRWSKM]", # any - "B": "[CGTNBDHVYRWSKM]", # not A - "D": "[AGTNBDHVYRWSKM]", # not C - "H": "[ACTNBDHVYRWSKM]", # not G - "V": "[ACGNBDHVYRWSKM]", # not T - "K": "[GTNBDHVYRWSK]", # keto - not A,C,M - "M": "[ACNBDHVYRWSM]", # amino - not G,T,K - "W": "[ATNBDHVYRWKM]", # weak - not C,G,S - "S": "[CGNBDHVYRSKM]", # strong - not A,G,W - "Y": "[CTNBDHVYWSKM]", # pyrimidine - not A,G,R - "R": "[AGNBDHVRWSKM]", # purine - not C,T,Y - "A": "[ANDHVRWM]", - "C": "[CNBHVYSM]", - "G": "[GNBDVRSK]", - "T": "[TNBDHYWK]"} - - # nucleotide_match_dict = {"N": ".", # any - # "B": "[^A]", # not A - # "D": "[^C]", # not C - # "H": "[^G]", # not G - # "V": "[^T]", # not T - # "K": "[^ACM]", # keto - not A,C,M - # "M": "[^GTK]", # amino - not G,T,K - # "W": "[^CGS]", # weak - not C,G,S - # "S": "[^AGW]", # strong - not A,G,W - # "Y": "[^AGR]", # pyrimidine - not A,G,R - # "R": "[^CTY]", # purine - not C,T,Y - # "A": "[ANDHVRWM]", - # "C": "[CNBHVYSM]", - # "G": "[GNBDVRSK]", - # "T": "[TNBDHYWK]"} - - aminoacid_alphabet = ["A", "R", "N", "D", "C", "E", "Q", "G", - "H", "I", "L", "K", "M", "F", "P", "S", - "T", "W", "Y", "V", "U", "O", "*"] - - aminoacid_alphabet_full = ["A", "R", "N", "D", "C", "E", "Q", "G", - "H", "I", "L", "K", "M", "F", "P", "S", - "T", "W", "Y", "V", "U", "O", "*", "J", - "Z", "B", "X"] - - aminoacid_ambiguity_code = {"J": ["I", "L"], - "Z": ["Q", "E"], - "B": ["N", "D"], - "X": ["A", "R", "N", "D", "C", "E", "Q", "G", - "H", "I", "L", "K", "M", "F", "P", "S", - "T", "W", "Y", "V", "U", "O", "*"]} # any - - aminoacid_match_dict = {"J": "[ILJ]", - "Z": "[QEZ]", - "B": "[NDB]", - # "X": ".", - "X": "[ARNDCEQGHILKMFPSTWYVUO*XBZJ]", - "A": "[AX]", - "R": "[RX]", - "N": "[NXB]", - "D": "[DXB]", - "C": "[CX]", - "E": "[EXZ]", - "Q": "[QXZ]", - "G": "[GX]", - "H": "[HX]", - "I": "[IXJ]", - "L": "[LXJ]", - "K": "[KX]", - "M": "[MX]", - "F": "[FX]", - "P": "[PX]", - "S": "[SX]", - "T": "[TX]", - "W": "[WX]", - "Y": "[YX]", - "V": "[VX]", - "U": "[UX]", - "O": "[OX]", - "*": "[*X]"} - - aa_only = set(['E', 'F', 'I', 'J', 'L', 'O', 'Q', 'P', 'U', 'X', 'Z', '*']) - # return nucleotide_alphabet, nucleotide_alphabet_full, nucleotide_ambiguity_code, aminoacid_alphabet, aminoacid_alphabet_full, aminoacid_ambiguity_code, aa_only - - if type_nuc: - return nucleotide_alphabet, nucleotide_alphabet_full, nucleotide_ambiguity_code, nucleotide_match_dict - else: - return aminoacid_alphabet, aminoacid_alphabet_full, aminoacid_ambiguity_code, aminoacid_match_dict - -def logprint(text, start=False, printing=True, prefix=""): - """ - log output to log_file and optionally print - """ - - # define log file name and open file - global log_file_name - if start and trial_mode: - log_file_name = "log_file.txt" - if prefix != "" and prefix != None: - if not prefix.endswith("-"): - prefix = prefix + "-" - log_file_name = prefix + log_file_name - log_file = open(log_file_name, 'w') - log_file.write("Date: %s\n\n" % str(datetime.datetime.now())) - elif start: - date = datetime.date.today() - time = str(datetime.datetime.now()).split(" ")[1].split(".")[0].replace(":", "-") - log_file_name = "%s_%s_log_file.txt" % (date, time) - if prefix != "" and prefix != None: - if not prefix.endswith("-"): - prefix = prefix + "-" - log_file_name = prefix + log_file_name - log_file = open(log_file_name, 'w') - log_file.write("Date: %s\n\n" % str(datetime.datetime.now())) - else: - log_file = open(log_file_name, 'a') - - # write log (and print) - log_file.write(text + "\n") - if printing: - print text - log_file.close() - -def time_track(starting_time, show=True): - """ - calculate time passed since last time measurement - """ - now = time.time() - delta = now - starting_time - if show: - text = "\n\t %s seconds\n" % str(delta) - logprint(text, start=False, printing=True) - return now - -def calc_fig_ratio(ncols, nrows, plot_size, verbose=False): - """ - calculate size ratio for given number of columns (ncols) and rows (nrows) - with plot_size as maximum width and length - """ - ratio = ncols*1./nrows - if verbose: - text = " ".join([ncols, nrows, ratio]) - logprint(text, start=False, printing=True) - if ncols >= nrows: - figsize_x = plot_size - figsize_y = plot_size / ratio - else: - figsize_x = plot_size * ratio - figsize_y = plot_size - return figsize_x, figsize_y - -def shorten_name(seq_name, max_len=20, title_clip_pos="B"): #, delim="_"): - """ - shorten sequence names (for diagram titles) - """ - - if len(seq_name) <= max_len: - return seq_name - - # take last characters - if title_clip_pos == "E": - name = seq_name[len(seq_name)-max_len:] - - # take first characters - else: - name = seq_name[:max_len] - - """# keep first and last part if multiple parts separated by delimiter (e.g. species_prefix + sequence_id) - if delim in seq_name: - if seq_name.count(delim) >= 2: - name = "%s..." % delim.join(seq_name.split(delim)[:1]) + seq_name.split(delim)[-1] # .replace("_000", "-") - else: - name = seq_name[:((max_len-2)//2)] + "..." + seq_name[((max_len-2)//2):] - - if len(name) > max_len: - name = name[:((max_len-2)//2)] + "..." + name[((max_len-2)//2):] - else: - name = seq_name[:((max_len-2)//2)] + "..." + seq_name[((max_len-2)//2):] - """ - - return name - -def unicode_name(name): - """ - replace non-ascii characters in string (e.g. for use in matplotlib) - """ - unicode_string = eval('u"%s"' % name) - return unicodedata.normalize('NFKD', unicode_string).encode('ascii','ignore') - -def check_bools(arg, update_log_txt = True, default=None): - """ - converts commandline arguments into boolean - """ - - - # convert valid arguments - if str(arg).lower() == "y" or str(arg) == "1": - return True - elif str(arg).lower() == "n" or str(arg) == "0": - return False - - # use default in case of invalid argument - else: - if update_log_txt: - global log_txt - log_txt += "using default for " + str(arg) - else: - try: - logprint("using default for " + str(arg)) - except: - print "using default for " + str(arg) - return default - -def create_color_list(number, color_map=None, logging=False, max_grey="#595959"): - """ - create color list with given number of entries - grey by default, matplotlib color_map can be provided - """ - - try: - # create pylab colormap - cmap = eval("P.cm." + color_map) - # get descrete color list from pylab - cmaplist = [cmap(i) for i in range(cmap.N)] # extract colors from map - # determine positions for number of colors required - steps = (len(cmaplist)-1)/(number) - numbers = range(0, len(cmaplist), steps) - - # extract color and convert to hex code - colors = [] - for idx in numbers[:-1]: - rgb_color = cmaplist[idx] - col = rgb2hex(rgb_color[0]*255, rgb_color[1]*255, rgb_color[2]*255) - colors.append(col) - - # grey - except: - if not color_map == None: - logprint("Invalid color_map (%s) provided! - Examples: jet, Blues, OrRd, bwr,..." % color_map) - logprint("See https://matplotlib.org/users/colormaps.html\n") - old_max_grey = "#373737" - old_max_grey = "#444444" - colors = list(Color("#FFFFFF").range_to(Color(max_grey), number)) # grey - for idx in range(len(colors)): - colors[idx] = str(colors[idx]).replace("Color ", "") - if "#" in colors[idx] and len(colors[idx]) != 7: - # print colors[idx] - colors[idx] = colors[idx] + colors[idx][-(7-len(colors[idx])):] - - text = "%d Colors: %s" % (len(colors), ", ".join(colors)) - if logging: logprint(text, start=False, printing=True) - - if len(colors) < number: - logprint("\nError in color range definition! %d colors missing\n" % (number - len(colors))) - - return colors - - -############################### -# File Handling # -############################### - -def read_seq(input_fasta, verbose=False): - """ - read fasta sequences from (all) file(s) - """ - - # check if file provided - if input_fasta == [] or input_fasta == "": - text = "Attention: No valid file names provided: >%s<" % input_fasta - logprint(text, start=False, printing=True) - return {}, [] - - # combine sequence files, if required - if type(input_fasta) == list: - # concatenate fasta files - if len(input_fasta) > 1: - if verbose: - print "concatenating fastas...", - text = "concatenating fastas..." - input_fasta_combi = concatenate_files(input_fasta) - if verbose: - print "done" - text += "done" - logprint(text, start=False, printing=False) - else: - input_fasta_combi = input_fasta[0] - else: - input_fasta_combi = input_fasta - - # read sequences - if verbose: - print "reading fasta...", - text = "reading fasta...", - try: - seq_dict = SeqIO.index(input_fasta_combi, "fasta") - except ValueError: - logprint("Error reading fasta sequences - please check input files, e.g. for duplicate names!") - return {}, [] - except: - logprint("Error reading fasta sequences - please check input files!") - return {}, [] - - if verbose: - print "done" - text += "done" - logprint(text, start=False, printing=False) - - for seq in seq_dict: - if "-" in seq_dict[seq].seq: - # ungapped = seq_dict[seq].seq.ungap("-") # cannot be assigned back to sequence record - text = "\nSequences degapped prior Analysis!!!" - logprint(text, start=False, printing=True) - return read_seq(degap_fasta(input_fasta), verbose=verbose) - - # get ordered sequence names - sequences = [] - for item in SeqIO.parse(input_fasta_combi, "fasta"): - sequences.append(item.id) - return seq_dict, sequences - -def read_gff_color_config(gff_color_config_file=""): - """ - define coloring options for gff-based color shading of self-dotplots - """ - - # default aestetics for annotation shading (e.g. if no user config file is provided) - # dictionary with feature_type as key and tuple(color, transparency, zoom) as value - gff_feat_colors = {"orf": ("#b41a31", 0.2, 0), - "orf_rev": ("#ff773b", 0.3, 0), - "gene": ("#b41a31", 0.2, 0), - "cds": ("darkorange", 0.2, 0), - "exon": ("orange", 0.2, 0), - "intron": ("lightgrey", 0.2, 0), - "utr": ("lightblue", 0.2, 0), - "repeat_region": ("green", 0.3, 0), - "repeat": ("green", 0.3, 0), - "tandem_repeat": ("red", 0.3, 0), - "transposable_element": ("blue", 0.3, 0), - "ltr_retrotransposon": ("#cccccc", 0.5, 0), - "ltr-retro": ("#cccccc", 0.5, 0), - "long_terminal_repeat": ("#2dd0f0", 0.75, 2), - "ltr": ("#2dd0f0", 0.75, 2), - "pbs": ("purple", 0.75, 2), - "ppt": ("#17805a", 0.5, 2), - "target_site_duplication": ("red", 0.75, 2), - "misc_feature": ("grey", 0.3, 0), - "misc_feat": ("grey", 0.3, 0), - "misc": ("grey", 0.3, 0), - "others": ("grey", 0.5, 0)} - if gff_color_config_file in ["", None] or not os.path.exists(str(gff_color_config_file)): - return gff_feat_colors - - text = "Updating GFF color configuration with custom specifications\n" - logprint(text, start=False, printing=True) - - # read custom gff_color_config_file - in_file = open(gff_color_config_file, 'rb') - overwritten = set([]) - for line in in_file: - if not line.startswith("#") and len(line.strip().split("\t")) >= 4: - data = line.strip().split("\t") - feat = data[0].lower() - color = data[1].lower() - - # check, if settings are valid - if not mcolors.is_color_like(color): - color = "grey" - text = "Invalid color specified for %s: %s - default grey" % (data[0], data[1]) - logprint(text) - try: - alpha = float(data[2]) - except: - alpha = 0.75 - text = "Invalid alpha specified for %s: %s - default 0.75" % (data[0], data[2]) - logprint(text) - try: - zoom = float(data[3]) - except: - zoom = 0 - text = "Invalid zoom specified for %s: %s - default 0" % (data[0], data[3]) - logprint(text) - - # track changes of predefined settings - if feat in gff_feat_colors.keys(): - overwritten.add(data[0].lower()) - - gff_feat_colors[feat] = (color, alpha, zoom) - in_file.close() - - # default coloring for unknown annotations - if not "others" in gff_feat_colors.keys(): - gff_feat_colors["others"] = ("grey", 0.5, 0) - - if verbose: - # print configuration - text = "\n\nGFF color specification:\n%s\n" % (60 * ".") - for item in sorted(gff_feat_colors.keys()): - text += "%-30s\t%-10s\t%-5s\t%s\n" % (item, str(gff_feat_colors[item][0]), str(gff_feat_colors[item][1]), str(gff_feat_colors[item][2])) - logprint (text, printing=True) - - # print overwritting feature type specifications - if len(overwritten) != 0: - text = "%d feature type specifications overwritten:" % len(overwritten) - text += "\n\t"+ ", ".join(overwritten) + "\n" - logprint(text, start=False, printing=True) - - text = "GFF color specification updated acc. to %s\n\t%s\n\n" % (gff_color_config_file, ", ".join(gff_feat_colors)) - logprint(text, start=False, printing=True) - - return gff_feat_colors - -def read_gffs(input_gff_files, color_dict={"others": ("grey", 1, 0)}, type_nuc=True, prefix="", filetype='png', verbose=False): - """ - create feature dictionary from input_gff - sequence name as key and (feature type, start, stop) as value - """ - if type(input_gff_files) != list: - input_gff_files = [input_gff_files] - - # create dictionary with seq_name as key and (type, start and stop) as value - unknown_feats = set([]) - used_feats = set([]) - feat_dict = {} - for input_gff in input_gff_files: - text = "...reading " + input_gff - logprint(text, start=False, printing=True) - - in_file = open(input_gff, 'rb') - for line in in_file: - if not line.startswith("#") and line.strip() != "": - data = line.strip().split("\t") - feat_type = data[2].lower() - if data[6] == "-": - feat_type += "_rev" - if not feat_type.lower() in color_dict.keys(): - if feat_type.lower().replace("_rev", "") in color_dict.keys(): - feat_type = feat_type.replace("_rev", "") - else: - unknown_feats.add(feat_type) - feat_type = "others" - used_feats.add(feat_type) - if not data[0] in feat_dict.keys(): - feat_dict[data[0]] = [(feat_type, int(data[3]), int(data[4]))] # feature type, start, stop - else: - feat_dict[data[0]].append((feat_type, int(data[3]), int(data[4]))) # feature type, start, stop - if verbose: - text = "\nAnnotations for: %s\n" % ", ".join(feat_dict.keys()[:10]) - if len(feat_dict.keys()) > 10: - text = text[:-1] + ", ...\n" - logprint(text, start=False, printing=True) - in_file.close() - - # print feature types without specific shading settings - if len(unknown_feats) != 0: - text = "Missing shading specification for %d feature type(s):\n\t%s\n" % (len(unknown_feats), ", ".join(sorted(unknown_feats))) - logprint(text, start=False, printing=True) - - # create color legend - colors, alphas = [], [] - for item in sorted(used_feats): - colors.append(color_dict[item][0]) - alphas.append(color_dict[item][1]) - legend_figure(colors=colors, lcs_shading_num=len(used_feats), type_nuc=type_nuc, bins=sorted(used_feats), alphas=alphas, gff_legend=True, prefix=prefix, filetype=filetype) - - # print settings - text = "GFF Feature Types: %s\nGFF Colors: %s" % (", ".join(sorted(used_feats)), ", ".join(sorted(colors))) - logprint(text, start=False, printing=True) - - return feat_dict - -def read_matrix(matrix_file_name, delim="\t", symmetric=True, recursion=False, verbose=False): - input_file = open(matrix_file_name, 'rb') - - # read sequence names from first column - names = [] - for line in input_file: - if not line.startswith("#") and not line.startswith(delim) and delim in line: - names.append(line.strip().split(delim)[0]) - logprint("Delimiter '%s': %d names - %s\n" % (delim, len(names), ", ".join(names))) - - # check if names were found - otherwise try another delimiter - if names == [] and not recursion: - if delim == "\t": - new_delim = "," - else: - new_delim = "\t" - logprint("\nMatrix file not containing data delimited by '%s' - trying to read matrix with delimiter '%s'" % (delim.replace("\t", "\\t"), new_delim)) - info_dict = read_matrix(matrix_file_name, delim=new_delim, symmetric=symmetric, recursion=True, verbose=verbose) - return info_dict - elif names == []: - logprint("Empty matrix file with alternative delimiter!") - return info_dict - input_file.close() - - input_file = open(matrix_file_name, 'rb') - # read matrix entries as values in dictionary with tuple(names) as key - info_dict = {} - contradictory_entries = [] - for line in input_file: - if not line.startswith("#") and not line.startswith(delim) and delim in line: - data = line.strip().split(delim) - for idx in range(len(data[1:])): - # print tuple(sorted([data[0], names[idx]])), data[idx+1] - if symmetric: - key = tuple(sorted([names[idx], data[0]])) - else: - key = tuple(names[idx], data[0]) - if key in info_dict.keys(): - if symmetric and info_dict[key] != data[idx+1] and data[idx+1] not in ["", "-"] and info_dict[key] not in ["", "-"]: - contradictory_entries.append(key) - info_dict[key] = data[idx+1] - input_file.close() - - if len(contradictory_entries) != 0: - try: - logprint("\nContradictory entries in matrix file %s:\n\t%s" % (matrix_file_name, ", ".join(contradictory_entries))) - except: - log_txt = "\nContradictory entries in matrix file %s:\n\t" % (matrix_file_name) - for item in contradictory_entries: - log_txt += str(item).replace("'", "") + ", " - log_txt = log_txt[:-2] - logprint(log_txt) - logprint("Using value from bottom left triangle!") - if verbose: - logprint("\nMatrix information for Sequences named: " % ", ".join(names)) - - return info_dict - -def concatenate_files(file_list, combi_filename="temp_combined.fasta", verbose=False): - """ - concatenate content of all files in file_list into a combined file named combi_filename - """ - out_file = open(combi_filename, 'w') - text = "" - for item in file_list: - if verbose: - text += item + " " - print item, - # read in_file linewise and write to out_file - in_file = open(item, 'rb') - for line in in_file: - out_file.write(line.strip()+"\n") - in_file.close() - out_file.close() - if verbose: - logprint(text, start=False, printing=False) - return combi_filename - -def degap_fasta(input_fasta): - """ - remove gaps from fasta - new degapped sequence file created - """ - - # degap all sequence files - output_fastas = [] - if type(input_fasta) != list: - input_fasta = list(input_fasta) - for input_fas in input_fasta: - output_fas = input_fas[:input_fas.rfind(".")] + "_degapped.fas" - in_file = open(input_fas, 'rb') - out_file = open(output_fas, 'w') - for line in in_file: - if line.startswith(">"): - out_file.write(line.strip()+"\n") - else: - out_file.write(line.strip().replace("-", "")+"\n") - out_file.close() - in_file.close() - output_fastas.append(output_fas) - return output_fastas - -def legend_figure(colors, lcs_shading_num, type_nuc=True, unit="%", filetype="png", max_lcs_len=None, min_lcs_len=0, bins=[], alphas=[], gff_legend=False, prefix="", verbose=False): - """ - create figure color legend - """ - max_legend_length_row = 8 - max_legend_length_col = 4 - - # define output file - if filetype not in ["png", "pdf", "svg"]: - text = "Provide valid file type - png, pdf, or svg" - logprint(text, start=False, printing=True) - filetype="png" - - # check if length of information fit - if not gff_legend and ((bins != [] and len(colors) != lcs_shading_num+1) or (bins != [] and len(colors) != len(bins)+1)): - if bins != [] and len(colors) != lcs_shading_num+1: - text = "**Attention**\nlcs_shading_num (%d) does not match number of colors (%d)!\n"% (lcs_shading_num, len(bins)) - elif bins != [] and len(colors) != len(bins)+1: - text = "**Attention**\nnumber of LCS length bins (%d) does not match number of colors (%d)!\n" % (len(colors), len(bins)) - logprint(text, start=False, printing=True) - elif gff_legend and len(bins) != len(colors): - text = "**Attention**\nnumber of GFF Feature Types (%d) does not match number of colors (%d)!\n" % (len(colors), len(bins)) - logprint(text, start=False, printing=True) - - # set alpha values to opaque if none are provided - if alphas == []: - for item in colors: - alphas.append(1) - - # legend data points - data_points = range(len(colors)) - if not gff_legend: - - # specify intervals, if max_lcs_len provided - if max_lcs_len != None: - multi_factor = 100 # one digit - if max_lcs_len <= 1: - multi_factor = 1000 # two digits - # len_interval_size = (max_lcs_len-min_lcs_len) * multi_factor *1. // lcs_shading_num * (1./ multi_factor) - len_interval_size = (max_lcs_len-min_lcs_len) * 1. / lcs_shading_num - len_pos = [float("%.2f" % (min_lcs_len))] - # calculate interval positions - for idx in range(lcs_shading_num): - len_pos.append(float("%.2f" % (len_pos[-1] + len_interval_size))) - - if prefix.startswith("custom-matrix") and (0 <= max_lcs_len <= 100 and 0 <= min_lcs_len <= 100): - unit = "%" - elif prefix.startswith("custom-matrix"): - unit = "" - - text = "\n%d Legend intervals from %.2f to %.2f: \n\t%s - number: %d, step: %.2f, unit: %s\n" % (lcs_shading_num+1, min_lcs_len, max_lcs_len, str(len_pos), len(len_pos), len_interval_size, unit) - logprint(text, start=False, printing=True) - pos = len_pos - interval_size = len_interval_size - else: - # generate legend labels acc. to standard interval notation - interval_size = 100 // lcs_shading_num - pos = range(interval_size, 101+interval_size, interval_size) - - if bins != []: # labels provided - legend_labels = bins[:] - legend_labels.append("max") - legend_labels_lengths = [] - for item in bins: - legend_labels_lengths.append("[%d %s, %d %s)" % (item - min(bins), unit, item, unit)) - if len(bins) == len(colors) - 1: - legend_labels_lengths.append("[%d %s, %s]" % (max(bins), unit, u"\u221E")) # infinite - - else: - legend_labels = [] - legend_labels_lengths = [] - for idx in range(len(pos)): - num = pos[idx] - legend_labels.append("[%d%%, %d%%)" % (num - interval_size, num)) - if max_lcs_len != None: - num = len_pos[idx] - # as int or float - if num == int(num) and int(len_interval_size) == len_interval_size: - legend_labels_lengths.append("[%d %s, %d %s)" % (num, unit, num + len_interval_size, unit)) - else: - legend_labels_lengths.append("[%.2f %s, %.2f %s)" % (num, unit, num + len_interval_size, unit)) - legend_labels[-1] = "100" + unit - if max_lcs_len != None: - if num == int(num) and int(len_interval_size) == len_interval_size: - legend_labels_lengths[-1] = "%d %s" % (max_lcs_len, unit) - else: - legend_labels_lengths[-1] = "%.2f %s" % (max_lcs_len, unit) - - # set labels and choose file name - if gff_legend: - label_text = bins[:] - edge_col = None - legend_file_name = "GFF_Shading_Legend_n%d." % lcs_shading_num + filetype - elif max_lcs_len != None: - label_text = legend_labels_lengths[:] - edge_col = "black" - legend_file_name = "Polydotplot_LCS_Shading_Legend_max%d%s_n%d." % (max_lcs_len, unit, lcs_shading_num) + filetype - elif bins != []: - label_text = legend_labels_lengths[:] - edge_col = "black" - legend_file_name = "Polydotplot_LCS_Shading_Legend_%d%s_n%d." % (bins[0], unit, lcs_shading_num) + filetype - else: - label_text = legend_labels[:] - edge_col = "black" - legend_file_name = "Polydotplot_LCS_Shading_Legend_%%len_n%d." % lcs_shading_num + filetype - - if prefix != None and prefix != "": - if not prefix.endswith("-"): - prefix = prefix + "-" - legend_type = "LCS" - if prefix.startswith("custom-matrix"): - prefix = prefix.replace("custom-matrix", "")[1:] - legend_type = "CustomMatrix" - legend_file_name = prefix + legend_file_name.replace("LCS", legend_type) - - # plot legend figure - fig, ax = P.subplots(3, 1, figsize=(len(colors)*2, len(colors)*2)) - for idx in range(len(colors)): - ax[0].bar(data_points[idx]+1, data_points[idx]+1, color=colors[idx], label=label_text[idx], - alpha=alphas[idx], edgecolor=edge_col) - ax[1].bar(data_points[idx]+1, 0, color=colors[idx], label=label_text[idx], - alpha=alphas[idx], edgecolor=edge_col) - ax[2].bar(data_points[idx]+1, 0, color=colors[idx], label=label_text[idx], - alpha=alphas[idx], edgecolor=edge_col) - ax[1].set_ylim(0,1) - ax[2].set_ylim(0,1) - ax[1].legend(ncol=((len(colors)-1)//max_legend_length_row)+1, framealpha=1) # vertical legend - col_num = len(colors) - if len(colors) > max_legend_length_col: - remainder = 0 - if len(colors) % max_legend_length_col != 0: - remainder = 1 - row_num = len(colors) // max_legend_length_col + remainder - remainder = 0 - if len(colors) % row_num != 0: - remainder = 1 - col_num = len(colors) // row_num + remainder - ax[2].legend(ncol=col_num, framealpha=1) # horizontal legend - - P.savefig(legend_file_name) - - return legend_file_name - - -############################### -# Analysis Functions # -############################### - -def wobble_replacement(sequence, general_ambiguity_code, verbose=False): - """ - get all degenerated sequences for sequence with ambiguous residues - (only residues considered that are keys in wobble_dictionary) - """ - - # get positions of ambiguous residues - wobble_pos = [] - for idx in range(len(sequence)): - letter = sequence[idx] - if letter in general_ambiguity_code.keys(): - wobble_pos.append(idx) - - if verbose: - text = "\t%d wobbles" % len(wobble_pos) - logprint(text, start=False, printing=True) - - # replace one wobble through each iteration by all possible residues - # repeat if still wobbles in new kmers - kmer_variants = [sequence] - while True: - if verbose: - text = "\t\t%d kmer variants" % len(kmer_variants) - logprint(text, start=False, printing=True) - temp_kmers = set([]) - for kmer in kmer_variants: - for idx in wobble_pos: - letter = kmer[idx] - if letter in general_ambiguity_code.keys(): - for base in general_ambiguity_code[kmer[idx]]: - newkmer = kmer[:idx] + base + kmer[idx+1:] - temp_kmers.add(newkmer) - wobble = False - for kmer in temp_kmers: - for idx in range(len(kmer)): - letter = kmer[idx] - if letter in general_ambiguity_code.keys(): - wobble = True - break - if wobble: - break - kmer_variants = set(list(temp_kmers)[:]) - if not wobble: - break - - return kmer_variants - -def split_diagonals(data, stepsize=1): - """ - split array if point difference exceeds stepsize - data = sorted list of numbers - """ - return np.split(data, np.where(np.diff(data) != stepsize)[0]+1) - -def longest_common_substring(s1, s2): - m = [[0] * (1 + len(s2)) for i in xrange(1 + len(s1))] - longest, x_longest = 0, 0 - for x in xrange(1, 1 + len(s1)): - for y in xrange(1, 1 + len(s2)): - if s1[x - 1] == s2[y - 1]: - m[x][y] = m[x - 1][y - 1] + 1 - if m[x][y] > longest: - longest = m[x][y] - x_longest = x - else: - m[x][y] = 0 - return longest - -def lcs_from_x_values(x_values): - """ - calculate length of longest common substring based on nested list of numbers - """ - if len(x_values) == 0: - return 0 - # get lengths of each subarray data - lengths = np.array([len(i) for i in x_values]) - return max(lengths) - - -############################### -# Matching Functions # -############################### - -def find_match_pos_diag(seq1, seq2, wordsize, report_lcs=False, rc_option=True, convert_wobbles=False, max_N_percentage=49, type_nuc=True, verbose=False): - """ - find all matching positions with matches >= wordsize - convert matching points into lines of the length of the match - (+ optional handling of ambiguities) - """ - global t1 # timer - - # look for Ns in DNA or Xs in proeins (minimum word size) - if type_nuc == True: - any_residue = "N" - else: - any_residue = "X" - - # read sequences - seq_one = seq1.upper(); len_one = len(seq_one) - seq_two = seq2.upper(); len_two = len(seq_two) - - # set ambiguity code for wobble replacement - general_ambiguity_code = alphabets(type_nuc)[2] # nucleotide_ambiguity_code or aminoacid_ambiguity_code - - # forward - ################################# - kmer_pos_dict_one = {}; kmer_pos_dict_two = {} # dictionaries for both sequences - - # reverse complement - ################################# - kmer_pos_dict_three = {}; kmer_pos_dict_four = {} # dictionaries for both sequences - - # create dictionaries with kmers (wordsize) and there position(s) in the sequence - if rc_option: - data_list = [(str(seq_one), kmer_pos_dict_one), - (str(seq_two), kmer_pos_dict_two), - (str(seq_one), kmer_pos_dict_three), - (str(seq_two.reverse_complement()), kmer_pos_dict_four)] - else: - data_list = [(str(seq_one), kmer_pos_dict_one), - (str(seq_two), kmer_pos_dict_two)] - for (seq, kmer_pos_dict) in data_list: - for i in range(len(seq)-wordsize+1): - kmer = seq[i:i+wordsize] - # discard kmer, if too many Ns included - if kmer.count(any_residue)*100./wordsize <= max_N_percentage: - if not convert_wobbles: - try: - kmer_pos_dict[kmer].append(i) - except KeyError: - kmer_pos_dict[kmer] = [i] - else: - wobbles = False - for item in general_ambiguity_code.keys(): - if item in kmer: - wobbles = True - break - if not wobbles: - try: - kmer_pos_dict[kmer].append(i) - except KeyError: - kmer_pos_dict[kmer] = [i] - else: - kmer_variants = wobble_replacement(kmer, general_ambiguity_code) - for new_kmer in kmer_variants: - # print "\t", new_kmer - try: - kmer_pos_dict[new_kmer].append(i) - except KeyError: - kmer_pos_dict[new_kmer] = [i] - - # find kmers shared between both sequences - matches_for = set(kmer_pos_dict_one).intersection(kmer_pos_dict_two) # forward - matches_rc = set(kmer_pos_dict_three).intersection(kmer_pos_dict_four) # reverse complement - - if verbose: - text = "[matches: %i for; %.i rc]" % (len(matches_for), len(matches_rc)) - logprint(text, start=False, printing=True) - - # create lists of x and y co-ordinates for scatter plot - # keep all coordinates of all shared kmers (may match multiple times) - diag_dict_for = {} - diag_dict_rc = {} - for (match_list, pos_dict1, pos_dict2, diag_dict) in [(matches_for, kmer_pos_dict_one, kmer_pos_dict_two, diag_dict_for), - (matches_rc, kmer_pos_dict_three, kmer_pos_dict_four, diag_dict_rc)]: - for kmer in match_list: - for i in pos_dict1[kmer]: - for j in pos_dict2[kmer]: - diag = i-j - points = set(range(i+1, i+wordsize+1)) - if not diag in diag_dict.keys(): - diag_dict[diag] = points - else: - diag_dict[diag].update(points) - - # convert coordinate points to line start and stop positions - x1 = [] # x values reverse - y1 = [] # y values forward - for diag in diag_dict_for.keys(): - x_values = np.array(sorted(diag_dict_for[diag])) - x1.extend(split_diagonals(x_values)) - y_values = split_diagonals(x_values - diag) - y1.extend(y_values) - - x2 = [] # x values rc - y2 = [] # y values rc - if rc_option: - for diag in diag_dict_rc.keys(): - factor = len_two + diag + 1 - x_values = np.array(sorted(diag_dict_rc[diag])) - x2.extend(split_diagonals(x_values)) - y_values = split_diagonals(factor - x_values, -1) - y2.extend(y_values) - - if verbose: - t1 = time_track(t1) - - if not report_lcs: - return np.array(x1), np.array(y1), np.array(x2), np.array(y2) - else: - # get length of longest common substring based on match lengths - lcs_for = lcs_from_x_values(x1) - lcs_rev = lcs_from_x_values(x2) - return np.array(x1), np.array(y1), np.array(x2), np.array(y2), lcs_for, lcs_rev - -def find_match_pos_regex(seq1, seq2, wordsize, substitution_count=0, report_lcs=False, rc_option=True, convert_wobbles=False, max_N_percentage=49, type_nuc=True, verbose=False): - """ - find all matching positions with matches >= wordsize via regular expression search - fuzzy matching - allow up to substitution_count substitutions - convert matching points into lines of the length of the match - (+ optional handling of ambiguities) - """ - global t1 # timer - - # read sequences - seq_one = seq1.upper(); len_one = len(seq_one) - seq_two = seq2.upper(); len_two = len(seq_two) - - # set ambiguity code for wobble replacement - general_ambiguity_code = alphabets(type_nuc)[2] # nucleotide_ambiguity_code or aminoacid_ambiguity_code - ambiguity_match_dict = alphabets(type_nuc)[3] - - ambiq_residues = "[%s]" % "".join(general_ambiguity_code.keys()) - - # look for Ns in DNA or Xs in proeins (minimum word size) - if type_nuc == True: - any_residue = "N" - else: - any_residue = "X" - - # check for wobble presence - if not (regex.search(ambiq_residues, str(seq_one)) == None and regex.search(ambiq_residues, str(seq_two)) == None): - wobble_found = True - else: - wobble_found = False - - # dictionary for matches - diag_dict_for = {} - diag_dict_rc = {} - counter = [0, 0] - - # one-way matching - if rc_option: - data_list = [(str(seq_one), str(seq_two), diag_dict_for, 0), - (str(seq_one), str(seq_two.reverse_complement()), diag_dict_rc, 1)] - else: - data_list = [(str(seq_one), str(seq_two), diag_dict_for, 0)] - - for seq_query, seq_target, diag_dict, counter_pos in data_list: - # split query sequence into kmers - if not rc_option and counter_pos == 1: - break - - for idx in range(len(str(seq_query))-wordsize+1): - kmer = str(seq_query)[idx:idx+wordsize] - - # skip excessive N/X stretches (big black areas) - if kmer.count(any_residue)*100./wordsize <= max_N_percentage: - # convert kmer to regular expression for wobble_matching - if convert_wobbles and wobble_found: - kmer_string = "" - # replace each residue with matching residues or wobbles - for jdx in range(len(kmer)): - kmer_string += ambiguity_match_dict[kmer[jdx]] - else: - kmer_string = kmer - - # convert to regular expression tolerating substitution errors - if type(substitution_count) == int and substitution_count != 0: - kmer_string = "(%s){s<=%d}" % (kmer_string, substitution_count) - - # search for regular expression in target sequence - kdx = 0 - start = True - if regex.search(kmer_string, seq_target[kdx:]) != None: - counter[counter_pos] += 1 - while regex.search(kmer_string, seq_target[kdx:]) != None: - # search for regular expression pattern in target sequence - result = regex.search(kmer_string, seq_target[kdx:]) - - kmer2 = seq_target[kdx:][result.start():result.end()] - - # skip excessive N/X stretches (big black areas) - if kmer2.count(any_residue)*100./wordsize <= max_N_percentage: - diag = idx-(kdx+result.start()) - points = set(range(idx+1, idx+wordsize+1)) - if not diag in diag_dict.keys(): - diag_dict[diag] = points - else: - diag_dict[diag].update(points) - - kdx += result.start() + 1 - if kdx >= len(seq_target): - break - elif regex.search(kmer_string, seq_target[kdx:]) != None: - counter[counter_pos] += 1 - - if verbose: - text = "%5.i \tforward matches" % counter[0] - text += "\n%5.i \treverse complementary matches" % counter[1] - logprint(text, start=False, printing=True) - - # convert coordinate points to line start and stop positions - x1 = [] # x values reverse - y1 = [] # y values forward - for diag in diag_dict_for.keys(): - x_values = np.array(sorted(diag_dict_for[diag])) - x1.extend(split_diagonals(x_values)) - y_values = split_diagonals(x_values - diag) - y1.extend(y_values) - - x2 = [] # x values rc - y2 = [] # y values rc - if rc_option: - for diag in diag_dict_rc.keys(): - factor = len_two + diag + 1 - x_values = np.array(sorted(diag_dict_rc[diag])) - x2.extend(split_diagonals(x_values)) - y_values = split_diagonals(factor - x_values, -1) - y2.extend(y_values) - - if verbose: - t1 = time_track(t1) - - if not report_lcs: - return np.array(x1), np.array(y1), np.array(x2), np.array(y2) - else: - # get length of longest common substring based on match lengths - lcs_for = lcs_from_x_values(x1) - lcs_rev = lcs_from_x_values(x2) - return np.array(x1), np.array(y1), np.array(x2), np.array(y2), lcs_for, lcs_rev - - -############################### -# Dot Plot Functions # -############################### - -def selfdotplot(input_fasta, wordsize, prefix=None, plot_size=10, label_size=10, filetype='png', type_nuc=True, convert_wobbles=False, substitution_count=0, alphabetic_sorting=False, max_N_percentage=49, verbose=False, multi=True, ncols=4, nrows=5, gff_files=[], gff_color_dict={"others": ("grey", 1, 0)}, title_length=float("Inf"), title_clip_pos="B"): - """ - self-against-self dotplot - partially from biopython cookbook - """ - - # read sequences - seq_dict, sequences = read_seq(input_fasta) - if seq_dict == {}: - logprint("\nFailed to load sequences") - return [] - - if alphabetic_sorting: - sequences = sorted(sequences) - - # check if at least one input sequence - if len(sequences) == 0: - text = "\n%s\n\nCreating %s selfdotplot images\n%s\n\n=>" % (50*"=", len(sequences), 28*"-") - text += " No sequences provided for selfdotplot!\n\nTerminating polydotplot!" - logprint(text, start=False, printing=True) - return - elif len(sequences) == 1 and multi: - text = "\n\nCreating collage output for single selfdotplot!" - text += "\nRecommendation: Change to individual mode by using '--collage_output n'!\n\n" - logprint(text, start=False, printing=True) - - if multi and (ncols == 0 or nrows == 0): - ncols = max(ncols, 1) - nrows = max(nrows, 1) - text = "\n\nSelfdotplot Collage: Invalid collage - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - if multi and ncols > len(sequences): - ncols = len(sequences) - nrows = 1 - text = "\n\nSelfdotplot Collage: Few sequences - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - elif multi and ncols*(nrows-1) > len(sequences): - nrows = ((len(sequences)-1) // ncols) + 1 - text = "\n\nSelfdotplot Collage: Few sequences - correcting number of rows:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - if multi and not (nrows == 1 and ncols == 1) and plot_size <= label_size/2: - label_size = plot_size * 3 // 2 - text = "Reducing label size for better visualization to %d\n" % label_size - logprint(text, start=False, printing=True) - - # read gff annotation data if provided for shading - if gff_files != None and gff_files != []: - text = "\n%s\n\nReading %s GFF annotation files\n%s\n\n=> %s\n" % (50*"=", len(gff_files), 28*"-", ", ".join(gff_files)) - logprint(text, start=False, printing=True) - if prefix != None and prefix != "": - legend_prefix = prefix + "-Selfdotplot" - else: legend_prefix = "Selfdotplot" - feat_dict = read_gffs(gff_files, color_dict=gff_color_dict, type_nuc=type_nuc, prefix=legend_prefix, filetype=filetype, verbose=verbose) - - global t1 - - print "\n%s\n\nCreating %s selfdotplot images\n%s\n\n=>" % (50*"=", len(sequences), 28*"-"), - log_txt = "\n%s\n\nCreating %s selfdotplot images\n%s\n\n=>" % (50*"=", len(sequences), 28*"-") - - # preparations for file name - name_graph = "Selfdotplots" - if prefix != None: - if not prefix[-1] == "-": - prefix = prefix + "-" - else: - prefix = "" - suffix = "" - if convert_wobbles: - suffix += "_wobbles" - if substitution_count != 0: - suffix += "_S%d" % substitution_count - if multi: - suffix += "_collage" - - # calculate fig ratios - if not multi: - ncols = 1 - nrows = 1 - figsize_x, figsize_y = calc_fig_ratio(ncols, nrows, plot_size) - - P.cla() # clear any prior graph - if multi: - fig = P.figure(figsize=(figsize_x, figsize_y)) - page_counter = 1 - list_of_png_names = [] - - counter = 0 - for seq_name in sequences: - print seq_name, - log_txt += " " + seq_name - - counter += 1 - if not multi: - P.cla() # clear any prior graph - - # read sequence - seq_record = seq_dict[seq_name] - name_seq = seq_record.id - seq_one = seq_record.seq.upper() - length_seq = len(seq_one) - - # get positions of matches - if substitution_count != 0: - # print "RE" - x_lists, y_lists, x_lists_rc, y_lists_rc = find_match_pos_regex(seq_one, seq_one, wordsize, substitution_count=substitution_count, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, type_nuc=type_nuc, verbose=verbose) - else: - # print "DIAG", - x_lists, y_lists, x_lists_rc, y_lists_rc = find_match_pos_diag(seq_one, seq_one, wordsize, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, type_nuc=type_nuc, verbose=verbose) - - # plotting with matplotlib - ################################# - - # combined plotting - if multi: - # plotting subplot with matplotlib - ax = P.subplot(nrows, ncols, counter) # rows, columns, plotnumber - - # shade annotated regions - if gff_files != None and gff_files != []: - if seq_name in feat_dict.keys(): - features = feat_dict[seq_name] - for item in features: - feat_type, start, stop = item - feat_color, strength, zoom = gff_color_dict[feat_type.lower()] - start = max(0, start - zoom - 0.5) - stop = min(length_seq+1, stop + zoom + 0.5) - width = stop - start - ax.add_patch(patches.Rectangle((start, start), # (x,y) - width, width, # width, height - edgecolor=None, linewidth=line_width+zoom, - fill=True, facecolor=feat_color, - alpha=strength)) - - # collect lines - lines = [] - color_list = [] - for (x_lines, y_lines, col) in [(x_lists_rc, y_lists_rc, line_col_rev), (x_lists, y_lists, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # format axes - P.xlim(0, length_seq+1) - P.ylim(length_seq+1, 0) # rotate y axis (point downwards) - P.xlabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.ylabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - P.title(unicode_name(shorten_name(name_seq, max_len=title_length, title_clip_pos=title_clip_pos)), fontsize=label_size, fontweight='bold') - # P.title(unicode_name(name_seq), fontsize=label_size*1.3, fontweight='bold') - - # save figure and reinitiate if page is full - if counter == ncols * nrows: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - P.subplots_adjust(hspace=0.5, wspace=0.5) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' % (prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() - - list_of_png_names.append(fig_name) - - counter = 0 - page_counter += 1 - - fig = P.figure(figsize=(figsize_x, figsize_y)) - - # plotting separate figure files - else: # not multi - - fig = P.figure(figsize=(plot_size, plot_size)) # figure size needs to be a square - ax = P.subplot(1, 1, 1) # rows, columns, plotnumber - - # shade annotated regions - if gff_files != None and gff_files != []: - if seq_name in feat_dict.keys(): - features = feat_dict[seq_name] - for item in features: - feat_type, start, stop = item - feat_color, strength, zoom = gff_color_dict[feat_type.lower()] - start = max(0, start - zoom - 0.5) - stop = min(length_seq+1, stop + zoom + 0.5) - width = stop - start - ax.add_patch(patches.Rectangle((start, start), # (x,y) - width, width, # width, height - edgecolor=None, linewidth=line_width+zoom, - fill=True, facecolor=feat_color, - alpha=strength)) - - # collect lines - lines = [] - number = 0 - color_list = [] - for (x_lines, y_lines, col) in [(x_lists_rc, y_lists_rc, line_col_rev), (x_lists, y_lists, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # format axes - P.xlim(0, length_seq+1) - P.ylim(length_seq+1, 0) # rotate y axis (point downwards) - P.xlabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.ylabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - P.title(unicode_name(shorten_name(name_seq, max_len=title_length, title_clip_pos=title_clip_pos)), fontsize=label_size*1.3, fontweight='bold') - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s-%d_%s_wordsize%i%s.%s' %(prefix, name_graph, counter, shorten_name(name_seq, max_len=title_length, title_clip_pos=title_clip_pos), wordsize, suffix, filetype) - P.savefig(fig_name, bbox_inches='tight') - - P.close() - P.cla() # clear any prior graph - - list_of_png_names.append(fig_name) - - if multi and counter >= 1: - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - P.subplots_adjust(hspace=0.5, wspace=0.5) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' %(prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() # clear any prior graph - - list_of_png_names.append(fig_name) - - print "\n\nDrawing selfdotplots done" - log_txt += "\n\nDrawing selfdotplots done" - logprint(log_txt, start=False, printing=False) - - return list_of_png_names - -def pairdotplot(input_fasta, wordsize, prefix=None, plot_size=10, label_size=10, filetype='png', type_nuc=True, convert_wobbles=False, substitution_count=0, alphabetic_sorting=False, max_N_percentage=49, verbose=False, multi=True, ncols=4, nrows=5, length_scaling=True, scale_delim_col="red", title_length=float("Inf"), title_clip_pos="B"): - """ - pairwise dotplot (all-against-all) - """ - - # read sequences - seq_dict, sequences = read_seq(input_fasta) - if seq_dict == {}: - logprint("\nFailed to load sequences") - return [] - - if alphabetic_sorting: - sequences = sorted(sequences) - - # check if at least two input sequences - if len(sequences) < 2: - text = "\n%s\n\nCreating %d paired dotplot image \n%s\n\n=>" % (50*"=", len(sequences)*(len(sequences)-1)/2, 36*"-") - text += " Please provide at least two sequences for pairdotplot!\n\nTerminating paired dotplot!" - logprint(text, start=False, printing=True) - return - elif len(sequences) == 2 and multi: - text = "\n\nCreating collage output for single pairdotplot!" - text += "\nRecommendation: Change to individual mode by using '--collage_output n'!\n\n" - logprint(text, start=False, printing=True) - - if multi and (ncols == 0 or nrows == 0): - ncols = max(ncols, 1) - nrows = max(nrows, 1) - text = "\n\nPairdotplot Collage: Invalid collage settings - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - if multi and ncols > len(sequences)*(len(sequences)-1): - ncols = len(sequences) - nrows = 1 - text = "\n\nPairdotplot Collage: Few sequences - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - elif multi and ncols*(nrows-1) > len(sequences)*(len(sequences)-1): - nrows = ((len(sequences)-1) // ncols) + 1 - text = "\n\nPairdotplot Collage: Few sequences - correcting number of rows:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - - text = "\n%s\n\nCreating %d paired dotplot image for\n%s\n\n=>" % (50*"=", len(sequences)*(len(sequences)-1)/2, 36*"-") - text += ", ".join(sequences) + "\n" - logprint(text, start=False, printing=True) - - if multi and not (nrows == 1 and ncols == 1) and plot_size <= label_size/2: - label_size = plot_size * 3 // 2 - text = "Reducing label size for better visualization to %d\n" % label_size - logprint(text, start=False, printing=True) - - y_label_rotation = "vertical" - - # preparations for file name - name_graph = "Pairdotplot" - if prefix != None: - if not prefix[-1] == "-": - prefix = prefix + "-" - else: - prefix = "" - suffix = "" - if convert_wobbles: - suffix += "_wobbles" - if substitution_count != 0: - suffix += "_S%d" % substitution_count - if length_scaling: - suffix += "_scaled" - if multi: - suffix += "_collage" - - # calculate fig ratios - if not multi: - ncols = 1 - nrows = 1 - figsize_x, figsize_y = calc_fig_ratio(ncols, nrows, plot_size) - - P.cla() # clear any prior graph - list_of_png_names = [] - if multi: - fig = P.figure(figsize=(figsize_x, figsize_y)) - page_counter = 1 - - # prepare LCS data file - lcs_data_file = open("%sPairdotplot_lcs_data_file%s.txt" % (prefix, suffix.replace("_scaled", "").replace("_collage", "")), 'w') - lcs_data_file.write("\t".join(["#title1", "title2", "len_seq1", "len_seq2", "len_lcs_for", "%_min_seq_len", "len_lcs_rev", "%_min_seq_len"])+"\n") - - counter, seq_counter = 0, 0 - print "Drawing pairwise dotplot...", - log_txt = "Drawing pairwise dotplot..." - if verbose: - seq_text = "" - for idx in range(len(sequences)-1): - if verbose: - print "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]), - seq_text += "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]) - rec_two = seq_dict[sequences[idx]] - name_two = rec_two.id - seq_two = rec_two.seq - len_two = len(seq_two) - - for jdx in range(idx+1, len(sequences)): - rec_one = seq_dict[sequences[jdx]] - name_one = rec_one.id - seq_one = rec_one.seq - len_one = len(seq_one) - - counter += 1 - seq_counter += 1 - if verbose: - print sequences[jdx], - seq_text += " " + sequences[jdx] - elif not seq_counter % 25: - print seq_counter, - log_txt += " " + str(seq_counter) - - # get positions of matches - if substitution_count != 0: - # print "RE" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_regex(seq_one, seq_two, wordsize, substitution_count=substitution_count, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - else: - # print "DIAG" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_diag(seq_one, seq_two, wordsize, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - - # write LCS data file - lcs_data_file.write("\t".join([name_one, name_two, str(len_one), str(len_two), - str(lcs_for), str(round((lcs_for*100./min(len_one, len_two)), 3)), - str(lcs_rev), str(round((lcs_rev*100./min(len_one, len_two)), 3))]) + "\n") - - - # plotting with matplotlib - ################################# - - # combined plotting - if multi: - # plotting subplot with matplotlib - ax = P.subplot(nrows, ncols, counter) # rows, columns, plotnumber - else: - # calculate figure size for separate figures - if len_one >= len_two: - sizing = (plot_size, max(2, (plot_size)*len_two*1./len_one)) - # sizing = (plot_size, min(plot_size, max(2, (plot_size-2)*len_two*1./len_one+2))) - else: - sizing = (max(2, (plot_size)*len_one*1./len_two), plot_size) - # sizing = (min(plot_size, max(2, (plot_size-2)*len_one*1./len_two+2)), plot_size) - fig = P.figure(figsize=(plot_size, plot_size)) - - ax = P.subplot(1, 1, 1) - - # collect lines - lines = [] - color_list = [] - for (x_lines, y_lines, col) in [(x2, y2, line_col_rev), (x1, y1, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # format axes - P.xlabel(unicode_name(shorten_name(name_one, max_len=title_length, title_clip_pos=title_clip_pos)) + " [%s]" % aa_bp_unit, fontsize=label_size, fontweight='bold', labelpad=4) - P.ylabel(unicode_name(shorten_name(name_two, max_len=title_length, title_clip_pos=title_clip_pos)) + " [%s]" % aa_bp_unit, fontsize=label_size, fontweight='bold', labelpad=4) - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - - if not multi: - if length_scaling: - ax.set_aspect(aspect='equal', adjustable='box', anchor='NW') - P.xlim(0, len_one+1) - P.ylim(len_two+1, 0) # rotate y axis (point downwards) - elif not length_scaling: - P.xlim(0, len_one+1) - P.ylim(len_two+1, 0) # rotate y axis (point downwards) - else: - max_len = max(len_one, len_two) - P.xlim(0, max_len+1) - P.ylim(max_len+1, 0) # rotate y axis (point downwards) - - # plot line deliminating shorter sequence - if max_len != len_one: - ax.plot((len_one+1, len_one+1), (0, len_two), marker="", linestyle="--", color=scale_delim_col, markerfacecolor="r") - if max_len != len_two: - ax.plot((0, len_one), (len_two+1, len_two+1), marker="", linestyle="--", color=scale_delim_col, markerfacecolor="r") - - # evtl. switch x axis position - if x_label_pos_top: - ax.xaxis.tick_top() - ax.xaxis.set_label_position('top') - P.setp(ax.get_xticklabels(), fontsize=label_size*.9) - P.setp(ax.get_yticklabels(), fontsize=label_size*.9) - - # save figure and reinitiate if page is full - if multi and counter == ncols * nrows: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - if x_label_pos_top: - P.subplots_adjust(hspace=.5, wspace=.5, top=0.95) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=.5, wspace=.5, bottom=0.05) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' %(prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() - - list_of_png_names.append(fig_name) - - counter = 0 - page_counter += 1 - - fig = P.figure(figsize=(figsize_x, figsize_y)) - - # plotting separate figure files - elif not multi: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - if y_label_rotation == "horizontal": - if x_label_pos_top: - P.subplots_adjust(hspace=0.02, wspace=0.02, left=0.13, top=0.95) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=0.02, wspace=0.02, left=0.13, bottom=0.05) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=0.02, wspace=0.02) # space between rows - def 0.4 - - # name and create output files - fig_name = '%s%s-%d_wordsize%i%s.%s' % (prefix, name_graph, counter, wordsize, suffix, filetype) - P.savefig(fig_name) - P.close() - P.cla() - - list_of_png_names.append(fig_name) - fig = P.figure() - - # save figure - if multi and counter >= 1: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - if x_label_pos_top: - P.subplots_adjust(hspace=0.5, wspace=0.5, top=0.95) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=0.5, wspace=0.5, bottom=0.05) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' %(prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() - - list_of_png_names.append(fig_name) - - if not verbose: - print seq_counter, "done" - log_txt += str(seq_counter) + " done" - else: - print "\n%d done" % seq_counter - log_txt += "\n%d done" % seq_counter - logprint(log_txt, start=False, printing=False) - - if verbose: - print - logprint(seq_text, start=False, printing=False) - - return list_of_png_names - -def polydotplot(input_fasta, wordsize, prefix=None, plot_size=10, label_size=10, filetype='png', type_nuc=True, convert_wobbles=False, substitution_count=0, alphabetic_sorting=False, max_N_percentage=49, verbose=False, lcs_shading=True, lcs_shading_ref=0, lcs_shading_interval_len=100, lcs_shading_ori=0, lcs_shading_num=5, spacing=0.04, input_user_matrix_file="", user_matrix_print=True, gff_files=[], gff_color_dict={"others": ("grey", 1, 0)}, title_length=float("Inf"), title_clip_pos="B", rotate_labels=False): - """ - all-against-all dotplot - derived from dotplot function - - lcs_shading_refs: - 0 color relative to maximum lcs observed in dataset [default] - 1 color by coverage of shorter sequence (e.g. lcs = 70% of seq1) - lcs_shading_ori - 0 forward only - 1 reverse only - 2 both orientations (in opposite plot) - """ - - # read sequences - seq_dict, sequences = read_seq(input_fasta) - if seq_dict == {}: - logprint("\nFailed to load sequences") - return [] - - if alphabetic_sorting: - sequences = sorted(sequences) - - if len(sequences) == 0: - text = "\n%s\n\nCreating %dx%d polydotplot image\n%s\n\n=>" % (50*"=", len(sequences), len(sequences), 30*"-") - text += " No sequences provided for polydotplot!\n\nTerminating polydotplot!" - logprint(text, start=False, printing=True) - return - elif len(sequences) == 1: - text = "\n\nCreating polydotplot for single sequence!" - text += "\nRecommendation: Use selfdotplot via '--plotting_mode 0'!\n\n" - logprint(text, start=False, printing=True) - - text = "\n%s\n\nCreating %dx%d polydotplot image\n%s\n\n=>" % (50*"=", len(sequences), len(sequences), 30*"-") - text += " " + " ".join(sequences) + "\n" - logprint(text, start=False, printing=True) - - # read gff annotation data if provided for shading - if gff_files != None and gff_files != []: - text = "\n%s\n\nReading %s GFF annotation files\n%s\n\n=> %s\n" % (50*"=", len(gff_files), 28*"-", ", ".join(gff_files)) - logprint(text, start=False, printing=True) - if prefix != None and prefix != "": - legend_prefix = prefix + "-Polydotplot" - else: legend_prefix = "Polydotplot" - feat_dict = read_gffs(gff_files, color_dict=gff_color_dict, type_nuc=type_nuc, prefix=legend_prefix, filetype=filetype, verbose=verbose) - - if lcs_shading and not type_nuc: - if lcs_shading_ori != 0: - lcs_shading_ori = 0 - text = "Protein shading does not support reverse complementary matching!\n" - logprint(text, start=False, printing=True) - - # read custom shading matrix & match names of sequences to fasta - if input_user_matrix_file != "" and input_user_matrix_file != None: - logprint("Reading user matrix file: %s" % input_user_matrix_file) - # lcs_shading_ori = 2 - custom_dict = read_matrix(input_user_matrix_file) - if custom_dict != {}: - custom_shading = True - custom_similarity_dict = {} - invalid_entries = [] - custom_max = 0 - custom_min = float("Inf") - for key in custom_dict.keys(): - number_key = [] - - # convert number into float - try: - value = float(custom_dict[key]) - if not "." in custom_dict[key]: - value = int(custom_dict[key]) - custom_max = max(custom_max, value) - custom_min = min(custom_min, value) - except: - value = custom_dict[key] - if value == "": - value = None - invalid_entries.append(key) - # match matrix names with sequence names - for item in key: - if item in sequences: - number_key.append(sequences.index(item)) - else: - number_key.append(-1) - # dictionary with tuple of sorted sequence indices as key and number as value - custom_similarity_dict[tuple(sorted(number_key))] = value - if len(invalid_entries) != 0: - text = "No valid number in custom similarity matrix for %d entries: \n\t" % (len(invalid_entries)) - for key in invalid_entries: - text += str(key) + " - " + str(custom_dict[key]) + "; " - logprint(text[:-2]+"\n") - - text = "Custom user matrix given: min %.2f, max %.2f\n" % (custom_min, custom_max) - - # artificially rounding intervals if likely identity/divergence percentages - if 0 <= custom_min < 1 and 0 < custom_max <= 1: - rounding_factor = 5 - multi_factor = 100 - text += " > artificially rounding custom shading intervals: old (%.2f, %.2f) - " % (custom_min, custom_max) - custom_min = max(0, (multi_factor*custom_min // rounding_factor) * (1.*rounding_factor/multi_factor)) - custom_max = min((multi_factor*custom_max // rounding_factor) * (1.*rounding_factor/multi_factor), 1) - text += "new (%.2f, %2f)\n" % (custom_min, custom_max) - - elif 0 <= custom_min < 100 and 0 < custom_max <= 100: - rounding_factor = 5 - text += " > artificially rounding custom shading intervals: old (%.2f, %.2f) - " % (custom_min, custom_max) - custom_min = max(0, (custom_min // rounding_factor) * rounding_factor) - custom_max = min((custom_max // rounding_factor) * rounding_factor, 100) - text += "new (%d, %d)\n" % (custom_min, custom_max) - - logprint(text) - - else: - custom_shading = False - - name_graph = "Polydotplot" - suffix = "" - if convert_wobbles: - suffix += "_wobbles" - if substitution_count != 0: - suffix += "_S%d" % substitution_count - if custom_shading: - suffix += "_matrix" - if lcs_shading: - suffix += "_%dshades_ref%d_ori%s" % (lcs_shading_num+1, lcs_shading_ref, lcs_shading_ori) - if "ref2" in suffix and type_nuc: - suffix = suffix.replace("ref2", "%dbp" % lcs_shading_interval_len) - elif "ref2" in suffix: - suffix = suffix.replace("ref2", "%daa" % lcs_shading_interval_len) - - - # name and create output files (names derived from SEQNAME) - if prefix != None and str(prefix) != "": - prefix = str(prefix) + "-" - else: - prefix = "" - - # preparations for background shading - if lcs_shading or custom_shading: - # create color range white to grey - colors = create_color_list(lcs_shading_num+1, color_map=None, logging=True) - colors_2 = create_color_list(lcs_shading_num+1, color_map="OrRd", logging=True) - - if custom_shading: - text = "Custom Matrix Colors: " + ", ".join(colors_2) - - # write lcs lengths to file - lcs_data_file = open("%sPolydotplot_lcs_data_file%s.txt" % (prefix, suffix.replace("_scaled", "").replace("_collage", "")), 'w') - lcs_data_file.write("\t".join(["#title1", "title2", "len_seq1", "len_seq2", "len_lcs_for", "%_min_seq_len", "len_lcs_rev", "%_min_seq_len"])+"\n") - - # compare sequences pairwise - save lcs and line information in dictionary for plotting - data_dict = {} # keys = tuple(idx, jdx), value = x1, y1, x2, y2 (line positions) - lcs_dict = {} # keys = tuple(idx, jdx), value = length of lcs: lcs_len or (lcs_for, lcs_rev) - for_lcs_set = set([]) # keep lengths to calculate max (excluding self comparisons) - rev_lcs_set = set([]) # keep lengths to calculate max (all) - - text = "\nTotal plot count: %d" % (len(sequences)*(len(sequences))) - text += "\nTotal calculations: %d" % (len(sequences)*(len(sequences)+1)/2) - logprint(text, start=False, printing=True) - - print "\nCalculating shared regions and lengths of longest_common_substring...", - log_txt = "\nCalculating shared regions and lengths of longest_common_substring..." - # determine matches and length of lcs by comparing all sequence pairs - if verbose: - seq_text = "" - counter = 0 - for idx in range(len(sequences)): - if verbose: - print "\n%d\t%s vs." % ((counter+1), sequences[idx]), - seq_text += "\n%d\t%s vs." % ((counter+1), sequences[idx]) - rec_two = seq_dict[sequences[idx]] - name_two = rec_two.id - seq_two = rec_two.seq - len_two = len(seq_two) - - for jdx in range(idx, len(sequences)): - rec_one = seq_dict[sequences[jdx]] - name_one = rec_one.id - seq_one = rec_one.seq - len_one = len(seq_one) - - counter += 1 - if verbose: - print sequences[jdx], - seq_text += " " + sequences[jdx] - elif len(sequences) < 5: - print "\t%s (%d %s), %s (%d %s)" % (name_one, len_one, aa_bp_unit, name_two, len_two, aa_bp_unit) - log_txt += "\t%s (%d %s), %s (%d %s)\n" % (name_one, len_one, aa_bp_unit, name_two, len_two, aa_bp_unit) - else: - if not counter % 25: - print counter, - log_txt += str(counter) - - # get positions of matches & length of longest common substring based on match lengths - if substitution_count != 0: - # print "RE" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_regex(seq_one, seq_two, wordsize, substitution_count=substitution_count, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - else: - # print "DIAG" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_diag(seq_one, seq_two, wordsize, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - data_dict[(idx, jdx)] = x1[:], y1[:], x2[:], y2[:] - lcs_dict[idx, jdx] = lcs_for, lcs_rev - - if idx != jdx: - for_lcs_set.add(lcs_for) - rev_lcs_set.add(lcs_rev) - - lcs_data_file.write("\t".join([name_one, name_two, str(len_one), str(len_two), - str(lcs_for), str(round((lcs_for*100./min(len_one, len_two)), 3)), - str(lcs_rev), str(round((lcs_rev*100./min(len_one, len_two)), 3))]) + "\n") - - if not verbose: - print len(sequences)*(len(sequences)+1)/2, " done\n" - log_txt += str(len(sequences)*(len(sequences)+1)/2) + " done\n" - else: - print "\n%d done" % (len(sequences)*(len(sequences)+1)/2) - log_txt += "\n%d done" % (len(sequences)*(len(sequences)+1)/2) - logprint(log_txt, start=False, printing=False) - - if verbose: - logprint ("\n\nlcs_dict\n" + str(lcs_dict)) - if custom_shading: - logprint ("\ncustom_dict\n" + str(custom_dict)) - logprint ("\ncustom_similarity_dict\n\n" + str(custom_similarity_dict)) - - if verbose: - print - logprint(seq_text+"\n", start=False, printing=False) - - if lcs_shading_ref == 2: - color_bins = [] - text = "\nLCS lengh bins: " - for idx in range(lcs_shading_num): - color_bins.append(lcs_shading_interval_len*(idx+1)) - text += " " + str(lcs_shading_interval_len*(idx+1)) - logprint(text, start=False, printing=True) - - # calculate maximum lcs length - if lcs_shading_ori == 0: # forward only - if len(for_lcs_set) != 0: - max_lcs = max(for_lcs_set) - else: - max_lcs = None - elif lcs_shading_ori == 1: # reverse complement only - if len(rev_lcs_set) != 0: - max_lcs = max(rev_lcs_set) - else: - max_lcs = None - else: # both orientations - if len(rev_lcs_set) != 0 and len(for_lcs_set) != 0: - max_lcs = max(max(rev_lcs_set), max(for_lcs_set)) - elif len(rev_lcs_set) != 0: - max_lcs = max(rev_lcs_set) - elif len(for_lcs_set) != 0: - max_lcs = max(for_lcs_set) - else: - max_lcs = None - - if not max_lcs == None: - text = "Maximum LCS: %d %s" % (max_lcs, aa_bp_unit) - logprint(text, start=False, printing=True) - if custom_shading: - text = "Maximum custom value: %d\n" % custom_max - logprint(text, start=False, printing=True) - - # count sequences - ncols = len(sequences); nrows = len(sequences) - - # get sequence lengths to scale plot widths and heights accordingly - size_ratios = [] - for item in sequences: - size_ratios.append(len(seq_dict[item].seq)) - - P.cla() # clear any prior graph - # use GridSpec to resize plots according to sequence length - gs = gridspec.GridSpec(nrows, ncols, - width_ratios=size_ratios, - height_ratios=size_ratios) - fig = P.figure(figsize=(plot_size, plot_size)) - - # determine label orientations - if len(sequences) > 5 or rotate_labels: - x_label_rotation = 45 - y_label_rotation = "horizontal" - if x_label_pos_top: - xhalign = 'left' - xvalign = 'bottom' - else: - xhalign = 'right' - xvalign = 'top' - yhalign = "right" - else: - x_label_rotation = "horizontal" - y_label_rotation = "vertical" - xvalign = "center" - xhalign = "center" - yhalign = "center" - yvalign = 'center' - - print "\nDrawing polydotplot...", - log_txt = "\nDrawing polydotplot..." - - # draw subplots - if verbose: - if lcs_shading and custom_shading: - lcs_text = "\n" + "\t".join(["#Seq1", "Seq2", "LCS for [%s]" %aa_bp_unit, "LCS for [%s]" %aa_bp_unit, "Custom matrix value", "Matrix color index", "LCS color index"]) + "\n" - elif lcs_shading: - lcs_text = "\n" + "\t".join(["#Seq1", "Seq2", "LCS for [%s]" %aa_bp_unit, "LCS for [%s]" %aa_bp_unit, "LCS color index for", "LCS color index rev"]) + "\n" - elif custom_shading: - lcs_text = "\n" + "\t".join(["#Seq1", "Seq2", "Custom matrix value", "Color index for", "Color index rev"]) + "\n" - - if verbose: - seq_text = "" - counter, seq_counter = 0, 0 - for idx in range(len(sequences)): - if verbose: - print "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]), - seq_text += "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]) - rec_two = seq_dict[sequences[idx]] - len_two = len(rec_two.seq) - name_two = rec_two.id - - for jdx in range(idx, len(sequences)): - rec_one = seq_dict[sequences[jdx]] - len_one = len(rec_one.seq) - name_one = rec_one.id - - counter += 1 - seq_counter += 1 - if verbose: - print sequences[jdx], - seq_text += " " + sequences[jdx] - elif not seq_counter % 25: - print seq_counter, - log_txt += str(seq_counter) - - # optional shade background according to length of LCS and/or user matrix - ######################################################################### - - # get interval based on LCS - background_colors = [None, None] - if lcs_shading and (lcs_shading_ref==1 or lcs_shading_ref==2 or max_lcs!=None): # self plot max_lcs_for == None - lcs_len = lcs_dict[(idx, jdx)] - l1 = lcs_len[0] # forward - l2 = lcs_len[1] # reverse complement - - lcs_shading_bool = True - - # calculate shading acc. to chosen option - if lcs_shading_ref == 1: # percentage of shorter sequence - color_idx0 = min(len(colors)-1, l1*lcs_shading_num // min(len_one, len_two)) - color_idx1 = min(len(colors)-1, l2*lcs_shading_num // min(len_one, len_two)) - elif lcs_shading_ref == 2: # by given interval size - color_idx0 = min(len(colors)-1, l1 // lcs_shading_interval_len) - color_idx1 = min(len(colors)-1, l2 // lcs_shading_interval_len) - if color_idx0 >= len(colors): - color_idx0 = len(colors) - if color_idx1 >= len(colors): - color_idx1 = len(colors) - else: # percentage of maximum lcs length - color_idx0 = min(len(colors)-1, l1*lcs_shading_num // max_lcs) - color_idx1 = min(len(colors)-1, l2*lcs_shading_num // max_lcs) - else: - lcs_shading_bool = False - - # get interval based on custom matrix - if custom_shading: - # matrix value - try: - custom_value = custom_similarity_dict[(idx, jdx)] - except: - custom_value = "" - - # bottom left triangle = LCS forward/reverse or best of both - if lcs_shading_bool: - if lcs_shading_ori == 0: # forward - color_idx1 = color_idx0 - elif lcs_shading_ori == 2: # both directions - color_idx1 = max(color_idx0, color_idx1) - - # top right triangle = custom value (not colored if text matrix provided) - if type(custom_value) == int or type(custom_value) == float: - color_idx0 = int((custom_value-custom_min)*lcs_shading_num // (custom_max-custom_min)) - # if string is proviced - else: - color_idx0 = 0 - - # set colors dependent on lcs dependent on orientation - if lcs_shading_bool and not custom_shading: - if idx != jdx: - if lcs_shading_ori == 0: - color_idx1 = color_idx0 - elif lcs_shading_ori == 1: - color_idx0 = color_idx1 - background_colors[0] = colors[color_idx0] - background_colors[1] = colors[color_idx1] - # for selfcomparison, only color reverse complement - elif lcs_shading_ori != 0 and not custom_shading: - background_colors[0] = colors[color_idx1] - # set different colors for shading by LCS + user matrix - elif lcs_shading_bool and custom_shading: - # print colors, background_colors, color_idx0, color_idx1 - background_colors[0] = colors_2[color_idx0] - background_colors[1] = colors[color_idx1] - # set grey color range for user matrix if no LCS shading - elif custom_shading: - background_colors[0] = colors[color_idx0] - background_colors[1] = colors[color_idx0] - - if verbose: - if custom_shading and lcs_shading_bool: - lcs_text += "\t".join([name_one, name_two, str(lcs_len[0]), str(lcs_len[1]), str(custom_value), str(color_idx0), str(color_idx1)]) + "\n" - elif lcs_shading_bool: - lcs_text += "\t".join([name_one, name_two, str(lcs_len[0]), str(lcs_len[1]), str(color_idx0), str(color_idx1)]) + "\n" - elif custom_shading: - lcs_text += "\t".join([name_one, name_two, str(custom_value), str(color_idx0), str(color_idx1)]) + "\n" - - # diagonal (self-dotplots) - if idx == jdx: - # skip positions below diagonal - counter = counter + (counter - 1) // (nrows) # + row_pos - counters = [counter] - # draw both graphs at once (due to symmetry) - else: - col_pos = (counter - 1) % ncols - row_pos = (counter - 1) // (nrows) - counter2 = col_pos * ncols + row_pos + 1 - counters = [counter, counter2] - - if len(counters) == 2: - seq_counter += 1 - if not verbose and not seq_counter % 25: - print seq_counter, - log_txt += str(seq_counter) - - x_lists, y_lists, x_lists_rc, y_lists_rc = data_dict[(idx, jdx)] - - # plot diagram(s) - for kdx in range(len(counters)): - - fig_pos = counters[kdx] - # plotting subplot with matplotlib - ax = P.subplot(gs[fig_pos-1]) # rows, columns, plotnumber - - # shade annotated regions if gff file(s) provided - if idx == jdx and gff_files != None and gff_files != []: - if name_one in feat_dict.keys(): - features = feat_dict[name_one] - if len_two != len_one: - logprint("Polydot GFF shading for diagonal fields - nequal length error!") - return - for item in features: - feat_type, start, stop = item - feat_color, strength, zoom = gff_color_dict[feat_type.lower()] - start = max(0, start - zoom - 0.5) - stop = min(len_one+1, stop + zoom + 0.5) - width = stop - start - ax.add_patch(patches.Rectangle((start, start), # (x,y) - width, width, # width, height - edgecolor=None, linewidth=line_width+zoom, - fill=True, facecolor=feat_color, - alpha=strength)) - - # if custom matrix value printed into upper matrix triangle, skip data plotting - # text print in top triangle - if user_matrix_print and custom_shading and kdx==0 and idx!=jdx: - data_plotting = False - # dotplot in bottom triangle - else: - data_plotting = True - - # mirror plot, if plotting below diagonal - if kdx == 0: - l1, l2 = len_one, len_two - n1, n2 = name_one, name_two - x1, y1 = x_lists, y_lists - x2, y2 = x_lists_rc, y_lists_rc - else: - l2, l1 = len_one, len_two - n2, n1 = name_one, name_two - x1, y1 = y_lists, x_lists - x2, y2 = y_lists_rc, x_lists_rc - - if data_plotting: - # collect lines - lines = [] - color_list = [] - for (x_lines, y_lines, col) in [(x2, y2, line_col_rev), (x1, y1, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # plot value provided by customer instead of dotplot - else: - alignment = {'horizontalalignment': 'center', 'verticalalignment': 'center'} - # P.text(0.5, 0.5, custom_value, size='medium', transform=ax.transAxes, **alignment) - P.text(0.5, 0.5, custom_value, size=label_size*1.5, transform=ax.transAxes, **alignment) - # P.text(0.5, 0.5, custom_value, size=label_size*1.5, transform=ax.transAxes, - # horizontalalignment='center', verticalalignment='center', color="black") - - if custom_shading: - # omit diagonal - if idx == jdx: - ax.set_facecolor("white") - # use white background for text fields (top right triangle only [kdx 0]) - elif type(custom_value) != int and type(custom_value) != float and kdx == 0: - ax.set_facecolor("white") - else: - ax.set_facecolor(background_colors[kdx]) - # set background color if lcs shading - elif lcs_shading_bool and background_colors[kdx] != None: - ax.set_facecolor(background_colors[kdx]) - - # set axis limits - P.xlim(0, l1+1) - P.ylim(l2+1, 0) # rotate y axis (point downwards) - - # determine axis positions - if x_label_pos_top: - ax.xaxis.tick_top() - ax.xaxis.set_label_position('top') - x_label_bool = fig_pos <= ncols - x_tick_bool = fig_pos > ncols*(ncols-1) - else: - x_label_bool = fig_pos > ncols*(ncols-1) - x_tick_bool = fig_pos <= ncols - - # x axis labels dependent on plot position/number - if x_label_bool: # x title and labels on top or bottom - P.xlabel(unicode_name(shorten_name(n1, max_len=title_length, title_clip_pos=title_clip_pos)), fontsize=label_size, rotation=x_label_rotation, verticalalignment=xvalign, horizontalalignment=xhalign, fontweight='bold', labelpad=8) # axis naming - if not x_label_rotation in ["horizontal", "vertical"]: - P.setp(ax.get_xticklabels(), fontsize=label_size*.9, rotation="vertical") - else: - P.setp(ax.get_xticklabels(), fontsize=label_size*.9, rotation=x_label_rotation) - elif x_tick_bool and x_label_pos_top: # x ticks on bottom row - ax.xaxis.tick_bottom() # ticks without labels on bottom - P.setp(ax.get_xticklabels(), fontsize=label_size, rotation=x_label_rotation, visible=False) - elif x_tick_bool: # x ticks on top row - ax.xaxis.tick_top() # # ticks without labels on top - P.setp(ax.get_xticklabels(), fontsize=label_size, rotation=x_label_rotation, visible=False) # inner diagrams without labelling - else: # no x ticks on internal rows - ax.axes.get_xaxis().set_visible(False) - - # y axis labels dependent on plot position/number - if fig_pos % ncols == 1 or (ncols == 1 and nrows == 1): # y title and labels in 1st column - P.ylabel(unicode_name(shorten_name(n2, max_len=title_length, title_clip_pos=title_clip_pos)), fontsize=label_size, rotation=y_label_rotation, verticalalignment=yvalign, horizontalalignment=yhalign, fontweight='bold', labelpad=8) - P.setp(ax.get_yticklabels(), fontsize=label_size*.9) # axis naming - elif fig_pos % ncols == 0: # y ticks in last column - ax.yaxis.tick_right() - P.setp(ax.get_yticklabels(), visible=False) # inner diagrams without labelling - else: - ax.axes.get_yaxis().set_visible(False) - - if not verbose: - print seq_counter, "done" - log_txt += str(seq_counter) + " done" - else: - print "\n%d done" % seq_counter - log_txt += "\n%d done" % seq_counter - logprint(log_txt, start=False, printing=False) - - if verbose: - try: - logprint(lcs_text, start=False, printing=True) - except: - pass - - # finalize layout - margins & spacing between plots - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - # gs.tight_layout(fig, h_pad=.02, w_pad=.02) # less overlapping tick labels, but also disturbingly large spacing - if y_label_rotation == "horizontal": - if x_label_pos_top: - P.subplots_adjust(hspace=spacing, wspace=spacing, left=0.13, top=0.87) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=spacing, wspace=spacing, left=0.13, bottom=0.13) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=spacing, wspace=spacing) # space between rows - def 0.4 - - # save figure and close instance - fig_name = '%s%s_wordsize%i%s.%s' % (prefix, name_graph, wordsize, suffix, filetype) - P.savefig(fig_name) - P.close() - P.cla() - - - # create figure color legend - if lcs_shading: - if lcs_shading_ref == 1: # percentage of shorter sequence - legend_file_name = legend_figure(colors, lcs_shading_num, unit="%", filetype=filetype, prefix=prefix) - elif lcs_shading_ref == 2: # interval sizes - legend_file_name = legend_figure(colors, lcs_shading_num, unit=aa_bp_unit, filetype=filetype, prefix=prefix, bins=color_bins) - else: # relative of maximum lcs - legend_file_name = legend_figure(colors, lcs_shading_num, unit=aa_bp_unit, filetype=filetype, prefix=prefix, max_lcs_len=max_lcs) - - if custom_shading: - custom_prefix = "custom-matrix-" + prefix - legend_file_name_custom = legend_figure(colors_2, lcs_shading_num, unit="%", filetype=filetype, prefix=custom_prefix, max_lcs_len=custom_max, min_lcs_len=custom_min) - - if lcs_shading and custom_shading: - return [fig_name, legend_file_name, legend_file_name_custom] - elif lcs_shading: - return [fig_name, legend_file_name] - elif custom_shading: - return [fig_name, legend_file_name_custom] - else: - return [fig_name] - - -############################### -# Function Call # -############################### - -def main(seq_list, wordsize, modes=[0, 1, 2], prefix=None, plot_size=10, label_size=10, filetype="png", type_nuc=True, convert_wobbles=False, substitution_count=0, rc_option=True, alphabetic_sorting=False, gff=None, multi=True, ncols=1, nrows=1, lcs_shading=True, lcs_shading_num=5, lcs_shading_ref=0, lcs_shading_interval_len=100, lcs_shading_ori=0, gff_color_config_file="", input_user_matrix_file="", user_matrix_print=False, length_scaling=True, title_length=50, title_clip_pos="B", spacing=0.04, max_N_percentage=49, verbose=False): - - global t1, line_col_rev - - # check input variables - if convert_wobbles and max_N_percentage > 49: - max_N_percentage = 49 - if type_nuc: - ambiq_res = "N" - else: - ambiq_res = "X" - text = "Provide valid max_N_percentage, kmers with >50%% %ss are ignored\n" % (ambiq_res) - logprint(text, start=False, printing=True) - - if filetype not in ["png", "pdf", "svg"]: - text = "Provide valid file type - png, pdf, or svg - given:%s\n" % filetype - logprint(text, start=False, printing=True) - filetype = "png" - - # read gff color config file if provided - if len(input_gff_files) != 0 and input_gff_files != None: - if gff_color_config_file not in ["", None]: - text = "\n%s\n\nReading GFF color configuration file\n%s\n\n=> %s\n" % (50*"=", 28*"-", gff_color_config_file) - logprint(text, start=False, printing=True) - gff_feat_colors = read_gff_color_config(gff_color_config_file) - else: - gff_feat_colors = {} - if gff_color_config_file not in ["", None]: - text = "Please provide GFF annotation files to use configuration file", gff_color_config_file - logprint(text, start=False, printing=True) - - # if color is set to white, reverse complementary matches are skipped - if not rc_option: - line_col_rev = "white" # reverse matches not calculated - elif not type_nuc: - logprint("Reverse complement deactivated for proteins!") - line_col_rev = "white" # reverse matches not calculated - - mode_text = [] - for item in modes: - mode_text.append(str(item)) - text = "%s\n\nRunning plotting modes %s" % (50*"=", ", ".join(mode_text)) - logprint(text, start=False, printing=True) - - - # create dotplots - ########################################## - - # self dotplots - t1 = time.time() - if 0 in modes: - list_of_png_names = selfdotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, title_clip_pos=title_clip_pos, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, multi=multi, ncols=ncols, nrows=nrows, gff_files=gff, gff_color_dict=gff_feat_colors, max_N_percentage=max_N_percentage, verbose=verbose) - t1 = time_track(t1) - if list_of_png_names != [] and list_of_png_names != None: - text = "-> Image file(s): %s\n" % ", ".join(list_of_png_names) - else: - text = "No image files were created!\n" - logprint(text, start=False, printing=True) - logprint(50*"=") - - # paired dotplots - if 1 in modes: - if multi: - list_of_png_names = pairdotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, title_clip_pos=title_clip_pos, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, multi=multi, ncols=ncols, nrows=nrows, length_scaling=length_scaling, max_N_percentage=max_N_percentage, verbose=verbose) - t1 = time_track(t1) - else: - if not length_scaling: - text = "\nPairwise dotplot with individual output files scaled by sequence length automatically!" - logprint(text, start=False, printing=True) - list_of_png_names = pairdotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, title_clip_pos=title_clip_pos, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, multi=multi, ncols=ncols, nrows=nrows, length_scaling=True, verbose=verbose) - t1 = time_track(t1) - if list_of_png_names != [] and list_of_png_names != None: - text = "-> Image file(s): %s\n" % ", ".join(list_of_png_names) - else: - text = "No image files were created!\n" - logprint(text, start=False, printing=True) - logprint(50*"=") - - # all-against-all dotplot - if 2 in modes: - list_of_png_names = polydotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, title_clip_pos=title_clip_pos, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, lcs_shading=lcs_shading, lcs_shading_num=lcs_shading_num, lcs_shading_ref=lcs_shading_ref, lcs_shading_interval_len=lcs_shading_interval_len, lcs_shading_ori=lcs_shading_ori, input_user_matrix_file=input_user_matrix_file, user_matrix_print=user_matrix_print, spacing=spacing, gff_files=gff, gff_color_dict=gff_feat_colors, max_N_percentage=max_N_percentage, verbose=verbose) - t1 = time_track(t1) - if list_of_png_names != [] and list_of_png_names != None: - text = "-> Image file(s): %s\n" % ", ".join(list_of_png_names) - else: - text = "No image files were created!\n" - logprint(text, start=False, printing=True) - logprint(50*"=") - - text = "\n" + 50 * "#" + "\n" + 50 * "#" - text += "\n\nThank you for using FlexiDot!\n" - logprint(text, start=False, printing=True) - -# testing mode for debugging -trial_mode = False -# trial_mode = True - -# parameters = check_input(sys.argv) -parameters = check_input(sys.argv, trial_mode=trial_mode) - -# read out parameters -commandline, auto_fas, input_fasta, output_file_prefix, collage_output, m_col, n_row, filetype, type_nuc, input_gff_files, gff_color_config_file, wordsize, plotting_modes, wobble_conversion, substitution_count, rc_option, alphabetic_sorting, lcs_shading, lcs_shading_num, lcs_shading_ref, lcs_shading_interval_len, lcs_shading_ori, input_user_matrix_file, user_matrix_print, plot_size, line_width, line_col_for, line_col_rev, x_label_pos_top, label_size, spacing, length_scaling, title_length, title_clip_pos, max_N_percentage, verbose = parameters - -# evtl. overwrite parameters for testing purposes in trial mode -if trial_mode: - input_fasta = ["test-sequences-8.fas"] - input_gff_files = ["Seq2_annotations.gff3"] - # input_user_matrix_file = "matrix.txt" - # user_matrix_print = True - output_file_prefix = "#GFF_poly" - plot_size = 10 - plotting_modes = [0,1,2] - plotting_modes = [2] - lcs_shading = False - lcs_shading = True - lcs_shading_ref = 2 - lcs_shading_num = 4 - lcs_shading_ori = 0 - lcs_shading_interval_len = 15 - wordsize = 10 - wordsize = 7 - x_label_pos_top = True - filetype = "pdf" - filetype = "png" - - wobble_conversion = False - wobble_conversion = True - - substitution_count = 0 - - rc_option = True - rc_option = False - label_size = 10 - - verbose = False - verbose = True - -if auto_fas: - path = os.path.dirname(os.path.abspath(__file__)) - files_long = glob.glob(path+"/*.fasta") - files_long.extend(glob.glob(path+"/*.fas")) - files_long.extend(glob.glob(path+"/*.fa")) - files_long.extend(glob.glob(path+"/*.fna")) - input_fasta = [] - for i in files_long: - if not "combined" in i: - filename = i[i.rfind('\\')+1:] - input_fasta.append(filename) - -if trial_mode: - # start logging file - logprint(commandline, start=True, printing=False, prefix=output_file_prefix) - -main(input_fasta, wordsize, modes=plotting_modes, prefix=output_file_prefix, plot_size=plot_size, label_size=label_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=wobble_conversion, substitution_count=substitution_count, rc_option=rc_option, gff=input_gff_files, multi=collage_output, ncols=m_col, nrows=n_row, alphabetic_sorting=alphabetic_sorting, lcs_shading=lcs_shading, lcs_shading_num=lcs_shading_num, lcs_shading_ref=lcs_shading_ref, lcs_shading_interval_len=lcs_shading_interval_len, lcs_shading_ori=lcs_shading_ori, gff_color_config_file=gff_color_config_file, input_user_matrix_file=input_user_matrix_file, user_matrix_print=user_matrix_print, length_scaling=length_scaling, title_length=title_length, title_clip_pos=title_clip_pos, spacing=spacing, max_N_percentage=max_N_percentage, verbose=verbose) - - diff --git a/code/flexidot_v1.04.py b/code/flexidot_v1.04.py deleted file mode 100644 index f5b3481..0000000 --- a/code/flexidot_v1.04.py +++ /dev/null @@ -1,3325 +0,0 @@ -#!/usr/bin/python2.7 -# -*- coding: utf-8 -*- - -""" -FlexiDot: Highly customizable ambiguity-aware dotplots for visual sequence investigation - -Kathrin M. Seibt, Thomas Schmidt and Tony Heitkam -Institute of Botany, TU Dresden, Dresden, 01277, Germany - -Bioinformatics, 2018, doi 10.1093/bioinformatics/bty395 - -FlexiDot version1.04 (aka lab version 137) - -""" - - -############################### -# Requirements # -############################### - -# import system modules -import os, glob -import time, datetime -import sys -import shutil, getopt -import unicodedata - -def module_install_command(module_name, upgrade=False): - """ - create installation commands for Python modules and print information - """ - if upgrade: - load_command = "python -m pip install --upgrade %s" % module_name - else: - load_command = "python -m pip install %s" % module_name - - try: - logprint("Installing Python module: %s\n\t%s\n" % (module_name, load_command)) - except: - print "Installing Python module: %s\n\t%s\n" % (module_name, load_command) - - return load_command - -def load_modules(): - """ - load Python modules, if possible - otherwise try to install them - """ - - # make module names global - global cllct, gridspec, patches, rcParams, mplrc, P, Color, SeqIO, np, ccv, mcolors, rgb2hex, regex - - # matplotlib - try: - import matplotlib.collections as cllct - except: - command = module_install_command("matplotlib", upgrade=True) - try: - os.system(command) - print "\n" - import matplotlib.collections as cllct - except: - print "Please install module matplotlib manually" - from matplotlib.colors import colorConverter as ccv - import matplotlib.colors as mcolors - import matplotlib.gridspec as gridspec - import matplotlib.patches as patches - import pylab as P - - # specify matplotlib font settings - from matplotlib import rc as mplrc - mplrc('pdf', fonttype=42, compression=0) - from matplotlib import rcParams - rcParams['font.family'] = 'sans-serif' - rcParams['font.sans-serif'] = ['Helvetica', 'Verdana', 'Tahoma', ] - - # colour for color gradient palette - try: - from colour import Color - except: - command = module_install_command("colour") - try: - os.system(command) - print "\n" - from colour import Color - except: - print "Please install module colour manually" - - # color converter - try: - from colormap import rgb2hex - except: - command = module_install_command("colormap") - # additional module easydev.tools required by colormap - command2 = module_install_command("easydev") - try: - os.system(command) - os.system(command2) - print "\n" - from colormap import rgb2hex - except: - print "Please install module colormap manually" - - # biopython - try: - from Bio import SeqIO - except: - command = module_install_command("biopython") - try: - os.system(command) - print "\n" - from Bio import SeqIO - except: - print "Please install module biopython manually" - - # numpy - try: - import numpy as np - except: - command = module_install_command("numpy") - try: - os.system(command) - print "\n" - import numpy as np - except: - print "Please install module numpy manually" - - # regex for pattern matching - try: - import regex - except: - command = module_install_command("regex") - try: - os.system(command) - print "\n" - import regex - except: - print "Please install module regex manually" - -load_modules() - - -############################### -# Usage & Input # -############################### - -def usage(): - """ - usage and help - """ - - print """\n\n FLEXIDOT - ------------------------------------------------------------------- - - Version: - 1.04 - - Citation: - Kathrin M. Seibt, Thomas Schmidt, Tony Heitkam (2018) - "FlexiDot: Highly customizable ambiguity-aware dotplots for visual sequence investigation" - Bioinformatics, doi: 10.1093/bioinformatics/bty395 - - - General usage: - $ python flexidot.py -a [ARGUMENTS] - $ python flexidot.py -i [ARGUMENTS] - - - ARGUMENTS - ------------------------------------------------------------------- - - - INPUT/OUTPUT OPTIONS... required are [-a] OR [-i] - - -a, --auto_fas Imports all fasta files from current directory (*.fasta, *.fas, *.fa, *.fna) - -i is not needed, if -a is activated - [inactive by default] - - -i, --in_file Input fasta file (fasta file name or comma-separated file list) - > Provide multiple files: Recall -i or provide comma-separated file names - - -o, --output_file_prefix File prefix to be added to the generated filenames [default = NONE] - - -c, --collage_output Multiple dotplots are combined in a collage - Y or 1 = ON [default] - N or 0 = OFF - - -m, --m_col Number of columns per page [default = 4] (only if --collage_output is ON) - - -n, --n_row Number of rows per page [default = 5] (only if --collage_output is ON) - - -f, --filetype Output file format - 0 = PNG [default] - 1 = PDF - 2 = SVG - - -s, --alphabetic_sorting Sort sequences alphabetically according to titles - Y or 1 = ON - N or 0 = OFF [default] - - - CALCULATION PARAMETERS... - - -k, --wordsize Wordsize (kmer length) for dotplot comparison [default = 7] - - -p, --plotting_mode Mode of FlexiDot dotplotting - 0 = self [default] - 1 = paired - 2 = poly (matrix with all-against-all dotplots) - > Run multiple plotting modes: Recall -p or provide comma-separated numbers - - -t, --type_nuc Type of residue is nucleotide - Y or 1 = nucleotide [default] - N or 0 = amino acid - - -w, --wobble_conversion Ambiguity handling for relaxed matching - Y or 1 = ON - N or 0 = OFF [default] - - -S, --substitution_count Number of substitutions (mismatches) allowed per window for relaxed matching - [default = 0] - - -r, --rc_option Find reverse complementary matches (only if type_nuc=y) - Y or 1 = ON [default] - N or 0 = OFF - - - GRAPHIC FORMATTING... - - -A, --line_width Line width [default = 1] - - -B, --line_col_for Line color [default = black] - - -C, --line_col_rev Reverse line color [default = green] - - -D, --x_label_pos Position of the X-label - Y or 1 = top [default] - N or 0 = bottom - - -E, --label_size Font size [default = 10] - - -F, --spacing Spacing between all-against-all dotplots (only if --plotting_mode=2) - [default = 0.04] - - -L, --length_scaling Scale plot size for pairwise comparison (only if --plotting_mode=1) - Y or 1 = Scaling ON (axes scaled according to sequence length) - N or 0 = Scaling OFF (squared plots) [default] - - -M, --mirror_y_axis Flip y-axis bottom to top (cartesian coordinate system) - Y or 1 = y-axis bottom to top - N or 0 = y-axis top to bottom [default] - - -P, --plot_size Plotsize [default = 10] - - -R, --representation Region of plot to display (only if --plotting_mode=2) - 0 = full [default] - 1 = upper - 2 = lower - - -T, --title_length Limit title length for dotplot comparisons - [default = 20] - Position of selection can be specified by appending a letter (e.g. -T 20E) - B = beginning [default] - E = end - - - GFF SHADING (for -p/--plotting_mode=0 only)... - - -g, --input_gff_files GFF3 file used for markup in self-dotplots - (provide multiple files: Recall -g or provide comma-separated file names) - - -G, --gff_color_config_file Tab-delimited config file for custom gff shading - column 1: feature type - column 2: color - column 3: alpha - column 4: zoom factor (for small regions) - - - LCS SHADING OPTIONS (for -p/--plotting_mode=2 only)... - - -x, --lcs_shading Shade subdotplot based on the length of the longest common substring (LCS) - Y or 1 = ON - N or 0 = OFF [default] - - -X, --lcs_shading_num Number of shading intervals (hues) for LCS (-x) and user matrix shading (-u) - [default = 5] - - -y, --lcs_shading_ref Reference for LCS shading - 0 = maximal LCS length [default] - 1 = maximally possible length (length of shorter sequence in pairwise comparison) - 2 = given interval sizes - DNA [default 100 bp] or proteins [default 10 aa] - see -Y - - -Y, --lcs_shading_interval_len Length of intervals for LCS shading (only if --lcs_shading_ref=2) - [default for nucleotides = 50; default for amino acids = 10] - - -z, --lcs_shading_ori Shade subdotplots according to LCS on - 0 = forward [default], - 1 = reverse, or - 2 = both strands (forward shading above diagonal, reverse shading on diagonal and below; - if using --input_user_matrix_file, best LCS is used below diagonal) - - - CUSTOM USER MATRIX SHADING OPTIONS (for -p/--plotting_mode=2 only)... - - -u, --input_user_matrix_file Shading above diagonal according to values in matrix file specified by the user - (tab-delimited or comma-separated matrix with sequence name in column 1 and numbers in columns 2-n - e.g. identity matrix from multiple sequence alignment - strings are ignored) - - -U, --user_matrix_print Display provided matrix entries in the fields above diagonal of all-against-all dotplot - Y or 1 = ON - N or 0 = OFF [default] - - - OTHERS... - - -h, --help Help screen - - -v, --verbose Verbose - - - - - """ - -def check_input(argv, trial_mode=False): - """ - commandline argument parsing - """ - - global log_txt, aa_bp_unit - - # helpers for argument parsing - ###################################### - - arguments = ["-a", "--auto_fas", "a", "auto_fas", - "-i", "--input_fasta", "i:", "input_fasta=", - "-o", "--output_file_prefix", "o:", "output_file_prefix=", - "-c", "--collage_output", "c:", "collage_output=", - "-m", "--m_col", "m:", "m_col=", - "-n", "--n_row", "n:", "n_row=", - "-f", "--filetype", "f:", "filetype=", - "-t", "--type_nuc", "t:", "type_nuc=", - "-g", "--input_gff_files", "g:", "input_gff_files", - "-G", "--gff_color_config_file", "G:", "gff_color_config_file", - "-k", "--wordsize", "k:", "wordsize=", - "-p", "--plotting_mode", "p:", "plotting_mode=", - "-w", "--wobble_conversion", "w:", "wobble_conversion=", - "-S", "--substitution_count", "S:", "substitution_count=", - "-r", "--rc_option", "r:", "rc_option=", - "-s", "--alphabetic_sorting", "s:", "alphabetic_sorting=", - "-x", "--lcs_shading", "x:", "lcs_shading=", - "-X", "--lcs_shading_num", "X:", "lcs_shading_num=", - "-y", "--lcs_shading_ref", "y:", "lcs_shading_ref=", - "-Y", "--lcs_shading_interval_len", "Y:", "lcs_shading_interval_len=", - "-z", "--lcs_shading_ori", "z:", "lcs_shading_ori=", - "-u", "--input_user_matrix_file", "u:", "input_user_matrix_file=", - "-U", "--user_matrix_print", "U:", "user_matrix_print=", - "-P", "--plot_size", "P:", "plot_size=", - "-A", "--line_width", "A:", "line_width=", - "-B", "--line_col_for", "B:", "line_col_for=", - "-C", "--line_col_rev", "C:", "line_col_rev=", - "-D", "--x_label_pos", "D:", "x_label_pos=", - "-E", "--label_size", "E:", "label_size=", - "-F", "--spacing", "F:", "spacing=", - "-L", "--length_scaling", "L:", "length_scaling=", - "-M", "--mirror_y_axis", "M:", "mirror_y_axis=", - "-R", "--representation", "R:", "representation=", - "-T", "--title_length", "T:", "title_length=", - "-h", "--help", "h", "help", - "-v", "--verbose", "v", "verbose"] - - arguments_sysargv = tuple(arguments[0::4] + arguments[1::4]) - arguments_opts = "".join(arguments[2::4]) - arguments_args = arguments[3::4] - - - # setting defaults - ###################################### - - auto_fas = False # 0 - input_fasta = [] - output_file_prefix = None - collage_output = True # 1 - m_col = 4 - n_row = 5 - filetype = 0 - type_nuc = True - input_gff_files = [] - gff_color_config_file = "" - - wordsize = 7 - plotting_modes = [0] - wobble_conversion = False # 0 - substitution_count = 0 - rc_option = True # 1 - alphabetic_sorting = False # 0 - - lcs_shading = False # 0 - lcs_shading_num = 4 - lcs_shading_ref = 0 - lcs_shading_interval_len = 50 # interval default changes to "10" for amino acids [type_nuc = n] - lcs_shading_ori = 0 - - input_user_matrix_file = "" - user_matrix_print = False - - plot_size = 10 - line_width = 1 - line_col_for = "black" - line_col_rev = "#009243" - x_label_pos = True # 0 - label_size = 10 - spacing = 0.04 - length_scaling = False # 0 - title_length = 20 # float("Inf") - title_clip_pos = "B" # B (begin), E (end) - max_N_percentage = 49 # fixed value, no user input - mirror_y_axis = False - representation = 0 - - aa_bp_unit = "bp" - - verbose = False # 0 - - filetype_dict = {0: "png", 1: "pdf", 2: "svg"} - lcs_shading_ref_dict = {0: "maximal LCS length", 1: "maximally possible length", 2: "given interval sizes"} - plotting_mode_dict = {0: "self", 1: "paired", 2: "all-against-all"} - lcs_shading_ori_dict = {0: "forward", 1: "reverse complement", 2: "both"} - representation_dict = {0: "full", 1: "upper", 2: "lower"} - - # return default parameters for testing purposes - if trial_mode: - print "ATTENTION: YOU ARE IN THE TRIAL MODE!!!\n\n" - - commandline = "trial_mode\n" - - parameters = [commandline, auto_fas, input_fasta, output_file_prefix, collage_output, m_col, n_row, filetype_dict[filetype], type_nuc, input_gff_files, gff_color_config_file, wordsize, plotting_modes, wobble_conversion, substitution_count, rc_option, alphabetic_sorting, lcs_shading, lcs_shading_num, lcs_shading_ref, lcs_shading_interval_len, lcs_shading_ori, input_user_matrix_file, user_matrix_print, plot_size, line_width, line_col_for, line_col_rev, x_label_pos, label_size, spacing, length_scaling, title_length, title_clip_pos, max_N_percentage, mirror_y_axis, representation, verbose] - return parameters - - - # read arguments - ###################################### - - commandline = "" - for arg in sys.argv: - commandline += arg + " " - - log_txt = "\n...reading input arguments..." - print log_txt - - if len(sys.argv) < 2: - print "\nERROR: More arguments are needed. Exit..." - log_txt += "\nERROR: More arguments are needed. Exit..." - usage() - sys.exit() - - elif sys.argv[1] not in arguments_sysargv: - print "\nINPUT ERROR: Input argument %s unknown. Please check the help screen." % sys.argv[1] - log_txt += "\nINPUT ERROR: Input argument %s unknown. Please check the help screen." % sys.argv[1] - # usage() - sys.exit() - - try: - opts, args = getopt.getopt(sys.argv[1:], arguments_opts, arguments_args) - - except getopt.GetoptError: - print "\nINPUT ERROR (getopt): Input argument %s unknown. Please check the help screen." % sys.argv[1:] - log_txt += "\nINPUT ERROR (getopt): Input argument %s unknown. Please check the help screen." % sys.argv[1:] - # usage() - sys.exit() - - for opt, arg in opts: - - if opt in ("-h", "--help"): - print "...fetch help screen" - log_txt += "\n...fetch help screen" - usage(), sys.exit() - - if opt in ("-v", "--verbose"): - print "...verbose output" - log_txt += "\n...verbose output" - verbose = True - - elif opt in ("-i", "--input_fasta"): - if "," in arg: - arg_list = arg.split(",") - for temp_file in arg_list: - if not os.path.exists(str(temp_file)): - message = "\nERROR: fasta_file '%s' was not found!" % str(temp_file) - sys.exit(message) - else: - input_fasta.append(str(temp_file)) - print "fasta file #%i: %s" % (len(input_fasta), str(temp_file)) - log_txt += "\nfasta file #%i: %s" % (len(input_fasta), str(temp_file)) - else: - if not os.path.exists(str(arg)): - message = "\nERROR: fasta_file '%s' was not found!" % str(arg) - log_txt += message - sys.exit(message) - else: - input_fasta.append(str(arg)) - print "fasta file #%i: %s" % (len(input_fasta), str(arg)) - log_txt += "\nfasta file #%i: %s" % (len(input_fasta), str(arg)) - - - elif opt in ("-a", "--auto_fas"): - auto_fas = True - - - # multiple gff files: reads them into a list - elif opt in ("-g", "--input_gff_files"): - - # append gff file only if existing - if "," in arg: - arg_list = arg.split(",") - for temp_file in arg_list: - if not os.path.exists(str(temp_file)): - message = "\nERROR: gff_file '%s' was not found!" % str(temp_file) - print message - log_txt += message - print " -->Running FlexiDot without this gff file!" - log_txt += "\n -->Running FlexiDot without this gff file!" - else: - print "GFF file #%i: %s" %(len(input_gff_files), str(temp_file)) - log_txt += "\nGFF file #%i: %s" %(len(input_gff_files), str(temp_file)) - input_gff_files.append(str(temp_file)) - else: - if not os.path.exists(str(arg)): - message = "\nERROR: gff_file '%s' was not found!" % str(arg) - print message - log_txt += message - print " -->Running FlexiDot without this gff file!" - log_txt += "\n -->Running FlexiDot without this gff file!" - else: - input_gff_files.append(str(arg)) - print "GFF file #%i: %s" %(len(input_gff_files), str(arg)) - log_txt += "\nGFF file #%i: %s" %(len(input_gff_files), str(arg)) - - - elif opt in ("-G", "--gff_color_config_file"): - if not os.path.exists(str(arg)): - message = "\nERROR: gff_color_config_file '%s' was not found!" % str(arg) - print message + "\n -->Running FlexiDot with default gff coloring specification!" - log_txt += message + "\n -->Running FlexiDot with default gff coloring specification!" - else: - gff_color_config_file = str(arg) - - - elif opt in ("-u", "--input_user_matrix_file"): - if not os.path.exists(str(arg)): - message = "\nERROR: input_user_matrix_file '%s' was not found!" % str(arg) - print message + "\n -->Running FlexiDot without input_user_matrix_file %s!" % arg - log_txt += message + "\n -->Running FlexiDot withdefault matrix shading file!" - else: - input_user_matrix_file = str(arg) - - elif opt in ("-U", "--user_matrix_print"): - user_matrix_print = check_bools(str(arg), default=user_matrix_print) - - elif opt in ("-o", "--output_file_prefix"): - output_file_prefix = arg - - elif opt in ("-c", "--collage_output"): - collage_output = check_bools(str(arg), default=collage_output) - - elif opt in ("-m", "--m_col"): - try: m_col = int(arg) - except: - print "m_col - invalid argument - using default value" - log_txt += "\nm_col - invalid argument - using default value" - - elif opt in ("-n", "--n_row"): - try: n_row = int(arg) - except: - print "n_row - invalid argument - using default value" - log_txt += "\nn_row - invalid argument - using default value" - - elif opt in ("-f", "--filetype"): - if 0 <= int(arg) <= 2: - filetype = int(arg) - else: - print "\nERROR: Please provide valid filetype argument. %s is out of range. It will be set to -f 0 [default]." %(filetype) - log_txt += "\nERROR: Please provide valid filetype argument. %s is out of range. It will be set to -f 0 [default]." %(filetype) - - elif opt in ("-t", "--type_nuc"): - type_nuc = check_bools(str(arg), default=type_nuc) - - if type_nuc == False: - # interval default changed for amino acids - lcs_shading_interval_len = 10 - aa_bp_unit = "aa" - - elif opt in ("-k", "--wordsize"): - try: wordsize = int(arg) - except: - print "wordsize - invalid argument - using default value" - log_txt += "\nwordsize - invalid argument - using default value" - - elif opt in ("-p", "--plotting_mode"): - if "," in arg: - temp_modes = arg.split(",") - for item in temp_modes: - if item in ["0","1","2"]: - plotting_modes.append(int(item)) - elif arg in ["0","1","2"]: - plotting_modes = [int(arg)] - else: - print "Please provide valid plotting_modes argument - e.g. 1 or 0,1,2 - using default [0]" - log_txt += "\nPlease provide valid plotting_modes argument - e.g. 1 or 0,1,2 - using default [0]" - - elif opt in ("-w", "--wobble_conversion"): - wobble_conversion = check_bools(str(arg), default=wobble_conversion) - - elif opt in ("-S", "--substitution_count"): - try: substitution_count = int(arg) - except: - print "substitution_count - invalid argument - using default value" - log_txt += "\nsubstitution_count - invalid argument - using default value" - - elif opt in ("-r", "--rc_option"): - rc_option = check_bools(str(arg), default=rc_option) - - elif opt in ("-s", "--alphabetic_sorting"): - alphabetic_sorting = check_bools(str(arg), default=alphabetic_sorting) - - elif opt in ("-x", "--lcs_shading"): - lcs_shading = check_bools(str(arg), default=lcs_shading) - - elif opt in ("-X", "--lcs_shading_num"): - try: lcs_shading_num = int(arg) - 1 - except: - print "lcs_shading_num - invalid argument - using default value" - log_txt += "\nlcs_shading_num - invalid argument - using default value" - - elif opt in ("-y", "--lcs_shading_ref"): - try: - if 0 <= int(arg) <= 2: - lcs_shading_ref = int(arg) - else: - print "\nERROR: lcs_shading_ref %s out of range. It will be set to -y 0 [default]." %(lcs_shading_ref) - log_txt += "\nERROR: lcs_shading_ref %s out of range. It will be set to -y 0 [default]." %(lcs_shading_ref) - except: - print "lcs_shading_ref - invalid argument - using default value" - log_txt += "\nlcs_shading_ref - invalid argument - using default value" - - elif opt in ("-Y", "--lcs_shading_interval_len"): - try: lcs_shading_interval_len = int(arg) - except: - print "lcs_shading_interval_len - invalid argument - using default value" - log_txt += "\nlcs_shading_interval_len - invalid argument - using default value" - - elif opt in ("-z", "--lcs_shading_ori"): - if 0 <= int(arg) <= 2: - lcs_shading_ori = int(arg) - else: - print "\nERROR: Please provide valid lcs_shading_ori argument. %s is out of range. It will be set to -z 0 [default]." %(lcs_shading_ori) - log_txt += "\nERROR: Please provide valid lcs_shading_ori argument. %s is out of range. It will be set to -z 0 [default]." %(lcs_shading_ori) - - elif opt in ("-P", "--plot_size"): - try: plot_size = float(arg) - except: - print "plot_size - invalid argument - using default value" - log_txt += "\nplot_size - invalid argument - using default value" - - - elif opt in ("-A", "--line_width"): - try: line_width = float(arg) - except: - print "line_width - invalid argument - using default value" - log_txt += "\nline_width - invalid argument - using default value" - - elif opt in ("-B", "--line_col_for"): - if mcolors.is_color_like(arg): - line_col_for = arg - else: - print "line_col_for - invalid argument - using default value" - log_txt += "\nline_col_for - invalid argument - using default value" - - elif opt in ("-C", "--line_col_rev"): - if mcolors.is_color_like(arg): - line_col_rev = arg - else: - print "line_col_rev - invalid argument - using default value" - log_txt += "\nline_col_rev - invalid argument - using default value" - - elif opt in ("-D", "--x_label_pos"): - x_label_pos = check_bools(str(arg), default=x_label_pos) - - elif opt in ("-E", "--label_size"): - try: label_size = float(arg) - except: - print "label_size - invalid argument - using default value" - log_txt += "\nlabel_size - invalid argument - using default value" - - elif opt in ("-F", "--spacing"): - try: spacing = float(arg) - except: - print "spacing - invalid argument - using default value" - log_txt += "\nspacing - invalid argument - using default value" - - elif opt in ("-L", "--length_scaling"): - length_scaling = check_bools(str(arg), default=length_scaling) - - elif opt in ("-M", "--mirror_y_axis"): - mirror_y_axis = check_bools(str(arg), default=mirror_y_axis) - - elif opt in ("-R", "--representation"): - if 0 <= int(arg) <= 2: - representation = int(arg) - else: - print "\nERROR: Please provide valid representation argument. %s is out of range. It will be set to -R 0 [default]." %(representation) - log_txt += "\nERROR: Please provide valid representation argument. %s is out of range. It will be set to -R 0 [default]." %(representation) - - elif opt in ("-T", "--title_length"): - try: title_length = int(arg) - except: - try: - title_length = int(str(arg)[:-1]) - if arg[-1].upper() in ["B", "E"]: # B (beginning), E (end) - title_clip_pos = arg[-1].upper() - else: - print "title_length position information invalid - using default value" - log_txt += "\ntitle_length position information invalid - using default value" - except: - print "title_length - invalid argument - using default value" - log_txt += "\ntitle_length - invalid argument - using default value" - - # start logging file - logprint(commandline, start=True, printing=False, prefix=output_file_prefix) - logprint(log_txt, start=False, printing=False) - - - # print chosen arguments - ###################################### - - text = "\n%s\n" % (70 * "-") - text += "\n" + "INPUT/OUTPUT OPTIONS...\n" - text += "\n" + "Input fasta file: " + ", ".join(input_fasta) - text += "\n" + "Automatic fasta collection from current directory: " + str(auto_fas) - text += "\n" + "Collage output: " + str(collage_output) - text += "\n" + "Number of columns per page: " + str(m_col) - text += "\n" + "Number of rows per page: " + str(n_row) - text += "\n" + "File format: " + filetype_dict[filetype] - text += "\n" + "Residue type is nucleotide: " + str(type_nuc) - - text += "\n" + "\n\nCALCULATION PARAMETERS...\n" - text += "\n" + "Wordsize: " + str(wordsize) - text += "\n" + "Plotting mode: " + str(plotting_modes).replace("[", "").replace("]", "") + "\n" + 51 * " " - for item in plotting_modes: - text += plotting_mode_dict[item] + " " - text += "\n" + "Ambiguity handling: " + str(wobble_conversion) - text += "\n" + "Reverse complement scanning: " + str(rc_option) - text += "\n" + "Alphabetic sorting: " + str(alphabetic_sorting) - - if 0 in plotting_modes and input_gff_files != []: - text += "\n" + "Input gff files: " + ", ".join(input_gff_files) - if gff_color_config_file != "": - text += "\n" + "GFF color config file: " + gff_color_config_file - text += "\n" + "Prefix for output files: " + str(output_file_prefix) - - if 2 in plotting_modes: - text += "\n" + "\n\nLCS SHADING OPTIONS (plotting_mode 'all-against-all' only)...\n" - text += "\n" + "LCS shading: " + str(lcs_shading) - text += "\n" + "LCS shading interval number: " + str(lcs_shading_num + 1) - text += "\n" + "LCS shading reference: " + lcs_shading_ref_dict[lcs_shading_ref] - if lcs_shading_ref == 2: - text += "\n" + "LCS shading interval size [%s]: " % (aa_bp_unit) + str(lcs_shading_interval_len) - text += "\n" + "LCS shading orientation: " + lcs_shading_ori_dict[lcs_shading_ori] - if input_user_matrix_file != "": - text += "\n" + "Custom user shading matrix file: " + input_user_matrix_file - text += "\n" + "Print user matrix values (instead of dotplot): " + str(user_matrix_print) - text += "\n" + "Displayed plot region: " + representation_dict[representation] - - text += "\n" + "\n\nGRAPHIC FORMATTING...\n" - text += "\n" + "Plot size: " + str(plot_size) - text += "\n" + "Line width: " + str(line_width) - text += "\n" + "Line color: " + line_col_for - text += "\n" + "Reverse line color: " + line_col_rev - text += "\n" + "X label position: " + str(x_label_pos) - text += "\n" + "Label size: " + str(label_size) - text += "\n" + "Spacing: " + str(spacing) - if mirror_y_axis: - text += "\n" + "Y-axis mirrored (bottom to top) " + str(mirror_y_axis) - if title_clip_pos == "E": - text += "\n" + "Title length (limit number of characters): " + "last" + str(title_length) + "characters" - else: - text += "\n" + "Title length (limit number of characters): " + "first" + str(title_length) + "characters" - text += "\n" + "Length scaling: " + str(length_scaling) - text += "\n%s\n" % (70 * "-") - logprint(text) - - - # collect settings - parameters = [commandline, auto_fas, input_fasta, output_file_prefix, collage_output, m_col, n_row, filetype_dict[filetype], type_nuc, input_gff_files, gff_color_config_file, wordsize, plotting_modes, wobble_conversion, substitution_count, rc_option, alphabetic_sorting, lcs_shading, lcs_shading_num, lcs_shading_ref, lcs_shading_interval_len, lcs_shading_ori, input_user_matrix_file, user_matrix_print, plot_size, line_width, line_col_for, line_col_rev, x_label_pos, label_size, spacing, length_scaling, title_length, title_clip_pos, max_N_percentage, mirror_y_axis, representation, verbose] - - return parameters - - -############################### -# Helper Functions # -############################### - -def alphabets(type_nuc=True): - """ - provide ambiguity code for sequences - """ - - nucleotide_alphabet = ["A", "C", "G", "T"] - - nucleotide_alphabet_full = ["A", "C", "G", "T", "N", "B", "D", "H", - "V", "Y", "R", "W", "S", "K", "M"] - - nucleotide_ambiguity_code = {"N": ["A", "C", "G", "T"], # any - "B": ["C", "G", "T"], # not A - "D": ["A", "G", "T"], # not C - "H": ["A", "C", "T"], # not G - "V": ["A", "C", "G"], # not T - "Y": ["C", "T"], # pyrimidine - "R": ["A", "G"], # purine - "W": ["A", "T"], # weak - "S": ["C", "G"], # strong - "K": ["G", "T"], # keto - "M": ["A", "C"]} # amino - - nucleotide_match_dict = {"N": "[ACGTNBDHVYRWSKM]", # any - "B": "[CGTNBDHVYRWSKM]", # not A - "D": "[AGTNBDHVYRWSKM]", # not C - "H": "[ACTNBDHVYRWSKM]", # not G - "V": "[ACGNBDHVYRWSKM]", # not T - "K": "[GTNBDHVYRWSK]", # keto - not A,C,M - "M": "[ACNBDHVYRWSM]", # amino - not G,T,K - "W": "[ATNBDHVYRWKM]", # weak - not C,G,S - "S": "[CGNBDHVYRSKM]", # strong - not A,G,W - "Y": "[CTNBDHVYWSKM]", # pyrimidine - not A,G,R - "R": "[AGNBDHVRWSKM]", # purine - not C,T,Y - "A": "[ANDHVRWM]", - "C": "[CNBHVYSM]", - "G": "[GNBDVRSK]", - "T": "[TNBDHYWK]"} - - # nucleotide_match_dict = {"N": ".", # any - # "B": "[^A]", # not A - # "D": "[^C]", # not C - # "H": "[^G]", # not G - # "V": "[^T]", # not T - # "K": "[^ACM]", # keto - not A,C,M - # "M": "[^GTK]", # amino - not G,T,K - # "W": "[^CGS]", # weak - not C,G,S - # "S": "[^AGW]", # strong - not A,G,W - # "Y": "[^AGR]", # pyrimidine - not A,G,R - # "R": "[^CTY]", # purine - not C,T,Y - # "A": "[ANDHVRWM]", - # "C": "[CNBHVYSM]", - # "G": "[GNBDVRSK]", - # "T": "[TNBDHYWK]"} - - aminoacid_alphabet = ["A", "R", "N", "D", "C", "E", "Q", "G", - "H", "I", "L", "K", "M", "F", "P", "S", - "T", "W", "Y", "V", "U", "O", "*"] - - aminoacid_alphabet_full = ["A", "R", "N", "D", "C", "E", "Q", "G", - "H", "I", "L", "K", "M", "F", "P", "S", - "T", "W", "Y", "V", "U", "O", "*", "J", - "Z", "B", "X"] - - aminoacid_ambiguity_code = {"J": ["I", "L"], - "Z": ["Q", "E"], - "B": ["N", "D"], - "X": ["A", "R", "N", "D", "C", "E", "Q", "G", - "H", "I", "L", "K", "M", "F", "P", "S", - "T", "W", "Y", "V", "U", "O", "*"]} # any - - aminoacid_match_dict = {"J": "[ILJ]", - "Z": "[QEZ]", - "B": "[NDB]", - # "X": ".", - "X": "[ARNDCEQGHILKMFPSTWYVUO*XBZJ]", - "A": "[AX]", - "R": "[RX]", - "N": "[NXB]", - "D": "[DXB]", - "C": "[CX]", - "E": "[EXZ]", - "Q": "[QXZ]", - "G": "[GX]", - "H": "[HX]", - "I": "[IXJ]", - "L": "[LXJ]", - "K": "[KX]", - "M": "[MX]", - "F": "[FX]", - "P": "[PX]", - "S": "[SX]", - "T": "[TX]", - "W": "[WX]", - "Y": "[YX]", - "V": "[VX]", - "U": "[UX]", - "O": "[OX]", - "*": "[*X]"} - - aa_only = set(['E', 'F', 'I', 'J', 'L', 'O', 'Q', 'P', 'U', 'X', 'Z', '*']) - # return nucleotide_alphabet, nucleotide_alphabet_full, nucleotide_ambiguity_code, aminoacid_alphabet, aminoacid_alphabet_full, aminoacid_ambiguity_code, aa_only - - if type_nuc: - return nucleotide_alphabet, nucleotide_alphabet_full, nucleotide_ambiguity_code, nucleotide_match_dict - else: - return aminoacid_alphabet, aminoacid_alphabet_full, aminoacid_ambiguity_code, aminoacid_match_dict - -def logprint(text, start=False, printing=True, prefix=""): - """ - log output to log_file and optionally print - """ - - # define log file name and open file - global log_file_name - if start and trial_mode: - log_file_name = "log_file.txt" - if prefix != "" and prefix != None: - if not prefix.endswith("-"): - prefix = prefix + "-" - log_file_name = prefix + log_file_name - log_file = open(log_file_name, 'w') - log_file.write("Date: %s\n\n" % str(datetime.datetime.now())) - elif start: - date = datetime.date.today() - time = str(datetime.datetime.now()).split(" ")[1].split(".")[0].replace(":", "-") - log_file_name = "%s_%s_log_file.txt" % (date, time) - if prefix != "" and prefix != None: - if not prefix.endswith("-"): - prefix = prefix + "-" - log_file_name = prefix + log_file_name - log_file = open(log_file_name, 'w') - log_file.write("Date: %s\n\n" % str(datetime.datetime.now())) - else: - log_file = open(log_file_name, 'a') - - # write log (and print) - log_file.write(text + "\n") - if printing: - print text - log_file.close() - -def time_track(starting_time, show=True): - """ - calculate time passed since last time measurement - """ - now = time.time() - delta = now - starting_time - if show: - text = "\n\t %s seconds\n" % str(delta) - logprint(text, start=False, printing=True) - return now - -def calc_fig_ratio(ncols, nrows, plot_size, verbose=False): - """ - calculate size ratio for given number of columns (ncols) and rows (nrows) - with plot_size as maximum width and length - """ - ratio = ncols*1./nrows - if verbose: - text = " ".join([ncols, nrows, ratio]) - logprint(text, start=False, printing=True) - if ncols >= nrows: - figsize_x = plot_size - figsize_y = plot_size / ratio - else: - figsize_x = plot_size * ratio - figsize_y = plot_size - return figsize_x, figsize_y - -def shorten_name(seq_name, max_len=20, title_clip_pos="B"): #, delim="_"): - """ - shorten sequence names (for diagram titles) - """ - - if len(seq_name) <= max_len: - return seq_name - - # take last characters - if title_clip_pos == "E": - name = seq_name[len(seq_name)-max_len:] - - # take first characters - else: - name = seq_name[:max_len] - - """# keep first and last part if multiple parts separated by delimiter (e.g. species_prefix + sequence_id) - if delim in seq_name: - if seq_name.count(delim) >= 2: - name = "%s..." % delim.join(seq_name.split(delim)[:1]) + seq_name.split(delim)[-1] # .replace("_000", "-") - else: - name = seq_name[:((max_len-2)//2)] + "..." + seq_name[((max_len-2)//2):] - - if len(name) > max_len: - name = name[:((max_len-2)//2)] + "..." + name[((max_len-2)//2):] - else: - name = seq_name[:((max_len-2)//2)] + "..." + seq_name[((max_len-2)//2):] - """ - - return name - -def unicode_name(name): - """ - replace non-ascii characters in string (e.g. for use in matplotlib) - """ - unicode_string = eval('u"%s"' % name) - return unicodedata.normalize('NFKD', unicode_string).encode('ascii','ignore') - -def check_bools(arg, update_log_txt = True, default=None): - """ - converts commandline arguments into boolean - """ - - - # convert valid arguments - if str(arg).lower() == "y" or str(arg) == "1": - return True - elif str(arg).lower() == "n" or str(arg) == "0": - return False - - # use default in case of invalid argument - else: - if update_log_txt: - global log_txt - log_txt += "using default for " + str(arg) - else: - try: - logprint("using default for " + str(arg)) - except: - print "using default for " + str(arg) - return default - -def create_color_list(number, color_map=None, logging=False, max_grey="#595959"): - """ - create color list with given number of entries - grey by default, matplotlib color_map can be provided - """ - - try: - # create pylab colormap - cmap = eval("P.cm." + color_map) - # get descrete color list from pylab - cmaplist = [cmap(i) for i in range(cmap.N)] # extract colors from map - # determine positions for number of colors required - steps = (len(cmaplist)-1)/(number) - numbers = range(0, len(cmaplist), steps) - - # extract color and convert to hex code - colors = [] - for idx in numbers[:-1]: - rgb_color = cmaplist[idx] - col = rgb2hex(rgb_color[0]*255, rgb_color[1]*255, rgb_color[2]*255) - colors.append(col) - - # grey - except: - if not color_map == None: - logprint("Invalid color_map (%s) provided! - Examples: jet, Blues, OrRd, bwr,..." % color_map) - logprint("See https://matplotlib.org/users/colormaps.html\n") - old_max_grey = "#373737" - old_max_grey = "#444444" - colors = list(Color("#FFFFFF").range_to(Color(max_grey), number)) # grey - for idx in range(len(colors)): - colors[idx] = str(colors[idx]).replace("Color ", "") - if "#" in colors[idx] and len(colors[idx]) != 7: - # print colors[idx] - colors[idx] = colors[idx] + colors[idx][-(7-len(colors[idx])):] - - text = "%d Colors: %s" % (len(colors), ", ".join(colors)) - if logging: logprint(text, start=False, printing=True) - - if len(colors) < number: - logprint("\nError in color range definition! %d colors missing\n" % (number - len(colors))) - - return colors - - -############################### -# File Handling # -############################### - -def read_seq(input_fasta, verbose=False): - """ - read fasta sequences from (all) file(s) - """ - - # check if file provided - if input_fasta == [] or input_fasta == "": - text = "Attention: No valid file names provided: >%s<" % input_fasta - logprint(text, start=False, printing=True) - return {}, [] - - # combine sequence files, if required - if type(input_fasta) == list: - # concatenate fasta files - if len(input_fasta) > 1: - if verbose: - print "concatenating fastas...", - text = "concatenating fastas..." - input_fasta_combi = concatenate_files(input_fasta) - if verbose: - print "done" - text += "done" - logprint(text, start=False, printing=False) - else: - input_fasta_combi = input_fasta[0] - else: - input_fasta_combi = input_fasta - - # read sequences - if verbose: - print "reading fasta...", - text = "reading fasta...", - try: - seq_dict = SeqIO.index(input_fasta_combi, "fasta") - except ValueError: - logprint("Error reading fasta sequences - please check input files, e.g. for duplicate names!") - return {}, [] - except: - logprint("Error reading fasta sequences - please check input files!") - return {}, [] - - if verbose: - print "done" - text += "done" - logprint(text, start=False, printing=False) - - for seq in seq_dict: - if "-" in seq_dict[seq].seq: - # ungapped = seq_dict[seq].seq.ungap("-") # cannot be assigned back to sequence record - text = "\nSequences degapped prior Analysis!!!" - logprint(text, start=False, printing=True) - return read_seq(degap_fasta(input_fasta), verbose=verbose) - - # get ordered sequence names - sequences = [] - for item in SeqIO.parse(input_fasta_combi, "fasta"): - sequences.append(item.id) - return seq_dict, sequences - -def read_gff_color_config(gff_color_config_file=""): - """ - define coloring options for gff-based color shading of self-dotplots - """ - - # default aestetics for annotation shading (e.g. if no user config file is provided) - # dictionary with feature_type as key and tuple(color, transparency, zoom) as value - gff_feat_colors = {"orf": ("#b41a31", 0.2, 0), - "orf_rev": ("#ff773b", 0.3, 0), - "gene": ("#b41a31", 0.2, 0), - "cds": ("darkorange", 0.2, 0), - "exon": ("orange", 0.2, 0), - "intron": ("lightgrey", 0.2, 0), - "utr": ("lightblue", 0.2, 0), - "repeat_region": ("green", 0.3, 0), - "repeat": ("green", 0.3, 0), - "tandem_repeat": ("red", 0.3, 0), - "transposable_element": ("blue", 0.3, 0), - "ltr_retrotransposon": ("#cccccc", 0.5, 0), - "ltr-retro": ("#cccccc", 0.5, 0), - "long_terminal_repeat": ("#2dd0f0", 0.75, 2), - "ltr": ("#2dd0f0", 0.75, 2), - "pbs": ("purple", 0.75, 2), - "ppt": ("#17805a", 0.5, 2), - "target_site_duplication": ("red", 0.75, 2), - "misc_feature": ("grey", 0.3, 0), - "misc_feat": ("grey", 0.3, 0), - "misc": ("grey", 0.3, 0), - "others": ("grey", 0.5, 0)} - if gff_color_config_file in ["", None] or not os.path.exists(str(gff_color_config_file)): - return gff_feat_colors - - text = "Updating GFF color configuration with custom specifications\n" - logprint(text, start=False, printing=True) - - # read custom gff_color_config_file - in_file = open(gff_color_config_file, 'rb') - overwritten = set([]) - for line in in_file: - if not line.startswith("#") and len(line.strip().split("\t")) >= 4: - data = line.strip().split("\t") - feat = data[0].lower() - color = data[1].lower() - - # check, if settings are valid - if not mcolors.is_color_like(color): - color = "grey" - text = "Invalid color specified for %s: %s - default grey" % (data[0], data[1]) - logprint(text) - try: - alpha = float(data[2]) - except: - alpha = 0.75 - text = "Invalid alpha specified for %s: %s - default 0.75" % (data[0], data[2]) - logprint(text) - try: - zoom = float(data[3]) - except: - zoom = 0 - text = "Invalid zoom specified for %s: %s - default 0" % (data[0], data[3]) - logprint(text) - - # track changes of predefined settings - if feat in gff_feat_colors.keys(): - overwritten.add(data[0].lower()) - - gff_feat_colors[feat] = (color, alpha, zoom) - in_file.close() - - # default coloring for unknown annotations - if not "others" in gff_feat_colors.keys(): - gff_feat_colors["others"] = ("grey", 0.5, 0) - - if verbose: - # print configuration - text = "\n\nGFF color specification:\n%s\n" % (60 * ".") - for item in sorted(gff_feat_colors.keys()): - text += "%-30s\t%-10s\t%-5s\t%s\n" % (item, str(gff_feat_colors[item][0]), str(gff_feat_colors[item][1]), str(gff_feat_colors[item][2])) - logprint (text, printing=True) - - # print overwritting feature type specifications - if len(overwritten) != 0: - text = "%d feature type specifications overwritten:" % len(overwritten) - text += "\n\t"+ ", ".join(overwritten) + "\n" - logprint(text, start=False, printing=True) - - text = "GFF color specification updated acc. to %s\n\t%s\n\n" % (gff_color_config_file, ", ".join(gff_feat_colors)) - logprint(text, start=False, printing=True) - - return gff_feat_colors - -def read_gffs(input_gff_files, color_dict={"others": ("grey", 1, 0)}, type_nuc=True, prefix="", filetype='png', verbose=False): - """ - create feature dictionary from input_gff - sequence name as key and (feature type, start, stop) as value - """ - if type(input_gff_files) != list: - input_gff_files = [input_gff_files] - - # create dictionary with seq_name as key and (type, start and stop) as value - unknown_feats = set([]) - used_feats = set([]) - feat_dict = {} - for input_gff in input_gff_files: - text = "...reading " + input_gff - logprint(text, start=False, printing=True) - - in_file = open(input_gff, 'rb') - for line in in_file: - if not line.startswith("#") and line.strip() != "": - data = line.strip().split("\t") - feat_type = data[2].lower() - if data[6] == "-": - feat_type += "_rev" - if not feat_type.lower() in color_dict.keys(): - if feat_type.lower().replace("_rev", "") in color_dict.keys(): - feat_type = feat_type.replace("_rev", "") - else: - unknown_feats.add(feat_type) - feat_type = "others" - used_feats.add(feat_type) - if not data[0] in feat_dict.keys(): - feat_dict[data[0]] = [(feat_type, int(data[3]), int(data[4]))] # feature type, start, stop - else: - feat_dict[data[0]].append((feat_type, int(data[3]), int(data[4]))) # feature type, start, stop - if verbose: - text = "\nAnnotations for: %s\n" % ", ".join(feat_dict.keys()[:10]) - if len(feat_dict.keys()) > 10: - text = text[:-1] + ", ...\n" - logprint(text, start=False, printing=True) - in_file.close() - - # print feature types without specific shading settings - if len(unknown_feats) != 0: - text = "Missing shading specification for %d feature type(s):\n\t%s\n" % (len(unknown_feats), ", ".join(sorted(unknown_feats))) - logprint(text, start=False, printing=True) - - # create color legend - colors, alphas = [], [] - for item in sorted(used_feats): - colors.append(color_dict[item][0]) - alphas.append(color_dict[item][1]) - legend_figure(colors=colors, lcs_shading_num=len(used_feats), type_nuc=type_nuc, bins=sorted(used_feats), alphas=alphas, gff_legend=True, prefix=prefix, filetype=filetype) - - # print settings - text = "GFF Feature Types: %s\nGFF Colors: %s" % (", ".join(sorted(used_feats)), ", ".join(sorted(colors))) - logprint(text, start=False, printing=True) - - return feat_dict - -def read_matrix(matrix_file_name, delim="\t", symmetric=True, recursion=False, verbose=False): - input_file = open(matrix_file_name, 'rb') - - # read sequence names from first column - names = [] - for line in input_file: - if not line.startswith("#") and not line.startswith(delim) and delim in line: - names.append(line.strip().split(delim)[0]) - logprint("Delimiter '%s': %d names - %s\n" % (delim, len(names), ", ".join(names))) - - # check if names were found - otherwise try another delimiter - if names == [] and not recursion: - if delim == "\t": - new_delim = "," - else: - new_delim = "\t" - logprint("\nMatrix file not containing data delimited by '%s' - trying to read matrix with delimiter '%s'" % (delim.replace("\t", "\\t"), new_delim)) - info_dict = read_matrix(matrix_file_name, delim=new_delim, symmetric=symmetric, recursion=True, verbose=verbose) - return info_dict - elif names == []: - logprint("Empty matrix file with alternative delimiter!") - return info_dict - input_file.close() - - input_file = open(matrix_file_name, 'rb') - # read matrix entries as values in dictionary with tuple(names) as key - info_dict = {} - contradictory_entries = [] - for line in input_file: - if not line.startswith("#") and not line.startswith(delim) and delim in line: - data = line.strip().split(delim) - for idx in range(len(data[1:])): - # print tuple(sorted([data[0], names[idx]])), data[idx+1] - if symmetric: - key = tuple(sorted([names[idx], data[0]])) - else: - key = tuple(names[idx], data[0]) - if key in info_dict.keys(): - if symmetric and info_dict[key] != data[idx+1] and data[idx+1] not in ["", "-"] and info_dict[key] not in ["", "-"]: - contradictory_entries.append(key) - info_dict[key] = data[idx+1] - input_file.close() - - if len(contradictory_entries) != 0: - try: - logprint("\nContradictory entries in matrix file %s:\n\t%s" % (matrix_file_name, ", ".join(contradictory_entries))) - except: - log_txt = "\nContradictory entries in matrix file %s:\n\t" % (matrix_file_name) - for item in contradictory_entries: - log_txt += str(item).replace("'", "") + ", " - log_txt = log_txt[:-2] - logprint(log_txt) - logprint("Using value from bottom left triangle!") - if verbose: - logprint("\nMatrix information for Sequences named: " % ", ".join(names)) - - return info_dict - -def concatenate_files(file_list, combi_filename="temp_combined.fasta", verbose=False): - """ - concatenate content of all files in file_list into a combined file named combi_filename - """ - out_file = open(combi_filename, 'w') - text = "" - for item in file_list: - if verbose: - text += item + " " - print item, - # read in_file linewise and write to out_file - in_file = open(item, 'rb') - for line in in_file: - out_file.write(line.strip()+"\n") - in_file.close() - out_file.close() - if verbose: - logprint(text, start=False, printing=False) - return combi_filename - -def degap_fasta(input_fasta): - """ - remove gaps from fasta - new degapped sequence file created - """ - - # degap all sequence files - output_fastas = [] - if type(input_fasta) != list: - input_fasta = list(input_fasta) - for input_fas in input_fasta: - output_fas = input_fas[:input_fas.rfind(".")] + "_degapped.fas" - in_file = open(input_fas, 'rb') - out_file = open(output_fas, 'w') - for line in in_file: - if line.startswith(">"): - out_file.write(line.strip()+"\n") - else: - out_file.write(line.strip().replace("-", "")+"\n") - out_file.close() - in_file.close() - output_fastas.append(output_fas) - return output_fastas - -def legend_figure(colors, lcs_shading_num, type_nuc=True, unit="%", filetype="png", max_lcs_len=None, min_lcs_len=0, bins=[], alphas=[], gff_legend=False, prefix="", verbose=False): - """ - create figure color legend - """ - max_legend_length_row = 8 - max_legend_length_col = 4 - - # define output file - if filetype not in ["png", "pdf", "svg"]: - text = "Provide valid file type - png, pdf, or svg" - logprint(text, start=False, printing=True) - filetype="png" - - # check if length of information fit - if not gff_legend and ((bins != [] and len(colors) != lcs_shading_num+1) or (bins != [] and len(colors) != len(bins)+1)): - if bins != [] and len(colors) != lcs_shading_num+1: - text = "**Attention**\nlcs_shading_num (%d) does not match number of colors (%d)!\n"% (lcs_shading_num, len(bins)) - elif bins != [] and len(colors) != len(bins)+1: - text = "**Attention**\nnumber of LCS length bins (%d) does not match number of colors (%d)!\n" % (len(colors), len(bins)) - logprint(text, start=False, printing=True) - elif gff_legend and len(bins) != len(colors): - text = "**Attention**\nnumber of GFF Feature Types (%d) does not match number of colors (%d)!\n" % (len(colors), len(bins)) - logprint(text, start=False, printing=True) - - # set alpha values to opaque if none are provided - if alphas == []: - for item in colors: - alphas.append(1) - - # legend data points - data_points = range(len(colors)) - if not gff_legend: - - # specify intervals, if max_lcs_len provided - if max_lcs_len != None: - multi_factor = 100 # one digit - if max_lcs_len <= 1: - multi_factor = 1000 # two digits - # len_interval_size = (max_lcs_len-min_lcs_len) * multi_factor *1. // lcs_shading_num * (1./ multi_factor) - len_interval_size = (max_lcs_len-min_lcs_len) * 1. / lcs_shading_num - len_pos = [float("%.2f" % (min_lcs_len))] - # calculate interval positions - for idx in range(lcs_shading_num): - len_pos.append(float("%.2f" % (len_pos[-1] + len_interval_size))) - - if prefix.startswith("custom-matrix") and (0 <= max_lcs_len <= 100 and 0 <= min_lcs_len <= 100): - unit = "%" - elif prefix.startswith("custom-matrix"): - unit = "" - - text = "\n%d Legend intervals from %.2f to %.2f: \n\t%s - number: %d, step: %.2f, unit: %s\n" % (lcs_shading_num+1, min_lcs_len, max_lcs_len, str(len_pos), len(len_pos), len_interval_size, unit) - logprint(text, start=False, printing=True) - pos = len_pos - interval_size = len_interval_size - else: - # generate legend labels acc. to standard interval notation - interval_size = 100 // lcs_shading_num - pos = range(interval_size, 101+interval_size, interval_size) - - if bins != []: # labels provided - legend_labels = bins[:] - legend_labels.append("max") - legend_labels_lengths = [] - for item in bins: - legend_labels_lengths.append("[%d %s, %d %s)" % (item - min(bins), unit, item, unit)) - if len(bins) == len(colors) - 1: - legend_labels_lengths.append("[%d %s, %s]" % (max(bins), unit, u"\u221E")) # infinite - - else: - legend_labels = [] - legend_labels_lengths = [] - for idx in range(len(pos)): - num = pos[idx] - legend_labels.append("[%d%%, %d%%)" % (num - interval_size, num)) - if max_lcs_len != None: - num = len_pos[idx] - # as int or float - if num == int(num) and int(len_interval_size) == len_interval_size: - legend_labels_lengths.append("[%d %s, %d %s)" % (num, unit, num + len_interval_size, unit)) - else: - legend_labels_lengths.append("[%.2f %s, %.2f %s)" % (num, unit, num + len_interval_size, unit)) - legend_labels[-1] = "100" + unit - if max_lcs_len != None: - if num == int(num) and int(len_interval_size) == len_interval_size: - legend_labels_lengths[-1] = "%d %s" % (max_lcs_len, unit) - else: - legend_labels_lengths[-1] = "%.2f %s" % (max_lcs_len, unit) - - # set labels and choose file name - if gff_legend: - label_text = bins[:] - edge_col = None - legend_file_name = "GFF_Shading_Legend_n%d." % lcs_shading_num + filetype - elif max_lcs_len != None: - label_text = legend_labels_lengths[:] - edge_col = "black" - legend_file_name = "Polydotplot_LCS_Shading_Legend_max%d%s_n%d." % (max_lcs_len, unit, lcs_shading_num) + filetype - elif bins != []: - label_text = legend_labels_lengths[:] - edge_col = "black" - legend_file_name = "Polydotplot_LCS_Shading_Legend_%d%s_n%d." % (bins[0], unit, lcs_shading_num) + filetype - else: - label_text = legend_labels[:] - edge_col = "black" - legend_file_name = "Polydotplot_LCS_Shading_Legend_%%len_n%d." % lcs_shading_num + filetype - - if prefix != None and prefix != "": - if not prefix.endswith("-"): - prefix = prefix + "-" - legend_type = "LCS" - if prefix.startswith("custom-matrix"): - prefix = prefix.replace("custom-matrix", "")[1:] - legend_type = "CustomMatrix" - legend_file_name = prefix + legend_file_name.replace("LCS", legend_type) - - # plot legend figure - fig, ax = P.subplots(3, 1, figsize=(len(colors)*2, len(colors)*2)) - for idx in range(len(colors)): - ax[0].bar(data_points[idx]+1, data_points[idx]+1, color=colors[idx], label=label_text[idx], - alpha=alphas[idx], edgecolor=edge_col) - ax[1].bar(data_points[idx]+1, 0, color=colors[idx], label=label_text[idx], - alpha=alphas[idx], edgecolor=edge_col) - ax[2].bar(data_points[idx]+1, 0, color=colors[idx], label=label_text[idx], - alpha=alphas[idx], edgecolor=edge_col) - ax[1].set_ylim(0,1) - ax[2].set_ylim(0,1) - ax[1].legend(ncol=((len(colors)-1)//max_legend_length_row)+1, framealpha=1) # vertical legend - col_num = len(colors) - if len(colors) > max_legend_length_col: - remainder = 0 - if len(colors) % max_legend_length_col != 0: - remainder = 1 - row_num = len(colors) // max_legend_length_col + remainder - remainder = 0 - if len(colors) % row_num != 0: - remainder = 1 - col_num = len(colors) // row_num + remainder - ax[2].legend(ncol=col_num, framealpha=1) # horizontal legend - - P.savefig(legend_file_name) - - return legend_file_name - - -############################### -# Analysis Functions # -############################### - -def wobble_replacement(sequence, general_ambiguity_code, verbose=False): - """ - get all degenerated sequences for sequence with ambiguous residues - (only residues considered that are keys in wobble_dictionary) - """ - - # get positions of ambiguous residues - wobble_pos = [] - for idx in range(len(sequence)): - letter = sequence[idx] - if letter in general_ambiguity_code.keys(): - wobble_pos.append(idx) - - if verbose: - text = "\t%d wobbles" % len(wobble_pos) - logprint(text, start=False, printing=True) - - # replace one wobble through each iteration by all possible residues - # repeat if still wobbles in new kmers - kmer_variants = [sequence] - while True: - if verbose: - text = "\t\t%d kmer variants" % len(kmer_variants) - logprint(text, start=False, printing=True) - temp_kmers = set([]) - for kmer in kmer_variants: - for idx in wobble_pos: - letter = kmer[idx] - if letter in general_ambiguity_code.keys(): - for base in general_ambiguity_code[kmer[idx]]: - newkmer = kmer[:idx] + base + kmer[idx+1:] - temp_kmers.add(newkmer) - wobble = False - for kmer in temp_kmers: - for idx in range(len(kmer)): - letter = kmer[idx] - if letter in general_ambiguity_code.keys(): - wobble = True - break - if wobble: - break - kmer_variants = set(list(temp_kmers)[:]) - if not wobble: - break - - return kmer_variants - -def split_diagonals(data, stepsize=1): - """ - split array if point difference exceeds stepsize - data = sorted list of numbers - """ - return np.split(data, np.where(np.diff(data) != stepsize)[0]+1) - -def longest_common_substring(s1, s2): - m = [[0] * (1 + len(s2)) for i in xrange(1 + len(s1))] - longest, x_longest = 0, 0 - for x in xrange(1, 1 + len(s1)): - for y in xrange(1, 1 + len(s2)): - if s1[x - 1] == s2[y - 1]: - m[x][y] = m[x - 1][y - 1] + 1 - if m[x][y] > longest: - longest = m[x][y] - x_longest = x - else: - m[x][y] = 0 - return longest - -def lcs_from_x_values(x_values): - """ - calculate length of longest common substring based on nested list of numbers - """ - if len(x_values) == 0: - return 0 - # get lengths of each subarray data - lengths = np.array([len(i) for i in x_values]) - return max(lengths) - - -############################### -# Matching Functions # -############################### - -def find_match_pos_diag(seq1, seq2, wordsize, report_lcs=False, rc_option=True, convert_wobbles=False, max_N_percentage=49, type_nuc=True, verbose=False): - """ - find all matching positions with matches >= wordsize - convert matching points into lines of the length of the match - (+ optional handling of ambiguities) - """ - global t1 # timer - - # look for Ns in DNA or Xs in proeins (minimum word size) - if type_nuc == True: - any_residue = "N" - else: - any_residue = "X" - - # read sequences - seq_one = seq1.upper(); len_one = len(seq_one) - seq_two = seq2.upper(); len_two = len(seq_two) - - # set ambiguity code for wobble replacement - general_ambiguity_code = alphabets(type_nuc)[2] # nucleotide_ambiguity_code or aminoacid_ambiguity_code - - # forward - ################################# - kmer_pos_dict_one = {}; kmer_pos_dict_two = {} # dictionaries for both sequences - - # reverse complement - ################################# - kmer_pos_dict_three = {}; kmer_pos_dict_four = {} # dictionaries for both sequences - - # create dictionaries with kmers (wordsize) and there position(s) in the sequence - if rc_option: - data_list = [(str(seq_one), kmer_pos_dict_one), - (str(seq_two), kmer_pos_dict_two), - (str(seq_one), kmer_pos_dict_three), - (str(seq_two.reverse_complement()), kmer_pos_dict_four)] - else: - data_list = [(str(seq_one), kmer_pos_dict_one), - (str(seq_two), kmer_pos_dict_two)] - for (seq, kmer_pos_dict) in data_list: - for i in range(len(seq)-wordsize+1): - kmer = seq[i:i+wordsize] - # discard kmer, if too many Ns included - if kmer.count(any_residue)*100./wordsize <= max_N_percentage: - if not convert_wobbles: - try: - kmer_pos_dict[kmer].append(i) - except KeyError: - kmer_pos_dict[kmer] = [i] - else: - wobbles = False - for item in general_ambiguity_code.keys(): - if item in kmer: - wobbles = True - break - if not wobbles: - try: - kmer_pos_dict[kmer].append(i) - except KeyError: - kmer_pos_dict[kmer] = [i] - else: - kmer_variants = wobble_replacement(kmer, general_ambiguity_code) - for new_kmer in kmer_variants: - # print "\t", new_kmer - try: - kmer_pos_dict[new_kmer].append(i) - except KeyError: - kmer_pos_dict[new_kmer] = [i] - - # find kmers shared between both sequences - matches_for = set(kmer_pos_dict_one).intersection(kmer_pos_dict_two) # forward - matches_rc = set(kmer_pos_dict_three).intersection(kmer_pos_dict_four) # reverse complement - - if verbose: - text = "[matches: %i for; %.i rc]" % (len(matches_for), len(matches_rc)) - logprint(text, start=False, printing=True) - - # create lists of x and y co-ordinates for scatter plot - # keep all coordinates of all shared kmers (may match multiple times) - diag_dict_for = {} - diag_dict_rc = {} - for (match_list, pos_dict1, pos_dict2, diag_dict) in [(matches_for, kmer_pos_dict_one, kmer_pos_dict_two, diag_dict_for), - (matches_rc, kmer_pos_dict_three, kmer_pos_dict_four, diag_dict_rc)]: - for kmer in match_list: - for i in pos_dict1[kmer]: - for j in pos_dict2[kmer]: - diag = i-j - points = set(range(i+1, i+wordsize+1)) - if not diag in diag_dict.keys(): - diag_dict[diag] = points - else: - diag_dict[diag].update(points) - - # convert coordinate points to line start and stop positions - x1 = [] # x values reverse - y1 = [] # y values forward - for diag in diag_dict_for.keys(): - x_values = np.array(sorted(diag_dict_for[diag])) - x1.extend(split_diagonals(x_values)) - y_values = split_diagonals(x_values - diag) - y1.extend(y_values) - - x2 = [] # x values rc - y2 = [] # y values rc - if rc_option: - for diag in diag_dict_rc.keys(): - factor = len_two + diag + 1 - x_values = np.array(sorted(diag_dict_rc[diag])) - x2.extend(split_diagonals(x_values)) - y_values = split_diagonals(factor - x_values, -1) - y2.extend(y_values) - - if verbose: - t1 = time_track(t1) - - if not report_lcs: - return np.array(x1), np.array(y1), np.array(x2), np.array(y2) - else: - # get length of longest common substring based on match lengths - lcs_for = lcs_from_x_values(x1) - lcs_rev = lcs_from_x_values(x2) - return np.array(x1), np.array(y1), np.array(x2), np.array(y2), lcs_for, lcs_rev - -def find_match_pos_regex(seq1, seq2, wordsize, substitution_count=0, report_lcs=False, rc_option=True, convert_wobbles=False, max_N_percentage=49, type_nuc=True, verbose=False): - """ - find all matching positions with matches >= wordsize via regular expression search - fuzzy matching - allow up to substitution_count substitutions - convert matching points into lines of the length of the match - (+ optional handling of ambiguities) - """ - global t1 # timer - - # read sequences - seq_one = seq1.upper(); len_one = len(seq_one) - seq_two = seq2.upper(); len_two = len(seq_two) - - # set ambiguity code for wobble replacement - general_ambiguity_code = alphabets(type_nuc)[2] # nucleotide_ambiguity_code or aminoacid_ambiguity_code - ambiguity_match_dict = alphabets(type_nuc)[3] - - ambiq_residues = "[%s]" % "".join(general_ambiguity_code.keys()) - - # look for Ns in DNA or Xs in proeins (minimum word size) - if type_nuc == True: - any_residue = "N" - else: - any_residue = "X" - - # check for wobble presence - if not (regex.search(ambiq_residues, str(seq_one)) == None and regex.search(ambiq_residues, str(seq_two)) == None): - wobble_found = True - else: - wobble_found = False - - # dictionary for matches - diag_dict_for = {} - diag_dict_rc = {} - counter = [0, 0] - - # one-way matching - if rc_option: - data_list = [(str(seq_one), str(seq_two), diag_dict_for, 0), - (str(seq_one), str(seq_two.reverse_complement()), diag_dict_rc, 1)] - else: - data_list = [(str(seq_one), str(seq_two), diag_dict_for, 0)] - - for seq_query, seq_target, diag_dict, counter_pos in data_list: - # split query sequence into kmers - if not rc_option and counter_pos == 1: - break - - for idx in range(len(str(seq_query))-wordsize+1): - kmer = str(seq_query)[idx:idx+wordsize] - - # skip excessive N/X stretches (big black areas) - if kmer.count(any_residue)*100./wordsize <= max_N_percentage: - # convert kmer to regular expression for wobble_matching - if convert_wobbles and wobble_found: - kmer_string = "" - # replace each residue with matching residues or wobbles - for jdx in range(len(kmer)): - kmer_string += ambiguity_match_dict[kmer[jdx]] - else: - kmer_string = kmer - - # convert to regular expression tolerating substitution errors - if type(substitution_count) == int and substitution_count != 0: - kmer_string = "(%s){s<=%d}" % (kmer_string, substitution_count) - - # search for regular expression in target sequence - kdx = 0 - start = True - if regex.search(kmer_string, seq_target[kdx:]) != None: - counter[counter_pos] += 1 - while regex.search(kmer_string, seq_target[kdx:]) != None: - # search for regular expression pattern in target sequence - result = regex.search(kmer_string, seq_target[kdx:]) - - kmer2 = seq_target[kdx:][result.start():result.end()] - - # skip excessive N/X stretches (big black areas) - if kmer2.count(any_residue)*100./wordsize <= max_N_percentage: - diag = idx-(kdx+result.start()) - points = set(range(idx+1, idx+wordsize+1)) - if not diag in diag_dict.keys(): - diag_dict[diag] = points - else: - diag_dict[diag].update(points) - - kdx += result.start() + 1 - if kdx >= len(seq_target): - break - elif regex.search(kmer_string, seq_target[kdx:]) != None: - counter[counter_pos] += 1 - - if verbose: - text = "%5.i \tforward matches" % counter[0] - text += "\n%5.i \treverse complementary matches" % counter[1] - logprint(text, start=False, printing=True) - - # convert coordinate points to line start and stop positions - x1 = [] # x values reverse - y1 = [] # y values forward - for diag in diag_dict_for.keys(): - x_values = np.array(sorted(diag_dict_for[diag])) - x1.extend(split_diagonals(x_values)) - y_values = split_diagonals(x_values - diag) - y1.extend(y_values) - - x2 = [] # x values rc - y2 = [] # y values rc - if rc_option: - for diag in diag_dict_rc.keys(): - factor = len_two + diag + 1 - x_values = np.array(sorted(diag_dict_rc[diag])) - x2.extend(split_diagonals(x_values)) - y_values = split_diagonals(factor - x_values, -1) - y2.extend(y_values) - - if verbose: - t1 = time_track(t1) - - if not report_lcs: - return np.array(x1), np.array(y1), np.array(x2), np.array(y2) - else: - # get length of longest common substring based on match lengths - lcs_for = lcs_from_x_values(x1) - lcs_rev = lcs_from_x_values(x2) - return np.array(x1), np.array(y1), np.array(x2), np.array(y2), lcs_for, lcs_rev - - -############################### -# Dot Plot Functions # -############################### - -def selfdotplot(input_fasta, wordsize, prefix=None, plot_size=10, label_size=10, filetype='png', type_nuc=True, convert_wobbles=False, substitution_count=0, alphabetic_sorting=False, mirror_y_axis=False, title_length=float("Inf"), title_clip_pos="B", max_N_percentage=49, verbose=False, multi=True, ncols=4, nrows=5, gff_files=[], gff_color_dict={"others": ("grey", 1, 0)}): - """ - self-against-self dotplot - partially from biopython cookbook - """ - - # read sequences - seq_dict, sequences = read_seq(input_fasta) - if seq_dict == {}: - logprint("\nFailed to load sequences") - return [] - - if alphabetic_sorting: - sequences = sorted(sequences) - - # check if at least one input sequence - if len(sequences) == 0: - text = "\n%s\n\nCreating %s selfdotplot images\n%s\n\n=>" % (50*"=", len(sequences), 28*"-") - text += " No sequences provided for selfdotplot!\n\nTerminating polydotplot!" - logprint(text, start=False, printing=True) - return - elif len(sequences) == 1 and multi: - text = "\n\nCreating collage output for single selfdotplot!" - text += "\nRecommendation: Change to individual mode by using '--collage_output n'!\n\n" - logprint(text, start=False, printing=True) - - if multi and (ncols == 0 or nrows == 0): - ncols = max(ncols, 1) - nrows = max(nrows, 1) - text = "\n\nSelfdotplot Collage: Invalid collage - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - if multi and ncols > len(sequences): - ncols = len(sequences) - nrows = 1 - text = "\n\nSelfdotplot Collage: Few sequences - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - elif multi and ncols*(nrows-1) > len(sequences): - nrows = ((len(sequences)-1) // ncols) + 1 - text = "\n\nSelfdotplot Collage: Few sequences - correcting number of rows:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - if multi and not (nrows == 1 and ncols == 1) and plot_size <= label_size/2: - label_size = plot_size * 3 // 2 - text = "Reducing label size for better visualization to %d\n" % label_size - logprint(text, start=False, printing=True) - - # read gff annotation data if provided for shading - if gff_files != None and gff_files != []: - text = "\n%s\n\nReading %s GFF annotation files\n%s\n\n=> %s\n" % (50*"=", len(gff_files), 28*"-", ", ".join(gff_files)) - logprint(text, start=False, printing=True) - if prefix != None and prefix != "": - legend_prefix = prefix + "-Selfdotplot" - else: legend_prefix = "Selfdotplot" - feat_dict = read_gffs(gff_files, color_dict=gff_color_dict, type_nuc=type_nuc, prefix=legend_prefix, filetype=filetype, verbose=verbose) - - global t1 - - print "\n%s\n\nCreating %s selfdotplot images\n%s\n\n=>" % (50*"=", len(sequences), 28*"-"), - log_txt = "\n%s\n\nCreating %s selfdotplot images\n%s\n\n=>" % (50*"=", len(sequences), 28*"-") - - # preparations for file name - name_graph = "Selfdotplots" - if prefix != None: - if not prefix[-1] == "-": - prefix = prefix + "-" - else: - prefix = "" - suffix = "" - if convert_wobbles: - suffix += "_wobbles" - if substitution_count != 0: - suffix += "_S%d" % substitution_count - if multi: - suffix += "_collage" - - # calculate fig ratios - if not multi: - ncols = 1 - nrows = 1 - figsize_x, figsize_y = calc_fig_ratio(ncols, nrows, plot_size) - - P.cla() # clear any prior graph - if multi: - fig = P.figure(figsize=(figsize_x, figsize_y)) - page_counter = 1 - list_of_png_names = [] - - counter = 0 - for seq_name in sequences: - print seq_name, - log_txt += " " + seq_name - - counter += 1 - if not multi: - P.cla() # clear any prior graph - - # read sequence - seq_record = seq_dict[seq_name] - name_seq = seq_record.id - seq_one = seq_record.seq.upper() - length_seq = len(seq_one) - - # get positions of matches - if substitution_count != 0: - # print "RE" - x_lists, y_lists, x_lists_rc, y_lists_rc = find_match_pos_regex(seq_one, seq_one, wordsize, substitution_count=substitution_count, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, type_nuc=type_nuc, verbose=verbose) - else: - # print "DIAG", - x_lists, y_lists, x_lists_rc, y_lists_rc = find_match_pos_diag(seq_one, seq_one, wordsize, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, type_nuc=type_nuc, verbose=verbose) - - # plotting with matplotlib - ################################# - - # combined plotting - if multi: - # plotting subplot with matplotlib - ax = P.subplot(nrows, ncols, counter) # rows, columns, plotnumber - - # shade annotated regions - if gff_files != None and gff_files != []: - if seq_name in feat_dict.keys(): - features = feat_dict[seq_name] - for item in features: - feat_type, start, stop = item - feat_color, strength, zoom = gff_color_dict[feat_type.lower()] - start = max(0, start - zoom - 0.5) - stop = min(length_seq+1, stop + zoom + 0.5) - width = stop - start - ax.add_patch(patches.Rectangle((start, start), # (x,y) - width, width, # width, height - edgecolor=None, linewidth=line_width+zoom, - fill=True, facecolor=feat_color, - alpha=strength)) - - # collect lines - lines = [] - color_list = [] - for (x_lines, y_lines, col) in [(x_lists_rc, y_lists_rc, line_col_rev), (x_lists, y_lists, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # format axes - # print P.xticks()[0], P.yticks()[0] - P.axis('scaled') # make images quadratic - P.xlim(0, length_seq+1) - if mirror_y_axis: - P.ylim(0, length_seq+1) # rotate y axis (point upwards) - else: - P.ylim(length_seq+1, 0) # rotate y axis (point downwards) - P.xlabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.ylabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - - # # use same tick labels for x and y axis - # tick_locs, tick_labels = P.yticks() - # P.xticks(tick_locs) - # P.xlim(0, length_seq+1) - - P.title(unicode_name(shorten_name(name_seq, max_len=title_length, title_clip_pos=title_clip_pos)), fontsize=label_size, fontweight='bold') - # P.title(unicode_name(name_seq), fontsize=label_size*1.3, fontweight='bold') - - # save figure and reinitiate if page is full - if counter == ncols * nrows: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - P.subplots_adjust(hspace=0.5, wspace=0.5) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' % (prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() - - list_of_png_names.append(fig_name) - - counter = 0 - page_counter += 1 - - fig = P.figure(figsize=(figsize_x, figsize_y)) - - # plotting separate figure files - else: # not multi - - fig = P.figure(figsize=(plot_size, plot_size)) # figure size needs to be a square - ax = P.subplot(1, 1, 1) # rows, columns, plotnumber - - # shade annotated regions - if gff_files != None and gff_files != []: - if seq_name in feat_dict.keys(): - features = feat_dict[seq_name] - for item in features: - feat_type, start, stop = item - feat_color, strength, zoom = gff_color_dict[feat_type.lower()] - start = max(0, start - zoom - 0.5) - stop = min(length_seq+1, stop + zoom + 0.5) - width = stop - start - ax.add_patch(patches.Rectangle((start, start), # (x,y) - width, width, # width, height - edgecolor=None, linewidth=line_width+zoom, - fill=True, facecolor=feat_color, - alpha=strength)) - - # collect lines - lines = [] - number = 0 - color_list = [] - for (x_lines, y_lines, col) in [(x_lists_rc, y_lists_rc, line_col_rev), (x_lists, y_lists, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # format axes - P.axis('scaled') # make images quadratic - P.xlim(0, length_seq+1) - if mirror_y_axis: - P.ylim(0, length_seq+1) # rotate y axis (point upwards) - else: - P.ylim(length_seq+1, 0) # rotate y axis (point downwards) - P.xlabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.ylabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - - # # use same tick labels for x and y axis - # tick_locs, tick_labels = P.yticks() - # P.xticks(tick_locs) - # P.xlim(0, length_seq+1) - - P.title(unicode_name(shorten_name(name_seq, max_len=title_length, title_clip_pos=title_clip_pos)), fontsize=label_size*1.3, fontweight='bold') - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s-%d_%s_wordsize%i%s.%s' %(prefix, name_graph, counter, shorten_name(name_seq, max_len=title_length, title_clip_pos=title_clip_pos), wordsize, suffix, filetype) - P.savefig(fig_name, bbox_inches='tight') - - P.close() - P.cla() # clear any prior graph - - list_of_png_names.append(fig_name) - - if multi and counter >= 1: - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - P.subplots_adjust(hspace=0.5, wspace=0.5) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' %(prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() # clear any prior graph - - list_of_png_names.append(fig_name) - - print "\n\nDrawing selfdotplots done" - log_txt += "\n\nDrawing selfdotplots done" - logprint(log_txt, start=False, printing=False) - - return list_of_png_names - -def pairdotplot(input_fasta, wordsize, prefix=None, plot_size=10, label_size=10, filetype='png', type_nuc=True, convert_wobbles=False, substitution_count=0, alphabetic_sorting=False, mirror_y_axis=False, title_length=float("Inf"), title_clip_pos="B", max_N_percentage=49, verbose=False, multi=True, ncols=4, nrows=5, x_label_pos_top=True, length_scaling=True, scale_delim_col="red"): - """ - pairwise dotplot (all-against-all) - """ - - # read sequences - seq_dict, sequences = read_seq(input_fasta) - if seq_dict == {}: - logprint("\nFailed to load sequences") - return [] - - if alphabetic_sorting: - sequences = sorted(sequences) - - # check if at least two input sequences - if len(sequences) < 2: - text = "\n%s\n\nCreating %d paired dotplot image \n%s\n\n=>" % (50*"=", len(sequences)*(len(sequences)-1)/2, 36*"-") - text += " Please provide at least two sequences for pairdotplot!\n\nTerminating paired dotplot!" - logprint(text, start=False, printing=True) - return - elif len(sequences) == 2 and multi: - text = "\n\nCreating collage output for single pairdotplot!" - text += "\nRecommendation: Change to individual mode by using '--collage_output n'!\n\n" - logprint(text, start=False, printing=True) - - if multi and (ncols == 0 or nrows == 0): - ncols = max(ncols, 1) - nrows = max(nrows, 1) - text = "\n\nPairdotplot Collage: Invalid collage settings - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - if multi and ncols > len(sequences)*(len(sequences)-1): - ncols = len(sequences) - nrows = 1 - text = "\n\nPairdotplot Collage: Few sequences - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - elif multi and ncols*(nrows-1) > len(sequences)*(len(sequences)-1): - nrows = ((len(sequences)-1) // ncols) + 1 - text = "\n\nPairdotplot Collage: Few sequences - correcting number of rows:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - - text = "\n%s\n\nCreating %d paired dotplot image for\n%s\n\n=>" % (50*"=", len(sequences)*(len(sequences)-1)/2, 36*"-") - text += ", ".join(sequences) + "\n" - logprint(text, start=False, printing=True) - - if multi and not (nrows == 1 and ncols == 1) and plot_size <= label_size/2: - label_size = plot_size * 3 // 2 - text = "Reducing label size for better visualization to %d\n" % label_size - logprint(text, start=False, printing=True) - - y_label_rotation = "vertical" - # for cartesian coordinate system with mirrored y-axis: plot x labels below plot - if mirror_y_axis: - x_label_pos_top = False - - # preparations for file name - name_graph = "Pairdotplot" - if prefix != None: - if not prefix[-1] == "-": - prefix = prefix + "-" - else: - prefix = "" - suffix = "" - if convert_wobbles: - suffix += "_wobbles" - if substitution_count != 0: - suffix += "_S%d" % substitution_count - if length_scaling: - suffix += "_scaled" - if multi: - suffix += "_collage" - - # calculate fig ratios - if not multi: - ncols = 1 - nrows = 1 - figsize_x, figsize_y = calc_fig_ratio(ncols, nrows, plot_size) - - P.cla() # clear any prior graph - list_of_png_names = [] - if multi: - fig = P.figure(figsize=(figsize_x, figsize_y)) - page_counter = 1 - - # prepare LCS data file - lcs_data_file = open("%sPairdotplot_lcs_data_file%s.txt" % (prefix, suffix.replace("_scaled", "").replace("_collage", "")), 'w') - lcs_data_file.write("\t".join(["#title1", "title2", "len_seq1", "len_seq2", "len_lcs_for", "%_min_seq_len", "len_lcs_rev", "%_min_seq_len"])+"\n") - - counter, seq_counter = 0, 0 - print "Drawing pairwise dotplot...", - log_txt = "Drawing pairwise dotplot..." - if verbose: - seq_text = "" - for idx in range(len(sequences)-1): - if verbose: - print "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]), - seq_text += "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]) - rec_two = seq_dict[sequences[idx]] - name_two = rec_two.id - seq_two = rec_two.seq - len_two = len(seq_two) - - for jdx in range(idx+1, len(sequences)): - rec_one = seq_dict[sequences[jdx]] - name_one = rec_one.id - seq_one = rec_one.seq - len_one = len(seq_one) - - counter += 1 - seq_counter += 1 - if verbose: - print sequences[jdx], - seq_text += " " + sequences[jdx] - elif not seq_counter % 25: - print seq_counter, - log_txt += " " + str(seq_counter) - - # get positions of matches - if substitution_count != 0: - # print "RE" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_regex(seq_one, seq_two, wordsize, substitution_count=substitution_count, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - else: - # print "DIAG" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_diag(seq_one, seq_two, wordsize, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - - # write LCS data file - lcs_data_file.write("\t".join([name_one, name_two, str(len_one), str(len_two), - str(lcs_for), str(round((lcs_for*100./min(len_one, len_two)), 3)), - str(lcs_rev), str(round((lcs_rev*100./min(len_one, len_two)), 3))]) + "\n") - - - # plotting with matplotlib - ################################# - - # combined plotting - if multi: - # plotting subplot with matplotlib - ax = P.subplot(nrows, ncols, counter) # rows, columns, plotnumber - - else: - # calculate figure size for separate figures - if len_one >= len_two: - sizing = (plot_size, max(2, (plot_size)*len_two*1./len_one)) - # sizing = (plot_size, min(plot_size, max(2, (plot_size-2)*len_two*1./len_one+2))) - else: - sizing = (max(2, (plot_size)*len_one*1./len_two), plot_size) - # sizing = (min(plot_size, max(2, (plot_size-2)*len_one*1./len_two+2)), plot_size) - fig = P.figure(figsize=(plot_size, plot_size)) - - ax = P.subplot(1, 1, 1) - - # collect lines - lines = [] - color_list = [] - for (x_lines, y_lines, col) in [(x2, y2, line_col_rev), (x1, y1, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # format axes - P.xlabel(unicode_name(shorten_name(name_one, max_len=title_length, title_clip_pos=title_clip_pos)) + " [%s]" % aa_bp_unit, fontsize=label_size, fontweight='bold', labelpad=4) - P.ylabel(unicode_name(shorten_name(name_two, max_len=title_length, title_clip_pos=title_clip_pos)) + " [%s]" % aa_bp_unit, fontsize=label_size, fontweight='bold', labelpad=4) - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - - # P.axis('scaled') # make images scaled by size ### optional update ### - if not multi: - if length_scaling: - ax.set_aspect(aspect='equal', adjustable='box', anchor='NW') - P.xlim(0, len_one+1) - # xlimit = [0, len_one+1] - if mirror_y_axis: - P.ylim(0, len_two+1) # rotate y axis (point upwards) - else: - P.ylim(len_two+1, 0) # rotate y axis (point downwards) - elif not length_scaling: - P.xlim(0, len_one+1) - # xlimit = [0, len_one+1] - if mirror_y_axis: - P.ylim(0, len_two+1) # rotate y axis (point upwards) - else: - P.ylim(len_two+1, 0) # rotate y axis (point downwards) - else: - max_len = max(len_one, len_two) - P.xlim(0, max_len+1) - # xlimit = [0, max_len+1] - if mirror_y_axis: - P.ylim(0, max_len+1) # rotate y axis (point upwards) - else: - P.ylim(max_len+1, 0) # rotate y axis (point downwards) - - # plot line deliminating shorter sequence - if max_len != len_one: - ax.plot((len_one+1, len_one+1), (0, len_two), marker="", linestyle="--", color=scale_delim_col, markerfacecolor="r") - if max_len != len_two: - ax.plot((0, len_one), (len_two+1, len_two+1), marker="", linestyle="--", color=scale_delim_col, markerfacecolor="r") - - # # use same tick labels for x and y axis - # if P.xlim() == P.ylim(): - # tick_locs, tick_labels = P.yticks() - # P.xticks(tick_locs) - # P.xlim(xlimit) - - # evtl. switch x axis position - if x_label_pos_top: - ax.xaxis.tick_top() - ax.xaxis.set_label_position('top') - P.setp(ax.get_xticklabels(), fontsize=label_size*.9) - P.setp(ax.get_yticklabels(), fontsize=label_size*.9) - - # save figure and reinitiate if page is full - if multi and counter == ncols * nrows: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - if x_label_pos_top: - P.subplots_adjust(hspace=.5, wspace=.5, top=0.95) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=.5, wspace=.5, bottom=0.05) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' %(prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() - - list_of_png_names.append(fig_name) - - counter = 0 - page_counter += 1 - - fig = P.figure(figsize=(figsize_x, figsize_y)) - - # plotting separate figure files - elif not multi: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - if y_label_rotation == "horizontal": - if x_label_pos_top: - P.subplots_adjust(hspace=0.02, wspace=0.02, left=0.13, top=0.95) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=0.02, wspace=0.02, left=0.13, bottom=0.05) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=0.02, wspace=0.02) # space between rows - def 0.4 - - # name and create output files - fig_name = '%s%s-%d_wordsize%i%s.%s' % (prefix, name_graph, counter, wordsize, suffix, filetype) - P.savefig(fig_name) - P.close() - P.cla() - - list_of_png_names.append(fig_name) - fig = P.figure() - - # save figure - if multi and counter >= 1: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - if x_label_pos_top: - P.subplots_adjust(hspace=0.5, wspace=0.5, top=0.95) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=0.5, wspace=0.5, bottom=0.05) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' %(prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() - - list_of_png_names.append(fig_name) - - if not verbose: - print seq_counter, "done" - log_txt += str(seq_counter) + " done" - else: - print "\n%d done" % seq_counter - log_txt += "\n%d done" % seq_counter - logprint(log_txt, start=False, printing=False) - - if verbose: - print - logprint(seq_text, start=False, printing=False) - - return list_of_png_names - -def polydotplot(input_fasta, wordsize, prefix=None, plot_size=10, label_size=10, filetype='png', type_nuc=True, convert_wobbles=False, substitution_count=0, alphabetic_sorting=False, mirror_y_axis=False, title_length=float("Inf"), title_clip_pos="B", max_N_percentage=49, verbose=False, gff_files=[], gff_color_dict={"others": ("grey", 1, 0)}, x_label_pos_top=True, lcs_shading=True, lcs_shading_ref=0, lcs_shading_interval_len=100, lcs_shading_ori=0, lcs_shading_num=5, spacing=0.04, input_user_matrix_file="", user_matrix_print=True, rotate_labels=False): - """ - all-against-all dotplot - derived from dotplot function - - lcs_shading_refs: - 0 color relative to maximum lcs observed in dataset [default] - 1 color by coverage of shorter sequence (e.g. lcs = 70% of seq1) - lcs_shading_ori - 0 forward only - 1 reverse only - 2 both orientations (in opposite plot) - """ - - # read sequences - seq_dict, sequences = read_seq(input_fasta) - if seq_dict == {}: - logprint("\nFailed to load sequences") - return [] - - if alphabetic_sorting: - sequences = sorted(sequences) - - if len(sequences) == 0: - text = "\n%s\n\nCreating %dx%d polydotplot image\n%s\n\n=>" % (50*"=", len(sequences), len(sequences), 30*"-") - text += " No sequences provided for polydotplot!\n\nTerminating polydotplot!" - logprint(text, start=False, printing=True) - return - elif len(sequences) == 1: - text = "\n\nCreating polydotplot for single sequence!" - text += "\nRecommendation: Use selfdotplot via '--plotting_mode 0'!\n\n" - logprint(text, start=False, printing=True) - - text = "\n%s\n\nCreating %dx%d polydotplot image\n%s\n\n=>" % (50*"=", len(sequences), len(sequences), 30*"-") - text += " " + " ".join(sequences) + "\n" - logprint(text, start=False, printing=True) - - # read gff annotation data if provided for shading - if gff_files != None and gff_files != []: - text = "\n%s\n\nReading %s GFF annotation files\n%s\n\n=> %s\n" % (50*"=", len(gff_files), 28*"-", ", ".join(gff_files)) - logprint(text, start=False, printing=True) - if prefix != None and prefix != "": - legend_prefix = prefix + "-Polydotplot" - else: legend_prefix = "Polydotplot" - feat_dict = read_gffs(gff_files, color_dict=gff_color_dict, type_nuc=type_nuc, prefix=legend_prefix, filetype=filetype, verbose=verbose) - - if lcs_shading and not type_nuc: - if lcs_shading_ori != 0: - lcs_shading_ori = 0 - text = "Protein shading does not support reverse complementary matching!\n" - logprint(text, start=False, printing=True) - - # read custom shading matrix & match names of sequences to fasta - if input_user_matrix_file != "" and input_user_matrix_file != None: - logprint("Reading user matrix file: %s" % input_user_matrix_file) - # lcs_shading_ori = 2 - custom_dict = read_matrix(input_user_matrix_file) - if custom_dict != {}: - custom_shading = True - custom_similarity_dict = {} - invalid_entries = [] - custom_max = 0 - custom_min = float("Inf") - for key in custom_dict.keys(): - number_key = [] - - # convert number into float - try: - value = float(custom_dict[key]) - if not "." in custom_dict[key]: - value = int(custom_dict[key]) - custom_max = max(custom_max, value) - custom_min = min(custom_min, value) - except: - value = custom_dict[key] - if value == "": - value = None - invalid_entries.append(key) - # match matrix names with sequence names - for item in key: - if item in sequences: - number_key.append(sequences.index(item)) - else: - number_key.append(-1) - # dictionary with tuple of sorted sequence indices as key and number as value - custom_similarity_dict[tuple(sorted(number_key))] = value - if len(invalid_entries) != 0: - text = "No valid number in custom similarity matrix for %d entries: \n\t" % (len(invalid_entries)) - for key in invalid_entries: - text += str(key) + " - " + str(custom_dict[key]) + "; " - logprint(text[:-2]+"\n") - - text = "Custom user matrix given: min %.2f, max %.2f\n" % (custom_min, custom_max) - - # artificially rounding intervals if likely identity/divergence percentages - if 0 <= custom_min < 1 and 0 < custom_max <= 1: - rounding_factor = 5 - multi_factor = 100 - text += " > artificially rounding custom shading intervals: old (%.2f, %.2f) - " % (custom_min, custom_max) - custom_min = max(0, (multi_factor*custom_min // rounding_factor) * (1.*rounding_factor/multi_factor)) - custom_max = min((multi_factor*custom_max // rounding_factor) * (1.*rounding_factor/multi_factor), 1) - text += "new (%.2f, %2f)\n" % (custom_min, custom_max) - - elif 0 <= custom_min < 100 and 0 < custom_max <= 100: - rounding_factor = 5 - text += " > artificially rounding custom shading intervals: old (%.2f, %.2f) - " % (custom_min, custom_max) - custom_min = max(0, (custom_min // rounding_factor) * rounding_factor) - custom_max = min((custom_max // rounding_factor) * rounding_factor, 100) - text += "new (%d, %d)\n" % (custom_min, custom_max) - - logprint(text) - - else: - custom_shading = False - - name_graph = "Polydotplot" - suffix = "" - if convert_wobbles: - suffix += "_wobbles" - if substitution_count != 0: - suffix += "_S%d" % substitution_count - if custom_shading: - suffix += "_matrix" - if lcs_shading: - suffix += "_%dshades_ref%d_ori%s" % (lcs_shading_num+1, lcs_shading_ref, lcs_shading_ori) - if "ref2" in suffix and type_nuc: - suffix = suffix.replace("ref2", "%dbp" % lcs_shading_interval_len) - elif "ref2" in suffix: - suffix = suffix.replace("ref2", "%daa" % lcs_shading_interval_len) - - - # name and create output files (names derived from SEQNAME) - if prefix != None and str(prefix) != "": - prefix = str(prefix) + "-" - else: - prefix = "" - - # preparations for background shading - if lcs_shading or custom_shading: - # create color range white to grey - colors = create_color_list(lcs_shading_num+1, color_map=None, logging=True) - colors_2 = create_color_list(lcs_shading_num+1, color_map="OrRd", logging=True) - - if custom_shading: - text = "Custom Matrix Colors: " + ", ".join(colors_2) - - # write lcs lengths to file - lcs_data_file = open("%sPolydotplot_lcs_data_file%s.txt" % (prefix, suffix.replace("_scaled", "").replace("_collage", "")), 'w') - lcs_data_file.write("\t".join(["#title1", "title2", "len_seq1", "len_seq2", "len_lcs_for", "%_min_seq_len", "len_lcs_rev", "%_min_seq_len"])+"\n") - - # compare sequences pairwise - save lcs and line information in dictionary for plotting - data_dict = {} # keys = tuple(idx, jdx), value = x1, y1, x2, y2 (line positions) - lcs_dict = {} # keys = tuple(idx, jdx), value = length of lcs: lcs_len or (lcs_for, lcs_rev) - for_lcs_set = set([]) # keep lengths to calculate max (excluding self comparisons) - rev_lcs_set = set([]) # keep lengths to calculate max (all) - - text = "\nTotal plot count: %d" % (len(sequences)*(len(sequences))) - text += "\nTotal calculations: %d" % (len(sequences)*(len(sequences)+1)/2) - logprint(text, start=False, printing=True) - - print "\nCalculating shared regions and lengths of longest_common_substring...", - log_txt = "\nCalculating shared regions and lengths of longest_common_substring..." - # determine matches and length of lcs by comparing all sequence pairs - if verbose: - seq_text = "" - counter = 0 - for idx in range(len(sequences)): - if verbose: - print "\n%d\t%s vs." % ((counter+1), sequences[idx]), - seq_text += "\n%d\t%s vs." % ((counter+1), sequences[idx]) - rec_two = seq_dict[sequences[idx]] - name_two = rec_two.id - seq_two = rec_two.seq - len_two = len(seq_two) - - for jdx in range(idx, len(sequences)): - rec_one = seq_dict[sequences[jdx]] - name_one = rec_one.id - seq_one = rec_one.seq - len_one = len(seq_one) - - counter += 1 - if verbose: - print sequences[jdx], - seq_text += " " + sequences[jdx] - elif len(sequences) < 5: - print "\t%s (%d %s), %s (%d %s)" % (name_one, len_one, aa_bp_unit, name_two, len_two, aa_bp_unit) - log_txt += "\t%s (%d %s), %s (%d %s)\n" % (name_one, len_one, aa_bp_unit, name_two, len_two, aa_bp_unit) - else: - if not counter % 25: - print counter, - log_txt += str(counter) - - # get positions of matches & length of longest common substring based on match lengths - if substitution_count != 0: - # print "RE" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_regex(seq_one, seq_two, wordsize, substitution_count=substitution_count, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - else: - # print "DIAG" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_diag(seq_one, seq_two, wordsize, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - data_dict[(idx, jdx)] = x1[:], y1[:], x2[:], y2[:] - lcs_dict[idx, jdx] = lcs_for, lcs_rev - - if idx != jdx: - for_lcs_set.add(lcs_for) - rev_lcs_set.add(lcs_rev) - - lcs_data_file.write("\t".join([name_one, name_two, str(len_one), str(len_two), - str(lcs_for), str(round((lcs_for*100./min(len_one, len_two)), 3)), - str(lcs_rev), str(round((lcs_rev*100./min(len_one, len_two)), 3))]) + "\n") - - if not verbose: - print len(sequences)*(len(sequences)+1)/2, " done\n" - log_txt += str(len(sequences)*(len(sequences)+1)/2) + " done\n" - else: - print "\n%d done" % (len(sequences)*(len(sequences)+1)/2) - log_txt += "\n%d done" % (len(sequences)*(len(sequences)+1)/2) - logprint(log_txt, start=False, printing=False) - - if verbose: - logprint ("\n\nlcs_dict\n" + str(lcs_dict)) - if custom_shading: - logprint ("\ncustom_dict\n" + str(custom_dict)) - logprint ("\ncustom_similarity_dict\n\n" + str(custom_similarity_dict)) - - if verbose: - print - logprint(seq_text+"\n", start=False, printing=False) - - if lcs_shading_ref == 2: - color_bins = [] - text = "\nLCS lengh bins: " - for idx in range(lcs_shading_num): - color_bins.append(lcs_shading_interval_len*(idx+1)) - text += " " + str(lcs_shading_interval_len*(idx+1)) - logprint(text, start=False, printing=True) - - # calculate maximum lcs length - if lcs_shading_ori == 0: # forward only - if len(for_lcs_set) != 0: - max_lcs = max(for_lcs_set) - else: - max_lcs = None - elif lcs_shading_ori == 1: # reverse complement only - if len(rev_lcs_set) != 0: - max_lcs = max(rev_lcs_set) - else: - max_lcs = None - else: # both orientations - if len(rev_lcs_set) != 0 and len(for_lcs_set) != 0: - max_lcs = max(max(rev_lcs_set), max(for_lcs_set)) - elif len(rev_lcs_set) != 0: - max_lcs = max(rev_lcs_set) - elif len(for_lcs_set) != 0: - max_lcs = max(for_lcs_set) - else: - max_lcs = None - - if not max_lcs == None: - text = "Maximum LCS: %d %s" % (max_lcs, aa_bp_unit) - logprint(text, start=False, printing=True) - if custom_shading: - text = "Maximum custom value: %d\n" % custom_max - logprint(text, start=False, printing=True) - - # count sequences - ncols = len(sequences); nrows = len(sequences) - - # get sequence lengths to scale plot widths and heights accordingly - size_ratios = [] - for item in sequences: - size_ratios.append(len(seq_dict[item].seq)) - - P.cla() # clear any prior graph - # use GridSpec to resize plots according to sequence length - if mirror_y_axis: - height_ratios = size_ratios[::-1] - else: - height_ratios = size_ratios[:] - gs = gridspec.GridSpec(nrows, ncols, - width_ratios=size_ratios, - height_ratios=height_ratios) - fig = P.figure(figsize=(plot_size, plot_size)) - - # for cartesian coordinate system with mirrored y-axis: plot x labels below plot - if mirror_y_axis and representation == 1: - x_label_pos_top = True - elif mirror_y_axis or representation == 2: - x_label_pos_top = False - - # print y labels on the right, if upper right triangle is displayed - if (representation == 1 and not mirror_y_axis) or (representation == 2 and mirror_y_axis): - y_label_pos = 0 # last column - else: # left y label - y_label_pos = 1 # first column - - # determine label orientations - if len(sequences) > 5 or rotate_labels: - x_label_rotation = 45 - y_label_rotation = "horizontal" - if x_label_pos_top: - xhalign = 'left' - xvalign = 'bottom' - else: - xhalign = 'right' - xvalign = 'top' - yhalign = "right" - else: - x_label_rotation = "horizontal" - y_label_rotation = "vertical" - xvalign = "center" - xhalign = "center" - yhalign = "center" - yvalign = 'center' - - # check combination of shading parameters for triangular output - if representation != 0 and lcs_shading and custom_shading: # both directions in triangle - logprint("\nAttention: For triangular output custom-shading and LCS shading cannot be combined!\n") - elif representation != 0 and lcs_shading and lcs_shading_ori == 2: # both directions in triangle - logprint("\nAttention: For triangular output LCS shading for both orientations is combined to max of both orientations!\n") - - print "\nDrawing polydotplot...", - log_txt = "\nDrawing polydotplot..." - - # draw subplots - if verbose: - if lcs_shading and custom_shading: - lcs_text = "\n" + "\t".join(["#Seq1", "Seq2", "LCS for [%s]" %aa_bp_unit, "LCS for [%s]" %aa_bp_unit, "Custom matrix value", "Matrix color index", "LCS color index"]) + "\n" - elif lcs_shading: - lcs_text = "\n" + "\t".join(["#Seq1", "Seq2", "LCS for [%s]" %aa_bp_unit, "LCS for [%s]" %aa_bp_unit, "LCS color index for", "LCS color index rev"]) + "\n" - elif custom_shading: - lcs_text = "\n" + "\t".join(["#Seq1", "Seq2", "Custom matrix value", "Color index for", "Color index rev"]) + "\n" - - if verbose: - seq_text = "" - counter, seq_counter = 0, 0 - for idx in range(len(sequences)): - if verbose: - print "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]), - seq_text += "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]) - rec_two = seq_dict[sequences[idx]] - len_two = len(rec_two.seq) - name_two = rec_two.id - - for jdx in range(idx, len(sequences)): - rec_one = seq_dict[sequences[jdx]] - len_one = len(rec_one.seq) - name_one = rec_one.id - - counter += 1 - seq_counter += 1 - if verbose: - print sequences[jdx], - seq_text += " " + sequences[jdx] - elif not seq_counter % 25: - print seq_counter, - log_txt += str(seq_counter) - - # optional shade background according to length of LCS and/or user matrix - ######################################################################### - - # get interval based on LCS - background_colors = [None, None] - if lcs_shading and (lcs_shading_ref==1 or lcs_shading_ref==2 or max_lcs!=None): # self plot max_lcs_for == None - lcs_len = lcs_dict[(idx, jdx)] - l1 = lcs_len[0] # forward - l2 = lcs_len[1] # reverse complement - - lcs_shading_bool = True - - # calculate shading acc. to chosen option - if lcs_shading_ref == 1: # percentage of shorter sequence - color_idx0 = min(len(colors)-1, l1*lcs_shading_num // min(len_one, len_two)) - color_idx1 = min(len(colors)-1, l2*lcs_shading_num // min(len_one, len_two)) - elif lcs_shading_ref == 2: # by given interval size - color_idx0 = min(len(colors)-1, l1 // lcs_shading_interval_len) - color_idx1 = min(len(colors)-1, l2 // lcs_shading_interval_len) - if color_idx0 >= len(colors): - color_idx0 = len(colors) - if color_idx1 >= len(colors): - color_idx1 = len(colors) - else: # percentage of maximum lcs length - color_idx0 = min(len(colors)-1, l1*lcs_shading_num // max_lcs) - color_idx1 = min(len(colors)-1, l2*lcs_shading_num // max_lcs) - else: - lcs_shading_bool = False - - # get interval based on custom matrix - if custom_shading: - # matrix value - try: - custom_value = custom_similarity_dict[(idx, jdx)] - except: - custom_value = "" - - # bottom left triangle = LCS forward/reverse or best of both - if lcs_shading_bool: - if lcs_shading_ori == 0: # forward - color_idx1 = color_idx0 - elif lcs_shading_ori == 2: # both directions - color_idx1 = max(color_idx0, color_idx1) - - # top right triangle = custom value (not colored if text matrix provided) - if type(custom_value) == int or type(custom_value) == float: - color_idx0 = int((custom_value-custom_min)*lcs_shading_num // (custom_max-custom_min)) - # no color if string is proviced - else: - color_idx0 = 0 - - # use best LCS of both orientations for coloring triangle with two-ori-LCS - if representation != 0 and lcs_shading_ori == 2: # both directions in triangle - color_idx0, color_idx1 = max(color_idx0, color_idx1), max(color_idx0, color_idx1) - - # set colors dependent on lcs dependent on orientation - if lcs_shading_bool and not custom_shading: - if idx != jdx: - if lcs_shading_ori == 0: - color_idx1 = color_idx0 - elif lcs_shading_ori == 1: - color_idx0 = color_idx1 - background_colors[0] = colors[color_idx0] - background_colors[1] = colors[color_idx1] - # for selfcomparison, only color reverse complement - elif lcs_shading_ori != 0 and not custom_shading: - background_colors[0] = colors[color_idx1] - # set different colors for shading by LCS + user matrix - elif lcs_shading_bool and custom_shading: - # print colors, background_colors, color_idx0, color_idx1 - background_colors[0] = colors_2[color_idx0] - background_colors[1] = colors[color_idx1] - # set grey color range for user matrix if no LCS shading - elif custom_shading: - background_colors[0] = colors[color_idx0] - background_colors[1] = colors[color_idx0] - - if verbose: - if custom_shading and lcs_shading_bool: - lcs_text += "\t".join([name_one, name_two, str(lcs_len[0]), str(lcs_len[1]), str(custom_value), str(color_idx0), str(color_idx1)]) + "\n" - elif lcs_shading_bool: - lcs_text += "\t".join([name_one, name_two, str(lcs_len[0]), str(lcs_len[1]), str(color_idx0), str(color_idx1)]) + "\n" - elif custom_shading: - lcs_text += "\t".join([name_one, name_two, str(custom_value), str(color_idx0), str(color_idx1)]) + "\n" - - # calculate figure position in polyplot - # diagonal (self-dotplots) - if idx == jdx: - if mirror_y_axis: - seq_num = sequences.index(name_one)+1 - counter1 = seq_num + len(sequences) * (len(sequences)-seq_num) - counter = counter + (counter - 1) // (nrows) - else: - # skip positions below diagonal - counter1 = counter + (counter - 1) // (nrows) # + row_pos - counter = counter1 - counters = [counter1] - - # draw both graphs at once (due to symmetry) - else: - if mirror_y_axis: - col_pos = sequences.index(name_two)+1 - row_pos = len(sequences) - (sequences.index(name_one)+1) - counter1 = row_pos * ncols + col_pos - counter2 = (ncols - col_pos) * ncols + ncols - row_pos - else: - counter1 = counter - col_pos = (counter - 1) % ncols - row_pos = (counter - 1) // (nrows) - counter2 = col_pos * ncols + row_pos + 1 - counters = [counter1, counter2] # lower, upper - - if len(counters) == 2: - seq_counter += 1 - if not verbose and not seq_counter % 25: - print seq_counter, - log_txt += str(seq_counter) - - x_lists, y_lists, x_lists_rc, y_lists_rc = data_dict[(idx, jdx)] - - # plot diagram(s) - for kdx in range(len(counters)): - - if representation == 0 or len(counters) == 1 or (representation == 1 and kdx == 0) or (representation == 2 and kdx == 1): - - fig_pos = counters[kdx] - # plotting subplot with matplotlib - ax = P.subplot(gs[fig_pos-1]) # rows, columns, plotnumber - - # shade annotated regions if gff file(s) provided - if idx == jdx and gff_files != None and gff_files != []: - if name_one in feat_dict.keys(): - features = feat_dict[name_one] - if len_two != len_one: - logprint("Polydot GFF shading for diagonal fields - nequal length error!") - return - for item in features: - feat_type, start, stop = item - feat_color, strength, zoom = gff_color_dict[feat_type.lower()] - start = max(0, start - zoom - 0.5) - stop = min(len_one+1, stop + zoom + 0.5) - width = stop - start - ax.add_patch(patches.Rectangle((start, start), # (x,y) - width, width, # width, height - edgecolor=None, linewidth=line_width+zoom, - fill=True, facecolor=feat_color, - alpha=strength)) - - # if custom matrix value printed into upper matrix triangle, skip data plotting - # text print in top triangle - if user_matrix_print and custom_shading and kdx==0 and idx!=jdx: - data_plotting = False - # dotplot in bottom triangle - else: - data_plotting = True - - # mirror plot, if plotting below diagonal - if kdx == 0: - l1, l2 = len_one, len_two - n1, n2 = name_one, name_two - x1, y1 = x_lists, y_lists - x2, y2 = x_lists_rc, y_lists_rc - else: - l2, l1 = len_one, len_two - n2, n1 = name_one, name_two - x1, y1 = y_lists, x_lists - x2, y2 = y_lists_rc, x_lists_rc - - if mirror_y_axis: - x1, y1, x2, y2 = y1, x1, y2, x2 - n1, n2 = n2, n1 - - if data_plotting: - # collect lines - lines = [] - color_list = [] - for (x_lines, y_lines, col) in [(x2, y2, line_col_rev), (x1, y1, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # plot value provided by customer instead of dotplot - else: - alignment = {'horizontalalignment': 'center', 'verticalalignment': 'center'} - # P.text(0.5, 0.5, custom_value, size='medium', transform=ax.transAxes, **alignment) - P.text(0.5, 0.5, custom_value, size=label_size*1.5, transform=ax.transAxes, **alignment) - # P.text(0.5, 0.5, custom_value, size=label_size*1.5, transform=ax.transAxes, - # horizontalalignment='center', verticalalignment='center', color="black") - - if custom_shading: - # omit diagonal - if idx == jdx: - ax.set_facecolor("white") - # use white background for text fields (top right triangle only [kdx 0]) - elif type(custom_value) != int and type(custom_value) != float and kdx == 0: - ax.set_facecolor("white") - else: - ax.set_facecolor(background_colors[kdx]) - # set background color if lcs shading - elif lcs_shading_bool and background_colors[kdx] != None: - ax.set_facecolor(background_colors[kdx]) - - # set axis limits - # P.xlim(0, l1+1) - if mirror_y_axis: - P.xlim(0, l2+1) - P.ylim(0, l1+1) # rotate y axis (point upwards) - else: - P.xlim(0, l1+1) - P.ylim(l2+1, 0) # rotate y axis (point downwards) - - ## axis labelling - ################## - - # determine axis positions - if x_label_pos_top: - ax.xaxis.tick_top() - ax.xaxis.set_label_position('top') - x_label_bool = fig_pos <= ncols - x_tick_bool = fig_pos > ncols*(ncols-1) - else: - x_label_bool = fig_pos > ncols*(ncols-1) - x_tick_bool = fig_pos <= ncols - - # settings for y labels on right side - if y_label_pos == 0: # right label - ax.yaxis.tick_right() - ax.yaxis.set_label_position("right") - label_dist = 30 - else: - label_dist = 8 - - # x axis labels dependent on plot position/number - if x_label_bool: # x title and labels on top or bottom - P.xlabel(unicode_name(shorten_name(n1, max_len=title_length, title_clip_pos=title_clip_pos)), fontsize=label_size, rotation=x_label_rotation, verticalalignment=xvalign, horizontalalignment=xhalign, fontweight='bold', labelpad=8) # axis naming - if not x_label_rotation in ["horizontal", "vertical"]: - P.setp(ax.get_xticklabels(), fontsize=label_size*.9, rotation="vertical") - else: - P.setp(ax.get_xticklabels(), fontsize=label_size*.9, rotation=x_label_rotation) - elif x_tick_bool and x_label_pos_top: # x ticks on bottom row - ax.xaxis.tick_bottom() # ticks without labels on bottom - P.setp(ax.get_xticklabels(), fontsize=label_size, rotation=x_label_rotation, visible=False) - elif x_tick_bool: # x ticks on top row - ax.xaxis.tick_top() # # ticks without labels on top - P.setp(ax.get_xticklabels(), fontsize=label_size, rotation=x_label_rotation, visible=False) # inner diagrams without labelling - elif idx == jdx and representation != 0: - if not mirror_y_axis and representation == 1: # upper - ax.xaxis.tick_bottom() - elif mirror_y_axis and representation == 2: # lower - ax.xaxis.tick_top() - elif mirror_y_axis and representation == 1: # upper - ax.xaxis.tick_bottom() - elif not mirror_y_axis and representation == 2: # lower - ax.xaxis.tick_top() - P.setp(ax.get_xticklabels(), visible=False) # inner diagrams without labelling - else: # no x ticks on internal rows - ax.axes.get_xaxis().set_visible(False) - - # y axis labels dependent on plot position/number - if fig_pos % ncols == y_label_pos or (ncols == 1 and nrows == 1): # y title and labels in 1st column - P.ylabel(unicode_name(shorten_name(n2, max_len=title_length, title_clip_pos=title_clip_pos)), fontsize=label_size, rotation=y_label_rotation, verticalalignment=yvalign, horizontalalignment=yhalign, fontweight='bold', labelpad=label_dist) - P.setp(ax.get_yticklabels(), fontsize=label_size*.9) # axis naming - elif fig_pos % ncols == 0: # y ticks in last column - ax.yaxis.tick_right() - P.setp(ax.get_yticklabels(), visible=False) # inner diagrams without labelling - elif idx == jdx and representation != 0: - if not mirror_y_axis and representation == 1: # upper - ax.yaxis.tick_left() - elif mirror_y_axis and representation == 2: # lower - ax.yaxis.tick_left() - elif mirror_y_axis and representation == 1: # upper - ax.yaxis.tick_right() - elif not mirror_y_axis and representation == 2: # lower - ax.yaxis.tick_right() - P.setp(ax.get_yticklabels(), visible=False) # inner diagrams without labelling - else: - ax.axes.get_yaxis().set_visible(False) - - if not verbose: - print seq_counter, "done" - log_txt += str(seq_counter) + " done" - else: - print "\n%d done" % seq_counter - log_txt += "\n%d done" % seq_counter - logprint(log_txt, start=False, printing=False) - - if verbose: - try: - logprint(lcs_text, start=False, printing=True) - except: - pass - - # finalize layout - margins & spacing between plots - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - # gs.tight_layout(fig, h_pad=.02, w_pad=.02) # less overlapping tick labels, but also disturbingly large spacing - if y_label_rotation == "horizontal": - if x_label_pos_top: - P.subplots_adjust(hspace=spacing, wspace=spacing, left=0.13, top=0.87) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=spacing, wspace=spacing, left=0.13, bottom=0.13) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=spacing, wspace=spacing) # space between rows - def 0.4 - - # save figure and close instance - fig_name = '%s%s_wordsize%i%s.%s' % (prefix, name_graph, wordsize, suffix, filetype) - P.savefig(fig_name) - P.close() - P.cla() - - - # create figure color legend - if lcs_shading: - if lcs_shading_ref == 1: # percentage of shorter sequence - legend_file_name = legend_figure(colors, lcs_shading_num, unit="%", filetype=filetype, prefix=prefix) - elif lcs_shading_ref == 2: # interval sizes - legend_file_name = legend_figure(colors, lcs_shading_num, unit=aa_bp_unit, filetype=filetype, prefix=prefix, bins=color_bins) - else: # relative of maximum lcs - legend_file_name = legend_figure(colors, lcs_shading_num, unit=aa_bp_unit, filetype=filetype, prefix=prefix, max_lcs_len=max_lcs) - - if custom_shading: - custom_prefix = "custom-matrix-" + prefix - legend_file_name_custom = legend_figure(colors_2, lcs_shading_num, unit="%", filetype=filetype, prefix=custom_prefix, max_lcs_len=custom_max, min_lcs_len=custom_min) - - if lcs_shading and custom_shading: - return [fig_name, legend_file_name, legend_file_name_custom] - elif lcs_shading: - return [fig_name, legend_file_name] - elif custom_shading: - return [fig_name, legend_file_name_custom] - else: - return [fig_name] - - -############################### -# Function Call # -############################### - -def main(seq_list, wordsize, modes=[0, 1, 2], prefix=None, plot_size=10, label_size=10, filetype="png", type_nuc=True, convert_wobbles=False, substitution_count=0, rc_option=True, alphabetic_sorting=False, gff=None, multi=True, ncols=1, nrows=1, lcs_shading=True, lcs_shading_num=5, lcs_shading_ref=0, lcs_shading_interval_len=100, lcs_shading_ori=0, gff_color_config_file="", input_user_matrix_file="", user_matrix_print=False, length_scaling=True, title_length=50, title_clip_pos="B", spacing=0.04, max_N_percentage=49, mirror_y_axis=False, verbose=False): - - global t1, line_col_rev - - # check input variables - if convert_wobbles and max_N_percentage > 49: - max_N_percentage = 49 - if type_nuc: - ambiq_res = "N" - else: - ambiq_res = "X" - text = "Provide valid max_N_percentage, kmers with >50%% %ss are ignored\n" % (ambiq_res) - logprint(text, start=False, printing=True) - - if filetype not in ["png", "pdf", "svg"]: - text = "Provide valid file type - png, pdf, or svg - given:%s\n" % filetype - logprint(text, start=False, printing=True) - filetype = "png" - - # read gff color config file if provided - if len(input_gff_files) != 0 and input_gff_files != None: - if gff_color_config_file not in ["", None]: - text = "\n%s\n\nReading GFF color configuration file\n%s\n\n=> %s\n" % (50*"=", 28*"-", gff_color_config_file) - logprint(text, start=False, printing=True) - gff_feat_colors = read_gff_color_config(gff_color_config_file) - else: - gff_feat_colors = {} - if gff_color_config_file not in ["", None]: - text = "Please provide GFF annotation files to use configuration file", gff_color_config_file - logprint(text, start=False, printing=True) - - # if color is set to white, reverse complementary matches are skipped - if not rc_option: - line_col_rev = "white" # reverse matches not calculated - elif not type_nuc: - logprint("Reverse complement deactivated for proteins!") - line_col_rev = "white" # reverse matches not calculated - - mode_text = [] - for item in modes: - mode_text.append(str(item)) - text = "%s\n\nRunning plotting modes %s" % (50*"=", ", ".join(mode_text)) - logprint(text, start=False, printing=True) - - - # create dotplots - ########################################## - - # self dotplots - t1 = time.time() - if 0 in modes: - list_of_png_names = selfdotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, title_clip_pos=title_clip_pos, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, multi=multi, ncols=ncols, nrows=nrows, gff_files=gff, gff_color_dict=gff_feat_colors, mirror_y_axis=mirror_y_axis, max_N_percentage=max_N_percentage, verbose=verbose) - t1 = time_track(t1) - if list_of_png_names != [] and list_of_png_names != None: - text = "-> Image file(s): %s\n" % ", ".join(list_of_png_names) - else: - text = "No image files were created!\n" - logprint(text, start=False, printing=True) - logprint(50*"=") - - # paired dotplots - if 1 in modes: - if multi: - list_of_png_names = pairdotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, title_clip_pos=title_clip_pos, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, multi=multi, ncols=ncols, nrows=nrows, length_scaling=length_scaling, mirror_y_axis=mirror_y_axis, max_N_percentage=max_N_percentage, verbose=verbose) - t1 = time_track(t1) - else: - if not length_scaling: - text = "\nPairwise dotplot with individual output files scaled by sequence length automatically!" - logprint(text, start=False, printing=True) - list_of_png_names = pairdotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, title_clip_pos=title_clip_pos, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, multi=multi, ncols=ncols, nrows=nrows, length_scaling=True, mirror_y_axis=mirror_y_axis, max_N_percentage=max_N_percentage, verbose=verbose) - t1 = time_track(t1) - if list_of_png_names != [] and list_of_png_names != None: - text = "-> Image file(s): %s\n" % ", ".join(list_of_png_names) - else: - text = "No image files were created!\n" - logprint(text, start=False, printing=True) - logprint(50*"=") - - # all-against-all dotplot - if 2 in modes: - list_of_png_names = polydotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, title_clip_pos=title_clip_pos, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, lcs_shading=lcs_shading, lcs_shading_num=lcs_shading_num, lcs_shading_ref=lcs_shading_ref, lcs_shading_interval_len=lcs_shading_interval_len, lcs_shading_ori=lcs_shading_ori, input_user_matrix_file=input_user_matrix_file, user_matrix_print=user_matrix_print, spacing=spacing, gff_files=gff, gff_color_dict=gff_feat_colors, mirror_y_axis=mirror_y_axis, max_N_percentage=max_N_percentage, verbose=verbose) - t1 = time_track(t1) - if list_of_png_names != [] and list_of_png_names != None: - text = "-> Image file(s): %s\n" % ", ".join(list_of_png_names) - else: - text = "No image files were created!\n" - logprint(text, start=False, printing=True) - logprint(50*"=") - - text = "\n" + 50 * "#" + "\n" + 50 * "#" - text += "\n\nThank you for using FlexiDot!\n" - logprint(text, start=False, printing=True) - -# testing mode for debugging -trial_mode = False -#trial_mode = True - -# parameters = check_input(sys.argv) -parameters = check_input(sys.argv, trial_mode=trial_mode) - -# read out parameters -commandline, auto_fas, input_fasta, output_file_prefix, collage_output, m_col, n_row, filetype, type_nuc, input_gff_files, gff_color_config_file, wordsize, plotting_modes, wobble_conversion, substitution_count, rc_option, alphabetic_sorting, lcs_shading, lcs_shading_num, lcs_shading_ref, lcs_shading_interval_len, lcs_shading_ori, input_user_matrix_file, user_matrix_print, plot_size, line_width, line_col_for, line_col_rev, x_label_pos_top, label_size, spacing, length_scaling, title_length, title_clip_pos, max_N_percentage, mirror_y_axis, representation, verbose = parameters - -# evtl. overwrite parameters for testing purposes in trial mode -if trial_mode: - input_fasta = ["test-sequences-8.fas"] - input_gff_files = ["Seq2_annotations.gff3"] - # input_user_matrix_file = "matrix.txt" - # user_matrix_print = True - output_file_prefix = "#Test" - plot_size = 10 - plotting_modes = [0,1,2] - plotting_modes = [2] - lcs_shading = False - lcs_shading = True - lcs_shading_ref = 2 - lcs_shading_num = 4 - lcs_shading_ori = 0 - lcs_shading_interval_len = 15 - wordsize = 10 - wordsize = 7 - x_label_pos_top = True - filetype = "pdf" - filetype = "png" - mirror_y_axis = False - mirror_y_axis = True - - output_file_prefix = "#R-upper" - representation = 0 # both - representation = 1 # upper - representation = 2 # lower - - wobble_conversion = False - wobble_conversion = True - - substitution_count = 0 - - rc_option = True - rc_option = False - label_size = 10 - - verbose = False - verbose = True - -if auto_fas: - path = os.path.dirname(os.path.abspath(__file__)) - files_long = glob.glob(path+"/*.fasta") - files_long.extend(glob.glob(path+"/*.fas")) - files_long.extend(glob.glob(path+"/*.fa")) - files_long.extend(glob.glob(path+"/*.fna")) - input_fasta = [] - for i in files_long: - if not "combined" in i: - filename = i[i.rfind('\\')+1:] - input_fasta.append(filename) - -if trial_mode: - # start logging file - logprint(commandline, start=True, printing=False, prefix=output_file_prefix) - -main(input_fasta, wordsize, modes=plotting_modes, prefix=output_file_prefix, plot_size=plot_size, label_size=label_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=wobble_conversion, substitution_count=substitution_count, rc_option=rc_option, gff=input_gff_files, multi=collage_output, ncols=m_col, nrows=n_row, alphabetic_sorting=alphabetic_sorting, lcs_shading=lcs_shading, lcs_shading_num=lcs_shading_num, lcs_shading_ref=lcs_shading_ref, lcs_shading_interval_len=lcs_shading_interval_len, lcs_shading_ori=lcs_shading_ori, gff_color_config_file=gff_color_config_file, input_user_matrix_file=input_user_matrix_file, user_matrix_print=user_matrix_print, length_scaling=length_scaling, title_length=title_length, title_clip_pos=title_clip_pos, spacing=spacing, max_N_percentage=max_N_percentage, mirror_y_axis=mirror_y_axis, verbose=verbose) - - diff --git a/code/flexidot_v1.05.py b/code/flexidot_v1.05.py deleted file mode 100644 index f326726..0000000 --- a/code/flexidot_v1.05.py +++ /dev/null @@ -1,3390 +0,0 @@ -#!/usr/bin/python2.7 -# -*- coding: utf-8 -*- - -""" -FlexiDot Version 1.05 - -FlexiDot: Highly customizable ambiguity-aware dotplots for visual sequence investigation - -Kathrin M. Seibt, Thomas Schmidt and Tony Heitkam -Institute of Botany, TU Dresden, Dresden, 01277, Germany - -Bioinformatics (2018) Vol. 34 (20), 3575–3577, doi 10.1093/bioinformatics/bty395 -""" - - -############################### -# Requirements # -############################### - -# import system modules -import os, glob -import time, datetime -import sys -import shutil, getopt -import unicodedata - -def module_install_command(module_name, upgrade=False): - """ - create installation commands for Python modules and print information - """ - if upgrade: - load_command = "python -m pip install --upgrade %s" % module_name - else: - load_command = "python -m pip install %s" % module_name - - try: - logprint("Installing Python module: %s\n\t%s\n" % (module_name, load_command)) - except: - print "Installing Python module: %s\n\t%s\n" % (module_name, load_command) - - return load_command - -def load_modules(): - """ - load Python modules, if possible - otherwise try to install them - """ - # make module names global - global cllct, gridspec, patches, rcParams, mplrc, P, Color, SeqIO, np, mcolors, rgb2hex, regex - - # matplotlib - try: - import matplotlib.collections as cllct - except: - command = module_install_command("matplotlib", upgrade=True) - try: - os.system(command) - print "\n" - import matplotlib.collections as cllct - except: - print "Please install module matplotlib manually" - import matplotlib.colors as mcolors - import matplotlib.gridspec as gridspec - import matplotlib.patches as patches - import pylab as P - P.switch_backend('agg') # bugfix for _tkinter.TclError on CentOs 7 servers, see Github Issue #5 - - # specify matplotlib font settings - from matplotlib import rc as mplrc - mplrc('pdf', fonttype=42, compression=0) - from matplotlib import rcParams - rcParams['font.family'] = 'sans-serif' - rcParams['font.sans-serif'] = ['Helvetica', 'Verdana', 'Tahoma' , 'DejaVu Sans', 'Droid Sans Mono', 'Sans', 'Liberation', 'Ubuntu', 'Arial', ] - - # colour for color gradient palette - try: - from colour import Color - except: - command = module_install_command("colour") - try: - os.system(command) - print "\n" - from colour import Color - except: - print "Please install module colour manually" - - # color converter - try: - from colormap import rgb2hex - except: - command = module_install_command("colormap") - # additional module easydev.tools required by colormap - command2 = module_install_command("easydev") - try: - os.system(command) - os.system(command2) - print "\n" - from colormap import rgb2hex - except: - print "Please install module colormap manually" - - # biopython - try: - from Bio import SeqIO - except: - command = module_install_command("biopython") - try: - os.system(command) - print "\n" - from Bio import SeqIO - except: - print "Please install module biopython manually" - - # numpy - try: - import numpy as np - except: - command = module_install_command("numpy") - try: - os.system(command) - print "\n" - import numpy as np - except: - print "Please install module numpy manually" - - # regex for pattern matching - try: - import regex - except: - command = module_install_command("regex") - try: - os.system(command) - print "\n" - import regex - except: - print "Please install module regex manually" - - - -############################### -# Usage & Input # -############################### - -def usage(): - """ - usage and help - """ - - print """\n\n FLEXIDOT - ------------------------------------------------------------------- - - Version: - 1.05 - - Citation: - Kathrin M. Seibt, Thomas Schmidt, Tony Heitkam (2018) - "FlexiDot: Highly customizable ambiguity-aware dotplots for visual sequence investigation" - Bioinformatics 34 (20), 3575–3577, doi: 10.1093/bioinformatics/bty395 - - - General usage: - $ python flexidot.py -a [ARGUMENTS] - $ python flexidot.py -i [ARGUMENTS] - - - ARGUMENTS - ------------------------------------------------------------------- - - - INPUT/OUTPUT OPTIONS... required are [-a] OR [-i] - - -a, --auto_fas Imports all fasta files from current directory (*.fasta, *.fas, *.fa, *.fna) - -i is not needed, if -a is activated - [inactive by default] - - -i, --in_file Input fasta file (fasta file name or comma-separated file list) - > Provide multiple files: Recall -i or provide comma-separated file names - - -o, --output_file_prefix File prefix to be added to the generated filenames [default = NONE] - - -c, --collage_output Multiple dotplots are combined in a collage - Y or 1 = ON [default] - N or 0 = OFF - - -m, --m_col Number of columns per page [default = 4] (only if --collage_output is ON) - - -n, --n_row Number of rows per page [default = 5] (only if --collage_output is ON) - - -f, --filetype Output file format - 0 = PNG [default] - 1 = PDF - 2 = SVG - - -s, --alphabetic_sorting Sort sequences alphabetically according to titles - Y or 1 = ON - N or 0 = OFF [default] - - - CALCULATION PARAMETERS... - - -k, --wordsize Wordsize (kmer length) for dotplot comparison [default = 10] - - -p, --plotting_mode Mode of FlexiDot dotplotting - 0 = self [default] - 1 = paired - 2 = poly (matrix with all-against-all dotplots) - > Run multiple plotting modes: Recall -p or provide comma-separated numbers - - -t, --type_nuc Type of residue is nucleotide - Y or 1 = nucleotide [default] - N or 0 = amino acid - - -w, --wobble_conversion Ambiguity handling for relaxed matching - Y or 1 = ON - N or 0 = OFF [default] - - -S, --substitution_count Number of substitutions (mismatches) allowed per window for relaxed matching - [default = 0] - - -r, --rc_option Find reverse complementary matches (only if type_nuc=y) - Y or 1 = ON [default] - N or 0 = OFF - - -O, --only_vs_first_seq Limit pairwise comparisons to match all sequences to 1st sequence only - (only if --plotting_mode=1) - Y or 1 = ON - N or 0 = OFF [default] - - GRAPHIC FORMATTING... - - -A, --line_width Line width [default = 1] - - -B, --line_col_for Line color [default = black] - - -C, --line_col_rev Reverse line color [default = green] - - -D, --x_label_pos Position of the X-label - Y or 1 = top [default] - N or 0 = bottom - - -E, --label_size Font size [default = 10] - - -F, --spacing Spacing between all-against-all dotplots (only if --plotting_mode=2) - [default = 0.04] - - -L, --length_scaling Scale plot size for pairwise comparison (only if --plotting_mode=1) - Y or 1 = Scaling ON (axes scaled according to sequence length) - N or 0 = Scaling OFF (squared plots) [default] - - -M, --mirror_y_axis Flip y-axis bottom to top (cartesian coordinate system) - Y or 1 = y-axis bottom to top - N or 0 = y-axis top to bottom [default] - - -P, --plot_size Plotsize [default = 10] - - -R, --representation Region of plot to display (only if --plotting_mode=2) - 0 = full [default] - 1 = upper - 2 = lower - - -T, --title_length Limit title length for dotplot comparisons - [default = 20] - Position of selection can be specified by appending a letter (e.g. -T 20E) - B = beginning [default] - E = end - - - GFF SHADING (for -p/--plotting_mode=0 only)... - - -g, --input_gff_files GFF3 file used for markup in self-dotplots - (provide multiple files: Recall -g or provide comma-separated file names) - - -G, --gff_color_config_file Tab-delimited config file for custom gff shading - column 1: feature type - column 2: color - column 3: alpha - column 4: zoom factor (for small regions) - - - LCS SHADING OPTIONS (for -p/--plotting_mode=2 only)... - - -x, --lcs_shading Shade subdotplot based on the length of the longest common substring (LCS) - Y or 1 = ON - N or 0 = OFF [default] - - -X, --lcs_shading_num Number of shading intervals (hues) for LCS (-x) and user matrix shading (-u) - [default = 5] - - -y, --lcs_shading_ref Reference for LCS shading - 0 = maximal LCS length [default] - 1 = maximally possible length (length of shorter sequence in pairwise comparison) - 2 = given interval sizes - DNA [default 100 bp] or proteins [default 10 aa] - see -Y - - -Y, --lcs_shading_interval_len Length of intervals for LCS shading (only if --lcs_shading_ref=2) - [default for nucleotides = 50; default for amino acids = 10] - - -z, --lcs_shading_ori Shade subdotplots according to LCS on - 0 = forward [default], - 1 = reverse, or - 2 = both strands (forward shading above diagonal, reverse shading on diagonal and below; - if using --input_user_matrix_file, best LCS is used below diagonal) - - - CUSTOM USER MATRIX SHADING OPTIONS (for -p/--plotting_mode=2 only)... - - -u, --input_user_matrix_file Shading above diagonal according to values in matrix file specified by the user - (tab-delimited or comma-separated matrix with sequence name in column 1 and numbers in columns 2-n - e.g. identity matrix from multiple sequence alignment - strings are ignored) - - -U, --user_matrix_print Display provided matrix entries in the fields above diagonal of all-against-all dotplot - Y or 1 = ON - N or 0 = OFF [default] - - - OTHERS... - - -h, --help Help screen - - -v, --verbose Verbose - - - - - """ - -def check_input(argv, trial_mode=False): - """ - commandline argument parsing - """ - - global log_txt, aa_bp_unit - - # helpers for argument parsing - ###################################### - - arguments = ["-a", "--auto_fas", "a", "auto_fas", - "-i", "--input_fasta", "i:", "input_fasta=", - "-o", "--output_file_prefix", "o:", "output_file_prefix=", - "-c", "--collage_output", "c:", "collage_output=", - "-m", "--m_col", "m:", "m_col=", - "-n", "--n_row", "n:", "n_row=", - "-f", "--filetype", "f:", "filetype=", - "-t", "--type_nuc", "t:", "type_nuc=", - "-g", "--input_gff_files", "g:", "input_gff_files", - "-G", "--gff_color_config_file", "G:", "gff_color_config_file", - "-k", "--wordsize", "k:", "wordsize=", - "-p", "--plotting_mode", "p:", "plotting_mode=", - "-w", "--wobble_conversion", "w:", "wobble_conversion=", - "-S", "--substitution_count", "S:", "substitution_count=", - "-r", "--rc_option", "r:", "rc_option=", - "-O", "--only_vs_first_seq", "O:", "only_vs_first_seq=", - "-s", "--alphabetic_sorting", "s:", "alphabetic_sorting=", - "-x", "--lcs_shading", "x:", "lcs_shading=", - "-X", "--lcs_shading_num", "X:", "lcs_shading_num=", - "-y", "--lcs_shading_ref", "y:", "lcs_shading_ref=", - "-Y", "--lcs_shading_interval_len", "Y:", "lcs_shading_interval_len=", - "-z", "--lcs_shading_ori", "z:", "lcs_shading_ori=", - "-u", "--input_user_matrix_file", "u:", "input_user_matrix_file=", - "-U", "--user_matrix_print", "U:", "user_matrix_print=", - "-P", "--plot_size", "P:", "plot_size=", - "-A", "--line_width", "A:", "line_width=", - "-B", "--line_col_for", "B:", "line_col_for=", - "-C", "--line_col_rev", "C:", "line_col_rev=", - "-D", "--x_label_pos", "D:", "x_label_pos=", - "-E", "--label_size", "E:", "label_size=", - "-F", "--spacing", "F:", "spacing=", - "-L", "--length_scaling", "L:", "length_scaling=", - "-M", "--mirror_y_axis", "M:", "mirror_y_axis=", - "-R", "--representation", "R:", "representation=", - "-T", "--title_length", "T:", "title_length=", - "-h", "--help", "h", "help", - "-v", "--verbose", "v", "verbose"] - - arguments_sysargv = tuple(arguments[0::4] + arguments[1::4]) - arguments_opts = "".join(arguments[2::4]) - arguments_args = arguments[3::4] - - - # setting defaults - ###################################### - - auto_fas = False # 0 - input_fasta = [] - output_file_prefix = None - collage_output = True # 1 - m_col = 4 - n_row = 5 - filetype = 0 - type_nuc = True - input_gff_files = [] - gff_color_config_file = "" - - wordsize = 10 - plotting_modes = [0] - wobble_conversion = False # 0 - substitution_count = 0 - rc_option = True # 1 - alphabetic_sorting = False # 0 - only_vs_first_seq = False # 0 - - lcs_shading = False # 0 - lcs_shading_num = 4 - lcs_shading_ref = 0 - lcs_shading_interval_len = 50 # interval default changes to "10" for amino acids [type_nuc = n] - lcs_shading_ori = 0 - - input_user_matrix_file = "" - user_matrix_print = False - - plot_size = 10 - line_width = 1 - line_col_for = "black" - line_col_rev = "#009243" - x_label_pos = True # 0 - label_size = 10 - spacing = 0.04 - length_scaling = False # 0 - title_length = 20 # float("Inf") - title_clip_pos = "B" # B (begin), E (end) - max_N_percentage = 49 # fixed value, no user input - mirror_y_axis = False - representation = 0 - - aa_bp_unit = "bp" - - verbose = False # 0 - - filetype_dict = {0: "png", 1: "pdf", 2: "svg"} - lcs_shading_ref_dict = {0: "maximal LCS length", 1: "maximally possible length", 2: "given interval sizes"} - plotting_mode_dict = {0: "self", 1: "paired", 2: "all-against-all"} - lcs_shading_ori_dict = {0: "forward", 1: "reverse complement", 2: "both"} - representation_dict = {0: "full", 1: "upper", 2: "lower"} - - # return default parameters for testing purposes - if trial_mode: - print "ATTENTION: YOU ARE IN THE TRIAL MODE!!!\n\n" - - commandline = "trial_mode\n" - - parameters = [commandline, auto_fas, input_fasta, output_file_prefix, collage_output, m_col, n_row, filetype_dict[filetype], type_nuc, input_gff_files, gff_color_config_file, wordsize, plotting_modes, wobble_conversion, substitution_count, rc_option, alphabetic_sorting, only_vs_first_seq, lcs_shading, lcs_shading_num, lcs_shading_ref, lcs_shading_interval_len, lcs_shading_ori, input_user_matrix_file, user_matrix_print, plot_size, line_width, line_col_for, line_col_rev, x_label_pos, label_size, spacing, length_scaling, title_length, title_clip_pos, max_N_percentage, mirror_y_axis, representation, verbose] - return parameters - - - # read arguments - ###################################### - - commandline = "" - for arg in sys.argv: - commandline += arg + " " - - log_txt = "\n...reading input arguments..." - print log_txt - - if len(sys.argv) < 2: - print "\nERROR: More arguments are needed. Exit..." - log_txt += "\nERROR: More arguments are needed. Exit..." - usage() - sys.exit() - - elif sys.argv[1] not in arguments_sysargv: - print "\nINPUT ERROR: Input argument %s unknown. Please check the help screen." % sys.argv[1] - log_txt += "\nINPUT ERROR: Input argument %s unknown. Please check the help screen." % sys.argv[1] - # usage() - sys.exit() - - try: - opts, args = getopt.getopt(sys.argv[1:], arguments_opts, arguments_args) - - except getopt.GetoptError: - print "\nINPUT ERROR (getopt): Input argument %s unknown. Please check the help screen." % sys.argv[1:] - log_txt += "\nINPUT ERROR (getopt): Input argument %s unknown. Please check the help screen." % sys.argv[1:] - # usage() - sys.exit() - - for opt, arg in opts: - - if opt in ("-h", "--help"): - print "...fetch help screen" - log_txt += "\n...fetch help screen" - usage(), sys.exit() - - if opt in ("-v", "--verbose"): - print "...verbose output" - log_txt += "\n...verbose output" - verbose = True - - elif opt in ("-i", "--input_fasta"): - if "," in arg: - arg_list = arg.split(",") - for temp_file in arg_list: - if not os.path.exists(str(temp_file)): - message = "\nERROR: fasta_file '%s' was not found!" % str(temp_file) - sys.exit(message) - else: - input_fasta.append(str(temp_file)) - print "fasta file #%i: %s" % (len(input_fasta), str(temp_file)) - log_txt += "\nfasta file #%i: %s" % (len(input_fasta), str(temp_file)) - else: - if not os.path.exists(str(arg)): - message = "\nERROR: fasta_file '%s' was not found!" % str(arg) - log_txt += message - sys.exit(message) - else: - input_fasta.append(str(arg)) - print "fasta file #%i: %s" % (len(input_fasta), str(arg)) - log_txt += "\nfasta file #%i: %s" % (len(input_fasta), str(arg)) - - - elif opt in ("-a", "--auto_fas"): - auto_fas = True - - - # multiple gff files: reads them into a list - elif opt in ("-g", "--input_gff_files"): - - # append gff file only if existing - if "," in arg: - arg_list = arg.split(",") - for temp_file in arg_list: - if not os.path.exists(str(temp_file)): - message = "\nERROR: gff_file '%s' was not found!" % str(temp_file) - print message - log_txt += message - print " -->Running FlexiDot without this gff file!" - log_txt += "\n -->Running FlexiDot without this gff file!" - else: - print "GFF file #%i: %s" %(len(input_gff_files), str(temp_file)) - log_txt += "\nGFF file #%i: %s" %(len(input_gff_files), str(temp_file)) - input_gff_files.append(str(temp_file)) - else: - if not os.path.exists(str(arg)): - message = "\nERROR: gff_file '%s' was not found!" % str(arg) - print message - log_txt += message - print " -->Running FlexiDot without this gff file!" - log_txt += "\n -->Running FlexiDot without this gff file!" - else: - input_gff_files.append(str(arg)) - print "GFF file #%i: %s" %(len(input_gff_files), str(arg)) - log_txt += "\nGFF file #%i: %s" %(len(input_gff_files), str(arg)) - - - elif opt in ("-G", "--gff_color_config_file"): - if not os.path.exists(str(arg)): - message = "\nERROR: gff_color_config_file '%s' was not found!" % str(arg) - print message + "\n -->Running FlexiDot with default gff coloring specification!" - log_txt += message + "\n -->Running FlexiDot with default gff coloring specification!" - else: - gff_color_config_file = str(arg) - - - elif opt in ("-u", "--input_user_matrix_file"): - if not os.path.exists(str(arg)): - message = "\nERROR: input_user_matrix_file '%s' was not found!" % str(arg) - print message + "\n -->Running FlexiDot without input_user_matrix_file %s!" % arg - log_txt += message + "\n -->Running FlexiDot withdefault matrix shading file!" - else: - input_user_matrix_file = str(arg) - - elif opt in ("-U", "--user_matrix_print"): - user_matrix_print = check_bools(str(arg), default=user_matrix_print) - - elif opt in ("-o", "--output_file_prefix"): - output_file_prefix = arg - - elif opt in ("-c", "--collage_output"): - collage_output = check_bools(str(arg), default=collage_output) - - elif opt in ("-m", "--m_col"): - try: m_col = int(arg) - except: - print "m_col - invalid argument - using default value" - log_txt += "\nm_col - invalid argument - using default value" - - elif opt in ("-n", "--n_row"): - try: n_row = int(arg) - except: - print "n_row - invalid argument - using default value" - log_txt += "\nn_row - invalid argument - using default value" - - elif opt in ("-f", "--filetype"): - if 0 <= int(arg) <= 2: - filetype = int(arg) - else: - print "\nERROR: Please provide valid filetype argument. %s is out of range. It will be set to -f 0 [default]." %(filetype) - log_txt += "\nERROR: Please provide valid filetype argument. %s is out of range. It will be set to -f 0 [default]." %(filetype) - - elif opt in ("-t", "--type_nuc"): - type_nuc = check_bools(str(arg), default=type_nuc) - - if type_nuc == False: - # interval default changed for amino acids - lcs_shading_interval_len = 10 - aa_bp_unit = "aa" - - elif opt in ("-k", "--wordsize"): - try: wordsize = int(arg) - except: - print "wordsize - invalid argument - using default value" - log_txt += "\nwordsize - invalid argument - using default value" - - elif opt in ("-p", "--plotting_mode"): - if "," in arg: - temp_modes = arg.split(",") - for item in temp_modes: - if item in ["0","1","2"]: - plotting_modes.append(int(item)) - elif arg in ["0","1","2"]: - plotting_modes = [int(arg)] - else: - print "Please provide valid plotting_modes argument - e.g. 1 or 0,1,2 - using default [0]" - log_txt += "\nPlease provide valid plotting_modes argument - e.g. 1 or 0,1,2 - using default [0]" - - elif opt in ("-w", "--wobble_conversion"): - wobble_conversion = check_bools(str(arg), default=wobble_conversion) - - elif opt in ("-S", "--substitution_count"): - try: substitution_count = int(arg) - except: - print "substitution_count - invalid argument - using default value" - log_txt += "\nsubstitution_count - invalid argument - using default value" - - elif opt in ("-r", "--rc_option"): - rc_option = check_bools(str(arg), default=rc_option) - - elif opt in ("-s", "--alphabetic_sorting"): - alphabetic_sorting = check_bools(str(arg), default=alphabetic_sorting) - - elif opt in ("-O", "--only_vs_first_seq"): - only_vs_first_seq = check_bools(str(arg), default=only_vs_first_seq) - - elif opt in ("-x", "--lcs_shading"): - lcs_shading = check_bools(str(arg), default=lcs_shading) - - elif opt in ("-X", "--lcs_shading_num"): - try: lcs_shading_num = int(arg) - 1 - except: - print "lcs_shading_num - invalid argument - using default value" - log_txt += "\nlcs_shading_num - invalid argument - using default value" - - elif opt in ("-y", "--lcs_shading_ref"): - try: - if 0 <= int(arg) <= 2: - lcs_shading_ref = int(arg) - else: - print "\nERROR: lcs_shading_ref %s out of range. It will be set to -y 0 [default]." %(lcs_shading_ref) - log_txt += "\nERROR: lcs_shading_ref %s out of range. It will be set to -y 0 [default]." %(lcs_shading_ref) - except: - print "lcs_shading_ref - invalid argument - using default value" - log_txt += "\nlcs_shading_ref - invalid argument - using default value" - - elif opt in ("-Y", "--lcs_shading_interval_len"): - try: lcs_shading_interval_len = int(arg) - except: - print "lcs_shading_interval_len - invalid argument - using default value" - log_txt += "\nlcs_shading_interval_len - invalid argument - using default value" - - elif opt in ("-z", "--lcs_shading_ori"): - if 0 <= int(arg) <= 2: - lcs_shading_ori = int(arg) - else: - print "\nERROR: Please provide valid lcs_shading_ori argument. %s is out of range. It will be set to -z 0 [default]." %(lcs_shading_ori) - log_txt += "\nERROR: Please provide valid lcs_shading_ori argument. %s is out of range. It will be set to -z 0 [default]." %(lcs_shading_ori) - - elif opt in ("-P", "--plot_size"): - try: plot_size = float(arg) - except: - print "plot_size - invalid argument - using default value" - log_txt += "\nplot_size - invalid argument - using default value" - - - elif opt in ("-A", "--line_width"): - try: line_width = float(arg) - except: - print "line_width - invalid argument - using default value" - log_txt += "\nline_width - invalid argument - using default value" - - elif opt in ("-B", "--line_col_for"): - if mcolors.is_color_like(arg): - line_col_for = arg - else: - print "line_col_for - invalid argument - using default value" - log_txt += "\nline_col_for - invalid argument - using default value" - - elif opt in ("-C", "--line_col_rev"): - if mcolors.is_color_like(arg): - line_col_rev = arg - else: - print "line_col_rev - invalid argument - using default value" - log_txt += "\nline_col_rev - invalid argument - using default value" - - elif opt in ("-D", "--x_label_pos"): - x_label_pos = check_bools(str(arg), default=x_label_pos) - - elif opt in ("-E", "--label_size"): - try: label_size = float(arg) - except: - print "label_size - invalid argument - using default value" - log_txt += "\nlabel_size - invalid argument - using default value" - - elif opt in ("-F", "--spacing"): - try: spacing = float(arg) - except: - print "spacing - invalid argument - using default value" - log_txt += "\nspacing - invalid argument - using default value" - - elif opt in ("-L", "--length_scaling"): - length_scaling = check_bools(str(arg), default=length_scaling) - - elif opt in ("-M", "--mirror_y_axis"): - mirror_y_axis = check_bools(str(arg), default=mirror_y_axis) - - elif opt in ("-R", "--representation"): - if 0 <= int(arg) <= 2: - representation = int(arg) - else: - print "\nERROR: Please provide valid representation argument. %s is out of range. It will be set to -R 0 [default]." %(representation) - log_txt += "\nERROR: Please provide valid representation argument. %s is out of range. It will be set to -R 0 [default]." %(representation) - - elif opt in ("-T", "--title_length"): - try: title_length = int(arg) - except: - try: - title_length = int(str(arg)[:-1]) - if arg[-1].upper() in ["B", "E"]: # B (beginning), E (end) - title_clip_pos = arg[-1].upper() - else: - print "title_length position information invalid - using default value" - log_txt += "\ntitle_length position information invalid - using default value" - except: - print "title_length - invalid argument - using default value" - log_txt += "\ntitle_length - invalid argument - using default value" - - # start logging file - logprint(commandline, start=True, printing=False, prefix=output_file_prefix) - logprint(log_txt, start=False, printing=False) - - - # print chosen arguments - ###################################### - - text = "\n%s\n" % (70 * "-") - text += "\n" + "INPUT/OUTPUT OPTIONS...\n" - text += "\n" + "Input fasta file: " + ", ".join(input_fasta) - text += "\n" + "Automatic fasta collection from current directory: " + str(auto_fas) - text += "\n" + "Collage output: " + str(collage_output) - text += "\n" + "Number of columns per page: " + str(m_col) - text += "\n" + "Number of rows per page: " + str(n_row) - text += "\n" + "File format: " + filetype_dict[filetype] - text += "\n" + "Residue type is nucleotide: " + str(type_nuc) - - text += "\n" + "\n\nCALCULATION PARAMETERS...\n" - text += "\n" + "Wordsize: " + str(wordsize) - text += "\n" + "Sustitution count: " + str(substitution_count) - text += "\n" + "Plotting mode: " + str(plotting_modes).replace("[", "").replace("]", "") + "\n" + 51 * " " - for item in plotting_modes: - text += plotting_mode_dict[item] + " " - text += "\n" + "Ambiguity handling: " + str(wobble_conversion) - text += "\n" + "Reverse complement scanning: " + str(rc_option) - text += "\n" + "Alphabetic sorting: " + str(alphabetic_sorting) - - if 1 in plotting_modes: - text += "\n" + "Only matching sequences to first entry: " + str(only_vs_first_seq) - - if 0 in plotting_modes and input_gff_files != []: - text += "\n" + "Input gff files: " + ", ".join(input_gff_files) - if gff_color_config_file != "": - text += "\n" + "GFF color config file: " + gff_color_config_file - text += "\n" + "Prefix for output files: " + str(output_file_prefix) - - if 2 in plotting_modes: - text += "\n" + "\n\nLCS SHADING OPTIONS (plotting_mode 'all-against-all' only)...\n" - text += "\n" + "LCS shading: " + str(lcs_shading) - text += "\n" + "LCS shading interval number: " + str(lcs_shading_num + 1) - text += "\n" + "LCS shading reference: " + lcs_shading_ref_dict[lcs_shading_ref] - if lcs_shading_ref == 2: - text += "\n" + "LCS shading interval size [%s]: " % (aa_bp_unit) + str(lcs_shading_interval_len) - text += "\n" + "LCS shading orientation: " + lcs_shading_ori_dict[lcs_shading_ori] - if input_user_matrix_file != "": - text += "\n" + "Custom user shading matrix file: " + input_user_matrix_file - text += "\n" + "Print user matrix values (instead of dotplot): " + str(user_matrix_print) - text += "\n" + "Displayed plot region: " + representation_dict[representation] - - text += "\n" + "\n\nGRAPHIC FORMATTING...\n" - text += "\n" + "Plot size: " + str(plot_size) - text += "\n" + "Line width: " + str(line_width) - text += "\n" + "Line color: " + line_col_for - text += "\n" + "Reverse line color: " + line_col_rev - text += "\n" + "X label position: " + str(x_label_pos) - text += "\n" + "Label size: " + str(label_size) - text += "\n" + "Spacing: " + str(spacing) - if mirror_y_axis: - text += "\n" + "Y-axis mirrored (bottom to top) " + str(mirror_y_axis) - if title_clip_pos == "E": - text += "\n" + "Title length (limit number of characters): " + "last" + str(title_length) + "characters" - else: - text += "\n" + "Title length (limit number of characters): " + "first" + str(title_length) + "characters" - text += "\n" + "Length scaling: " + str(length_scaling) - text += "\n%s\n" % (70 * "-") - logprint(text) - - - # collect settings - parameters = [commandline, auto_fas, input_fasta, output_file_prefix, collage_output, m_col, n_row, filetype_dict[filetype], type_nuc, input_gff_files, gff_color_config_file, wordsize, plotting_modes, wobble_conversion, substitution_count, rc_option, alphabetic_sorting, only_vs_first_seq, lcs_shading, lcs_shading_num, lcs_shading_ref, lcs_shading_interval_len, lcs_shading_ori, input_user_matrix_file, user_matrix_print, plot_size, line_width, line_col_for, line_col_rev, x_label_pos, label_size, spacing, length_scaling, title_length, title_clip_pos, max_N_percentage, mirror_y_axis, representation, verbose] - - return parameters - - -############################### -# Helper Functions # -############################### - -def alphabets(type_nuc=True): - """ - provide ambiguity code for sequences - """ - - nucleotide_alphabet = ["A", "C", "G", "T"] - - nucleotide_alphabet_full = ["A", "C", "G", "T", "N", "B", "D", "H", - "V", "Y", "R", "W", "S", "K", "M"] - - nucleotide_ambiguity_code = {"N": ["A", "C", "G", "T"], # any - "B": ["C", "G", "T"], # not A - "D": ["A", "G", "T"], # not C - "H": ["A", "C", "T"], # not G - "V": ["A", "C", "G"], # not T - "Y": ["C", "T"], # pyrimidine - "R": ["A", "G"], # purine - "W": ["A", "T"], # weak - "S": ["C", "G"], # strong - "K": ["G", "T"], # keto - "M": ["A", "C"]} # amino - - nucleotide_match_dict = {"N": "[ACGTNBDHVYRWSKM]", # any - "B": "[CGTNBDHVYRWSKM]", # not A - "D": "[AGTNBDHVYRWSKM]", # not C - "H": "[ACTNBDHVYRWSKM]", # not G - "V": "[ACGNBDHVYRWSKM]", # not T - "K": "[GTNBDHVYRWSK]", # keto - not A,C,M - "M": "[ACNBDHVYRWSM]", # amino - not G,T,K - "W": "[ATNBDHVYRWKM]", # weak - not C,G,S - "S": "[CGNBDHVYRSKM]", # strong - not A,G,W - "Y": "[CTNBDHVYWSKM]", # pyrimidine - not A,G,R - "R": "[AGNBDHVRWSKM]", # purine - not C,T,Y - "A": "[ANDHVRWM]", - "C": "[CNBHVYSM]", - "G": "[GNBDVRSK]", - "T": "[TNBDHYWK]"} - - # nucleotide_match_dict = {"N": ".", # any - # "B": "[^A]", # not A - # "D": "[^C]", # not C - # "H": "[^G]", # not G - # "V": "[^T]", # not T - # "K": "[^ACM]", # keto - not A,C,M - # "M": "[^GTK]", # amino - not G,T,K - # "W": "[^CGS]", # weak - not C,G,S - # "S": "[^AGW]", # strong - not A,G,W - # "Y": "[^AGR]", # pyrimidine - not A,G,R - # "R": "[^CTY]", # purine - not C,T,Y - # "A": "[ANDHVRWM]", - # "C": "[CNBHVYSM]", - # "G": "[GNBDVRSK]", - # "T": "[TNBDHYWK]"} - - aminoacid_alphabet = ["A", "R", "N", "D", "C", "E", "Q", "G", - "H", "I", "L", "K", "M", "F", "P", "S", - "T", "W", "Y", "V", "U", "O", "*"] - - aminoacid_alphabet_full = ["A", "R", "N", "D", "C", "E", "Q", "G", - "H", "I", "L", "K", "M", "F", "P", "S", - "T", "W", "Y", "V", "U", "O", "*", "J", - "Z", "B", "X"] - - aminoacid_ambiguity_code = {"J": ["I", "L"], - "Z": ["Q", "E"], - "B": ["N", "D"], - "X": ["A", "R", "N", "D", "C", "E", "Q", "G", - "H", "I", "L", "K", "M", "F", "P", "S", - "T", "W", "Y", "V", "U", "O", "*"]} # any - - aminoacid_match_dict = {"J": "[ILJ]", - "Z": "[QEZ]", - "B": "[NDB]", - # "X": ".", - "X": "[ARNDCEQGHILKMFPSTWYVUO*XBZJ]", - "A": "[AX]", - "R": "[RX]", - "N": "[NXB]", - "D": "[DXB]", - "C": "[CX]", - "E": "[EXZ]", - "Q": "[QXZ]", - "G": "[GX]", - "H": "[HX]", - "I": "[IXJ]", - "L": "[LXJ]", - "K": "[KX]", - "M": "[MX]", - "F": "[FX]", - "P": "[PX]", - "S": "[SX]", - "T": "[TX]", - "W": "[WX]", - "Y": "[YX]", - "V": "[VX]", - "U": "[UX]", - "O": "[OX]", - "*": "[*X]"} - - aa_only = set(['E', 'F', 'I', 'J', 'L', 'O', 'Q', 'P', 'U', 'X', 'Z', '*']) - # return nucleotide_alphabet, nucleotide_alphabet_full, nucleotide_ambiguity_code, aminoacid_alphabet, aminoacid_alphabet_full, aminoacid_ambiguity_code, aa_only - - if type_nuc: - return nucleotide_alphabet, nucleotide_alphabet_full, nucleotide_ambiguity_code, nucleotide_match_dict - else: - return aminoacid_alphabet, aminoacid_alphabet_full, aminoacid_ambiguity_code, aminoacid_match_dict - -def logprint(text, start=False, printing=True, prefix=""): - """ - log output to log_file and optionally print - """ - - # define log file name and open file - global log_file_name - if start and trial_mode: - log_file_name = "log_file.txt" - if prefix != "" and prefix != None: - if not prefix.endswith("-"): - prefix = prefix + "-" - log_file_name = prefix + log_file_name - log_file = open(log_file_name, 'w') - log_file.write("Date: %s\n\n" % str(datetime.datetime.now())) - elif start: - date = datetime.date.today() - time = str(datetime.datetime.now()).split(" ")[1].split(".")[0].replace(":", "-") - log_file_name = "%s_%s_log_file.txt" % (date, time) - if prefix != "" and prefix != None: - if not prefix.endswith("-"): - prefix = prefix + "-" - log_file_name = prefix + log_file_name - log_file = open(log_file_name, 'w') - log_file.write("Date: %s\n\n" % str(datetime.datetime.now())) - else: - log_file = open(log_file_name, 'a') - - # write log (and print) - log_file.write(text + "\n") - if printing: - print text - log_file.close() - -def time_track(starting_time, show=True): - """ - calculate time passed since last time measurement - """ - now = time.time() - delta = now - starting_time - if show: - text = "\n\t %s seconds\n" % str(delta) - logprint(text, start=False, printing=True) - return now - -def calc_fig_ratio(ncols, nrows, plot_size, verbose=False): - """ - calculate size ratio for given number of columns (ncols) and rows (nrows) - with plot_size as maximum width and length - """ - ratio = ncols*1./nrows - if verbose: - text = " ".join([ncols, nrows, ratio]) - logprint(text, start=False, printing=True) - if ncols >= nrows: - figsize_x = plot_size - figsize_y = plot_size / ratio - else: - figsize_x = plot_size * ratio - figsize_y = plot_size - return figsize_x, figsize_y - -def shorten_name(seq_name, max_len=20, title_clip_pos="B"): #, delim="_"): - """ - shorten sequence names (for diagram titles) - """ - - if len(seq_name) <= max_len: - return seq_name - - # take last characters - if title_clip_pos == "E": - name = seq_name[len(seq_name)-max_len:] - - # take first characters - else: - name = seq_name[:max_len] - - """# keep first and last part if multiple parts separated by delimiter (e.g. species_prefix + sequence_id) - if delim in seq_name: - if seq_name.count(delim) >= 2: - name = "%s..." % delim.join(seq_name.split(delim)[:1]) + seq_name.split(delim)[-1] # .replace("_000", "-") - else: - name = seq_name[:((max_len-2)//2)] + "..." + seq_name[((max_len-2)//2):] - - if len(name) > max_len: - name = name[:((max_len-2)//2)] + "..." + name[((max_len-2)//2):] - else: - name = seq_name[:((max_len-2)//2)] + "..." + seq_name[((max_len-2)//2):] - """ - - return name - -def unicode_name(name): - """ - replace non-ascii characters in string (e.g. for use in matplotlib) - """ - unicode_string = eval('u"%s"' % name) - return unicodedata.normalize('NFKD', unicode_string).encode('ascii','ignore') - -def check_bools(arg, update_log_txt = True, default=None): - """ - converts commandline arguments into boolean - """ - - - # convert valid arguments - if str(arg).lower() == "y" or str(arg) == "1": - return True - elif str(arg).lower() == "n" or str(arg) == "0": - return False - - # use default in case of invalid argument - else: - if update_log_txt: - global log_txt - log_txt += "using default for " + str(arg) - else: - try: - logprint("using default for " + str(arg)) - except: - print "using default for " + str(arg) - return default - -def create_color_list(number, color_map=None, logging=False, max_grey="#595959"): - """ - create color list with given number of entries - grey by default, matplotlib color_map can be provided - """ - - try: - # create pylab colormap - cmap = eval("P.cm." + color_map) - # get descrete color list from pylab - cmaplist = [cmap(i) for i in range(cmap.N)] # extract colors from map - # determine positions for number of colors required - steps = (len(cmaplist)-1)/(number) - numbers = range(0, len(cmaplist), steps) - - # extract color and convert to hex code - colors = [] - for idx in numbers[:-1]: - rgb_color = cmaplist[idx] - col = rgb2hex(rgb_color[0]*255, rgb_color[1]*255, rgb_color[2]*255) - colors.append(col) - - # grey - except: - if not color_map == None: - logprint("Invalid color_map (%s) provided! - Examples: jet, Blues, OrRd, bwr,..." % color_map) - logprint("See https://matplotlib.org/users/colormaps.html\n") - old_max_grey = "#373737" - old_max_grey = "#444444" - colors = list(Color("#FFFFFF").range_to(Color(max_grey), number)) # grey - for idx in range(len(colors)): - colors[idx] = str(colors[idx]).replace("Color ", "") - if "#" in colors[idx] and len(colors[idx]) != 7: - # print colors[idx] - colors[idx] = colors[idx] + colors[idx][-(7-len(colors[idx])):] - - text = "%d Colors: %s" % (len(colors), ", ".join(colors)) - if logging: logprint(text, start=False, printing=True) - - if len(colors) < number: - logprint("\nError in color range definition! %d colors missing\n" % (number - len(colors))) - - return colors - - -############################### -# File Handling # -############################### - -def read_seq(input_fasta, verbose=False): - """ - read fasta sequences from (all) file(s) - """ - - # check if file provided - if input_fasta == [] or input_fasta == "": - text = "Attention: No valid file names provided: >%s<" % input_fasta - logprint(text, start=False, printing=True) - return {}, [] - - # combine sequence files, if required - if type(input_fasta) == list: - # concatenate fasta files - if len(input_fasta) > 1: - if verbose: - print "concatenating fastas...", - text = "concatenating fastas..." - input_fasta_combi = concatenate_files(input_fasta) - if verbose: - print "done" - text += "done" - logprint(text, start=False, printing=False) - else: - input_fasta_combi = input_fasta[0] - else: - input_fasta_combi = input_fasta - - # read sequences - if verbose: - print "reading fasta...", - text = "reading fasta...", - try: - seq_dict = SeqIO.index(input_fasta_combi, "fasta") - except ValueError: - logprint("Error reading fasta sequences - please check input files, e.g. for duplicate names!") - return {}, [] - except: - logprint("Error reading fasta sequences - please check input files!") - return {}, [] - - if verbose: - print "done" - text += "done" - logprint(text, start=False, printing=False) - - for seq in seq_dict: - if "-" in seq_dict[seq].seq: - # ungapped = seq_dict[seq].seq.ungap("-") # cannot be assigned back to sequence record - text = "\nSequences degapped prior Analysis!!!" - logprint(text, start=False, printing=True) - return read_seq(degap_fasta(input_fasta), verbose=verbose) - - # get ordered sequence names - sequences = [] - for item in SeqIO.parse(input_fasta_combi, "fasta"): - sequences.append(item.id) - return seq_dict, sequences - -def read_gff_color_config(gff_color_config_file=""): - """ - define coloring options for gff-based color shading of self-dotplots - """ - - # default aestetics for annotation shading (e.g. if no user config file is provided) - # dictionary with feature_type as key and tuple(color, transparency, zoom) as value - gff_feat_colors = {"orf": ("#b41a31", 0.2, 0), - "orf_rev": ("#ff773b", 0.3, 0), - "gene": ("#b41a31", 0.2, 0), - "cds": ("darkorange", 0.2, 0), - "exon": ("orange", 0.2, 0), - "intron": ("lightgrey", 0.2, 0), - "utr": ("lightblue", 0.2, 0), - "repeat_region": ("green", 0.3, 0), - "repeat": ("green", 0.3, 0), - "tandem_repeat": ("red", 0.3, 0), - "transposable_element": ("blue", 0.3, 0), - "ltr_retrotransposon": ("#cccccc", 0.5, 0), - "ltr-retro": ("#cccccc", 0.5, 0), - "long_terminal_repeat": ("#2dd0f0", 0.75, 2), - "ltr": ("#2dd0f0", 0.75, 2), - "pbs": ("purple", 0.75, 2), - "ppt": ("#17805a", 0.5, 2), - "target_site_duplication": ("red", 0.75, 2), - "misc_feature": ("grey", 0.3, 0), - "misc_feat": ("grey", 0.3, 0), - "misc": ("grey", 0.3, 0), - "others": ("grey", 0.5, 0)} - if gff_color_config_file in ["", None] or not os.path.exists(str(gff_color_config_file)): - return gff_feat_colors - - text = "Updating GFF color configuration with custom specifications\n" - logprint(text, start=False, printing=True) - - # read custom gff_color_config_file - in_file = open(gff_color_config_file, 'rb') - overwritten = set([]) - for line in in_file: - if not line.startswith("#") and len(line.strip().split("\t")) >= 4: - data = line.strip().split("\t") - feat = data[0].lower() - color = data[1].lower() - - # check, if settings are valid - if not mcolors.is_color_like(color): - color = "grey" - text = "Invalid color specified for %s: %s - default grey" % (data[0], data[1]) - logprint(text) - try: - alpha = float(data[2]) - except: - alpha = 0.75 - text = "Invalid alpha specified for %s: %s - default 0.75" % (data[0], data[2]) - logprint(text) - try: - zoom = float(data[3]) - except: - zoom = 0 - text = "Invalid zoom specified for %s: %s - default 0" % (data[0], data[3]) - logprint(text) - - # track changes of predefined settings - if feat in gff_feat_colors.keys(): - overwritten.add(data[0].lower()) - - gff_feat_colors[feat] = (color, alpha, zoom) - in_file.close() - - # default coloring for unknown annotations - if not "others" in gff_feat_colors.keys(): - gff_feat_colors["others"] = ("grey", 0.5, 0) - - if verbose: - # print configuration - text = "\n\nGFF color specification:\n%s\n" % (60 * ".") - for item in sorted(gff_feat_colors.keys()): - text += "%-30s\t%-10s\t%-5s\t%s\n" % (item, str(gff_feat_colors[item][0]), str(gff_feat_colors[item][1]), str(gff_feat_colors[item][2])) - logprint (text, printing=True) - - # print overwritting feature type specifications - if len(overwritten) != 0: - text = "%d feature type specifications overwritten:" % len(overwritten) - text += "\n\t"+ ", ".join(overwritten) + "\n" - logprint(text, start=False, printing=True) - - text = "GFF color specification updated acc. to %s\n\t%s\n\n" % (gff_color_config_file, ", ".join(gff_feat_colors)) - logprint(text, start=False, printing=True) - - return gff_feat_colors - -def read_gffs(input_gff_files, color_dict={"others": ("grey", 1, 0)}, type_nuc=True, prefix="", filetype='png', verbose=False): - """ - create feature dictionary from input_gff - sequence name as key and (feature type, start, stop) as value - """ - if type(input_gff_files) != list: - input_gff_files = [input_gff_files] - - # create dictionary with seq_name as key and (type, start and stop) as value - unknown_feats = set([]) - used_feats = set([]) - feat_dict = {} - for input_gff in input_gff_files: - text = "...reading " + input_gff - logprint(text, start=False, printing=True) - - in_file = open(input_gff, 'rb') - for line in in_file: - if not line.startswith("#") and line.strip() != "": - data = line.strip().split("\t") - feat_type = data[2].lower() - if data[6] == "-": - feat_type += "_rev" - if not feat_type.lower() in color_dict.keys(): - if feat_type.lower().replace("_rev", "") in color_dict.keys(): - feat_type = feat_type.replace("_rev", "") - else: - unknown_feats.add(feat_type) - feat_type = "others" - used_feats.add(feat_type) - if not data[0] in feat_dict.keys(): - feat_dict[data[0]] = [(feat_type, int(data[3]), int(data[4]))] # feature type, start, stop - else: - feat_dict[data[0]].append((feat_type, int(data[3]), int(data[4]))) # feature type, start, stop - if verbose: - text = "\nAnnotations for: %s\n" % ", ".join(feat_dict.keys()[:10]) - if len(feat_dict.keys()) > 10: - text = text[:-1] + ", ...\n" - logprint(text, start=False, printing=True) - in_file.close() - - # print feature types without specific shading settings - if len(unknown_feats) != 0: - text = "Missing shading specification for %d feature type(s):\n\t%s\n" % (len(unknown_feats), ", ".join(sorted(unknown_feats))) - logprint(text, start=False, printing=True) - - # create color legend - colors, alphas = [], [] - for item in sorted(used_feats): - colors.append(color_dict[item][0]) - alphas.append(color_dict[item][1]) - legend_figure(colors=colors, lcs_shading_num=len(used_feats), type_nuc=type_nuc, bins=sorted(used_feats), alphas=alphas, gff_legend=True, prefix=prefix, filetype=filetype) - - # print settings - text = "GFF Feature Types: %s\nGFF Colors: %s" % (", ".join(sorted(used_feats)), ", ".join(sorted(colors))) - logprint(text, start=False, printing=True) - - return feat_dict - -def read_matrix(matrix_file_name, delim="\t", symmetric=True, recursion=False, verbose=False): - input_file = open(matrix_file_name, 'rb') - - # read sequence names from first column - names = [] - for line in input_file: - if not line.startswith("#") and not line.startswith(delim) and delim in line: - names.append(line.strip().split(delim)[0]) - logprint("Delimiter '%s': %d names - %s\n" % (delim, len(names), ", ".join(names))) - - # check if names were found - otherwise try another delimiter - if names == [] and not recursion: - if delim == "\t": - new_delim = "," - else: - new_delim = "\t" - logprint("\nMatrix file not containing data delimited by '%s' - trying to read matrix with delimiter '%s'" % (delim.replace("\t", "\\t"), new_delim)) - info_dict = read_matrix(matrix_file_name, delim=new_delim, symmetric=symmetric, recursion=True, verbose=verbose) - return info_dict - elif names == []: - logprint("Empty matrix file with alternative delimiter!") - return info_dict - input_file.close() - - input_file = open(matrix_file_name, 'rb') - # read matrix entries as values in dictionary with tuple(names) as key - info_dict = {} - contradictory_entries = [] - for line in input_file: - if not line.startswith("#") and not line.startswith(delim) and delim in line: - data = line.strip().split(delim) - for idx in range(len(data[1:])): - # print tuple(sorted([data[0], names[idx]])), data[idx+1] - if symmetric: - key = tuple(sorted([names[idx], data[0]])) - else: - key = tuple(names[idx], data[0]) - if key in info_dict.keys(): - if symmetric and info_dict[key] != data[idx+1] and data[idx+1] not in ["", "-"] and info_dict[key] not in ["", "-"]: - contradictory_entries.append(key) - info_dict[key] = data[idx+1] - input_file.close() - - if len(contradictory_entries) != 0: - try: - logprint("\nContradictory entries in matrix file %s:\n\t%s" % (matrix_file_name, ", ".join(contradictory_entries))) - except: - log_txt = "\nContradictory entries in matrix file %s:\n\t" % (matrix_file_name) - for item in contradictory_entries: - log_txt += str(item).replace("'", "") + ", " - log_txt = log_txt[:-2] - logprint(log_txt) - logprint("Using value from bottom left triangle!") - if verbose: - logprint("\nMatrix information for Sequences named: " % ", ".join(names)) - - return info_dict - -def concatenate_files(file_list, combi_filename="temp_combined.fasta", verbose=False): - """ - concatenate content of all files in file_list into a combined file named combi_filename - """ - out_file = open(combi_filename, 'w') - text = "" - for item in file_list: - if verbose: - text += item + " " - print item, - # read in_file linewise and write to out_file - in_file = open(item, 'rb') - for line in in_file: - out_file.write(line.strip()+"\n") - in_file.close() - out_file.close() - if verbose: - logprint(text, start=False, printing=False) - return combi_filename - -def degap_fasta(input_fasta): - """ - remove gaps from fasta - new degapped sequence file created - """ - - # degap all sequence files - output_fastas = [] - if type(input_fasta) != list: - input_fasta = list(input_fasta) - for input_fas in input_fasta: - output_fas = input_fas[:input_fas.rfind(".")] + "_degapped.fas" - in_file = open(input_fas, 'rb') - out_file = open(output_fas, 'w') - for line in in_file: - if line.startswith(">"): - out_file.write(line.strip()+"\n") - else: - out_file.write(line.strip().replace("-", "")+"\n") - out_file.close() - in_file.close() - output_fastas.append(output_fas) - return output_fastas - -def legend_figure(colors, lcs_shading_num, type_nuc=True, unit="%", filetype="png", max_len=None, min_len=0, bins=[], alphas=[], gff_legend=False, prefix="", verbose=False): - """ - create figure color legend - """ - max_legend_length_row = 8 - max_legend_length_col = 4 - - # define output file - if filetype not in ["png", "pdf", "svg"]: - text = "Provide valid file type - png, pdf, or svg" - logprint(text, start=False, printing=True) - filetype="png" - - # check if length of information fit - if not gff_legend and ((bins != [] and len(colors) != lcs_shading_num+1) or (bins != [] and len(colors) != len(bins)+1)): - if bins != [] and len(colors) != lcs_shading_num+1: - text = "**Attention**\nlcs_shading_num (%d) does not match number of colors (%d)!\n"% (lcs_shading_num, len(bins)) - elif bins != [] and len(colors) != len(bins)+1: - text = "**Attention**\nnumber of LCS length bins (%d) does not match number of colors (%d)!\n" % (len(colors), len(bins)) - logprint(text, start=False, printing=True) - elif gff_legend and len(bins) != len(colors): - text = "**Attention**\nnumber of GFF Feature Types (%d) does not match number of colors (%d)!\n" % (len(colors), len(bins)) - logprint(text, start=False, printing=True) - - # set alpha values to opaque if none are provided - if alphas == []: - for item in colors: - alphas.append(1) - - # legend data points - data_points = range(len(colors)) - if not gff_legend: - - # specify intervals, if max_len provided - if max_len != None: - multi_factor = 100 # one digit - if max_len <= 1: - multi_factor = 1000 # two digits - # len_interval_size = (max_len-min_len) * multi_factor *1. // lcs_shading_num * (1./ multi_factor) - len_interval_size = (max_len-min_len) * 1. / lcs_shading_num - len_pos = [float("%.2f" % (min_len))] - # calculate interval positions - for idx in range(lcs_shading_num): - len_pos.append(float("%.2f" % (len_pos[-1] + len_interval_size))) - - if prefix.startswith("custom-matrix") and (0 <= max_len <= 100 and 0 <= min_len <= 100): - unit = "%" - elif prefix.startswith("custom-matrix"): - unit = "" - - text = "\n%d Legend intervals from %.2f to %.2f: \n\t%s - number: %d, step: %.2f, unit: %s\n" % (lcs_shading_num+1, min_len, max_len, str(len_pos), len(len_pos), len_interval_size, unit) - logprint(text, start=False, printing=True) - pos = len_pos - interval_size = len_interval_size - # generate legend labels acc. to standard interval notation - else: - # use default max_len = 100 and min_len = 0 - len_interval_size = 100. / lcs_shading_num - pos = [float("%.2f" % (0))] - # calculate interval positions - for idx in range(lcs_shading_num): - pos.append(float("%.2f" % (pos[-1] + len_interval_size))) - - # interval_size = 100 // lcs_shading_num - # pos = range(interval_size, 101+interval_size, interval_size) - - # remove unneccessary zeros in decimal places (i.e. if x.x00 in all entries) - while True: - last_digit_all_zero = True - no_delim = False - for idx in range(len(pos)): - # only process if fraction with decimal places - if not "." in str(pos[idx]): - no_delim = True - break - # only process when all entries end in zero - elif str(pos[idx])[-1] != "0": - last_digit_all_zero = False - break - if not last_digit_all_zero or no_delim: - break - # remove last decimal place (== 0) from all entries - else: - temp_pos = pos[:] - for idx in range(len(pos)): - if not str(pos[idx])[-2] == ".": - pos[idx] = float(str(pos[idx])[:-1]) - else: - pos[idx] = int(str(pos[idx])[:-2]) - logprint("Shortening legend entries: %s - %s" % (temp_pos, pos)) - - # eliminate fractions if unit == bp/aa - if unit in ["aa", "bp"]: - for idx in range(len(pos)): - temp_pos = pos[:] - rounded_unit = False - if "." in str(pos[idx]): - rounded_unit = True - # round values up to next integer (keep integer, if not a fraction) - pos[idx] = int(pos[idx] / 1) + int(pos[idx] % 1 > 0) - if idx == len(pos) - 1 and pos[idx] == 101: - pos[idx] = 100 - if rounded_unit: - logprint("Fractions not permitted for unit '%s': %s -> %s" % (unit, temp_pos, pos)) - - if bins != []: # labels provided - legend_labels = bins[:] - legend_labels.append("max") - legend_labels_lengths = [] - for item in bins: - legend_labels_lengths.append("[%d %s, %d %s)" % (item - min(bins), unit, item, unit)) - if len(bins) == len(colors) - 1: - legend_labels_lengths.append("[%d %s, %s]" % (max(bins), unit, u"\u221E")) # infinite - - else: - legend_labels = [] - legend_labels_lengths = [] - for idx in range(len(pos)): - num = pos[idx] - legend_labels.append("[%d%%, %d%%)" % (num - interval_size, num)) - if max_len != None: - num = len_pos[idx] - # as int or float - if num == int(num) and int(len_interval_size) == len_interval_size: - legend_labels_lengths.append("[%d %s, %d %s)" % (num, unit, num + len_interval_size, unit)) - else: - legend_labels_lengths.append("[%.2f %s, %.2f %s)" % (num, unit, num + len_interval_size, unit)) - legend_labels[-1] = "100" + unit - if max_len != None: - if num == int(num) and int(len_interval_size) == len_interval_size: - legend_labels_lengths[-1] = u"[%d %s, \u221E]" % (max_len, unit) - else: - legend_labels_lengths[-1] = u"[%.2f %s, \u221E]" % (max_len, unit) - - # set labels and choose file name - if gff_legend: - label_text = bins[:] - edge_col = None - legend_file_name = "GFF_Shading_Legend_n%d." % lcs_shading_num + filetype - elif max_len != None: - label_text = legend_labels_lengths[:] - edge_col = "black" - legend_file_name = "Polydotplot_LCS_Shading_Legend_max%d%s_n%d." % (max_len, unit, lcs_shading_num+1) + filetype - elif bins != []: - label_text = legend_labels_lengths[:] - edge_col = "black" - legend_file_name = "Polydotplot_LCS_Shading_Legend_%d%s_n%d." % (bins[0], unit, lcs_shading_num+1) + filetype - else: - label_text = legend_labels[:] - edge_col = "black" - legend_file_name = "Polydotplot_LCS_Shading_Legend_%%len_n%d." % (lcs_shading_num+1) + filetype - - if prefix != None and prefix != "": - if not prefix.endswith("-"): - prefix = prefix + "-" - legend_type = "LCS" - if prefix.startswith("custom-matrix"): - prefix = prefix.replace("custom-matrix", "")[1:] - legend_type = "CustomMatrix" - legend_file_name = prefix + legend_file_name.replace("LCS", legend_type) - - # plot legend figure - fig, ax = P.subplots(3, 1, figsize=(len(colors)*2, len(colors)*2)) - for idx in range(len(colors)): - ax[0].bar(data_points[idx]+1, data_points[idx]+1, color=colors[idx], label=label_text[idx], - alpha=alphas[idx], edgecolor=edge_col) - ax[1].bar(data_points[idx]+1, 0, color=colors[idx], label=label_text[idx], - alpha=alphas[idx], edgecolor=edge_col) - ax[2].bar(data_points[idx]+1, 0, color=colors[idx], label=label_text[idx], - alpha=alphas[idx], edgecolor=edge_col) - ax[1].set_ylim(0,1) - ax[2].set_ylim(0,1) - ax[1].legend(ncol=((len(colors)-1)//max_legend_length_row)+1, framealpha=1) # vertical legend - col_num = len(colors) - if len(colors) > max_legend_length_col: - remainder = 0 - if len(colors) % max_legend_length_col != 0: - remainder = 1 - row_num = len(colors) // max_legend_length_col + remainder - remainder = 0 - if len(colors) % row_num != 0: - remainder = 1 - col_num = len(colors) // row_num + remainder - ax[2].legend(ncol=col_num, framealpha=1) # horizontal legend - - P.savefig(legend_file_name) - - return legend_file_name - - -############################### -# Analysis Functions # -############################### - -def wobble_replacement(sequence, general_ambiguity_code, verbose=False): - """ - get all degenerated sequences for sequence with ambiguous residues - (only residues considered that are keys in wobble_dictionary) - """ - - # get positions of ambiguous residues - wobble_pos = [] - for idx in range(len(sequence)): - letter = sequence[idx] - if letter in general_ambiguity_code.keys(): - wobble_pos.append(idx) - - if verbose: - text = "\t%d wobbles" % len(wobble_pos) - logprint(text, start=False, printing=True) - - # replace one wobble through each iteration by all possible residues - # repeat if still wobbles in new kmers - kmer_variants = [sequence] - while True: - if verbose: - text = "\t\t%d kmer variants" % len(kmer_variants) - logprint(text, start=False, printing=True) - temp_kmers = set([]) - for kmer in kmer_variants: - for idx in wobble_pos: - letter = kmer[idx] - if letter in general_ambiguity_code.keys(): - for base in general_ambiguity_code[kmer[idx]]: - newkmer = kmer[:idx] + base + kmer[idx+1:] - temp_kmers.add(newkmer) - wobble = False - for kmer in temp_kmers: - for idx in range(len(kmer)): - letter = kmer[idx] - if letter in general_ambiguity_code.keys(): - wobble = True - break - if wobble: - break - kmer_variants = set(list(temp_kmers)[:]) - if not wobble: - break - - return kmer_variants - -def split_diagonals(data, stepsize=1): - """ - split array if point difference exceeds stepsize - data = sorted list of numbers - """ - return np.split(data, np.where(np.diff(data) != stepsize)[0]+1) - -def longest_common_substring(s1, s2): - m = [[0] * (1 + len(s2)) for i in xrange(1 + len(s1))] - longest, x_longest = 0, 0 - for x in xrange(1, 1 + len(s1)): - for y in xrange(1, 1 + len(s2)): - if s1[x - 1] == s2[y - 1]: - m[x][y] = m[x - 1][y - 1] + 1 - if m[x][y] > longest: - longest = m[x][y] - x_longest = x - else: - m[x][y] = 0 - return longest - -def lcs_from_x_values(x_values): - """ - calculate length of longest common substring based on nested list of numbers - """ - if len(x_values) == 0: - return 0 - # get lengths of each subarray data - lengths = np.array([len(i) for i in x_values]) - return max(lengths) - - -############################### -# Matching Functions # -############################### - -def find_match_pos_diag(seq1, seq2, wordsize, report_lcs=False, rc_option=True, convert_wobbles=False, max_N_percentage=49, type_nuc=True, verbose=False): - """ - find all matching positions with matches >= wordsize - convert matching points into lines of the length of the match - (+ optional handling of ambiguities) - """ - global t1 # timer - - # look for Ns in DNA or Xs in proeins (minimum word size) - if type_nuc == True: - any_residue = "N" - else: - any_residue = "X" - - # read sequences - seq_one = seq1.upper(); len_one = len(seq_one) - seq_two = seq2.upper(); len_two = len(seq_two) - - # set ambiguity code for wobble replacement - general_ambiguity_code = alphabets(type_nuc)[2] # nucleotide_ambiguity_code or aminoacid_ambiguity_code - - # forward - ################################# - kmer_pos_dict_one = {}; kmer_pos_dict_two = {} # dictionaries for both sequences - - # reverse complement - ################################# - kmer_pos_dict_three = {}; kmer_pos_dict_four = {} # dictionaries for both sequences - - # create dictionaries with kmers (wordsize) and there position(s) in the sequence - if rc_option: - data_list = [(str(seq_one), kmer_pos_dict_one), - (str(seq_two), kmer_pos_dict_two), - (str(seq_one), kmer_pos_dict_three), - (str(seq_two.reverse_complement()), kmer_pos_dict_four)] - else: - data_list = [(str(seq_one), kmer_pos_dict_one), - (str(seq_two), kmer_pos_dict_two)] - for (seq, kmer_pos_dict) in data_list: - for i in range(len(seq)-wordsize+1): - kmer = seq[i:i+wordsize] - # discard kmer, if too many Ns included - if kmer.count(any_residue)*100./wordsize <= max_N_percentage: - if not convert_wobbles: - try: - kmer_pos_dict[kmer].append(i) - except KeyError: - kmer_pos_dict[kmer] = [i] - else: - wobbles = False - for item in general_ambiguity_code.keys(): - if item in kmer: - wobbles = True - break - if not wobbles: - try: - kmer_pos_dict[kmer].append(i) - except KeyError: - kmer_pos_dict[kmer] = [i] - else: - kmer_variants = wobble_replacement(kmer, general_ambiguity_code) - for new_kmer in kmer_variants: - # print "\t", new_kmer - try: - kmer_pos_dict[new_kmer].append(i) - except KeyError: - kmer_pos_dict[new_kmer] = [i] - - # find kmers shared between both sequences - matches_for = set(kmer_pos_dict_one).intersection(kmer_pos_dict_two) # forward - matches_rc = set(kmer_pos_dict_three).intersection(kmer_pos_dict_four) # reverse complement - - if verbose: - text = "[matches: %i for; %.i rc]" % (len(matches_for), len(matches_rc)) - logprint(text, start=False, printing=True) - - # create lists of x and y co-ordinates for scatter plot - # keep all coordinates of all shared kmers (may match multiple times) - diag_dict_for = {} - diag_dict_rc = {} - for (match_list, pos_dict1, pos_dict2, diag_dict) in [(matches_for, kmer_pos_dict_one, kmer_pos_dict_two, diag_dict_for), - (matches_rc, kmer_pos_dict_three, kmer_pos_dict_four, diag_dict_rc)]: - for kmer in match_list: - for i in pos_dict1[kmer]: - for j in pos_dict2[kmer]: - diag = i-j - points = set(range(i+1, i+wordsize+1)) - if not diag in diag_dict.keys(): - diag_dict[diag] = points - else: - diag_dict[diag].update(points) - - # convert coordinate points to line start and stop positions - x1 = [] # x values reverse - y1 = [] # y values forward - for diag in diag_dict_for.keys(): - x_values = np.array(sorted(diag_dict_for[diag])) - x1.extend(split_diagonals(x_values)) - y_values = split_diagonals(x_values - diag) - y1.extend(y_values) - - x2 = [] # x values rc - y2 = [] # y values rc - if rc_option: - for diag in diag_dict_rc.keys(): - factor = len_two + diag + 1 - x_values = np.array(sorted(diag_dict_rc[diag])) - x2.extend(split_diagonals(x_values)) - y_values = split_diagonals(factor - x_values, -1) - y2.extend(y_values) - - if verbose: - t1 = time_track(t1) - - if not report_lcs: - return np.array(x1), np.array(y1), np.array(x2), np.array(y2) - else: - # get length of longest common substring based on match lengths - lcs_for = lcs_from_x_values(x1) - lcs_rev = lcs_from_x_values(x2) - return np.array(x1), np.array(y1), np.array(x2), np.array(y2), lcs_for, lcs_rev - -def find_match_pos_regex(seq1, seq2, wordsize, substitution_count=0, report_lcs=False, rc_option=True, convert_wobbles=False, max_N_percentage=49, type_nuc=True, verbose=False): - """ - find all matching positions with matches >= wordsize via regular expression search - fuzzy matching - allow up to substitution_count substitutions - convert matching points into lines of the length of the match - (+ optional handling of ambiguities) - """ - global t1 # timer - - # read sequences - seq_one = seq1.upper(); len_one = len(seq_one) - seq_two = seq2.upper(); len_two = len(seq_two) - - # set ambiguity code for wobble replacement - general_ambiguity_code = alphabets(type_nuc)[2] # nucleotide_ambiguity_code or aminoacid_ambiguity_code - ambiguity_match_dict = alphabets(type_nuc)[3] - - ambiq_residues = "[%s]" % "".join(general_ambiguity_code.keys()) - - # look for Ns in DNA or Xs in proeins (minimum word size) - if type_nuc == True: - any_residue = "N" - else: - any_residue = "X" - - # check for wobble presence - if not (regex.search(ambiq_residues, str(seq_one)) == None and regex.search(ambiq_residues, str(seq_two)) == None): - wobble_found = True - else: - wobble_found = False - - # dictionary for matches - diag_dict_for = {} - diag_dict_rc = {} - counter = [0, 0] - - # one-way matching - if rc_option: - data_list = [(str(seq_one), str(seq_two), diag_dict_for, 0), - (str(seq_one), str(seq_two.reverse_complement()), diag_dict_rc, 1)] - else: - data_list = [(str(seq_one), str(seq_two), diag_dict_for, 0)] - - for seq_query, seq_target, diag_dict, counter_pos in data_list: - # split query sequence into kmers - if not rc_option and counter_pos == 1: - break - - for idx in range(len(str(seq_query))-wordsize+1): - kmer = str(seq_query)[idx:idx+wordsize] - - # skip excessive N/X stretches (big black areas) - if kmer.count(any_residue)*100./wordsize <= max_N_percentage: - # convert kmer to regular expression for wobble_matching - if convert_wobbles and wobble_found: - kmer_string = "" - # replace each residue with matching residues or wobbles - for jdx in range(len(kmer)): - kmer_string += ambiguity_match_dict[kmer[jdx]] - else: - kmer_string = kmer - - # convert to regular expression tolerating substitution errors - if type(substitution_count) == int and substitution_count != 0: - kmer_string = "(%s){s<=%d}" % (kmer_string, substitution_count) - - # search for regular expression pattern in target sequence - result_matches = regex.finditer(kmer_string, seq_target, overlapped=True, concurrent=True) - - # investigate all hits - last_motif_start = 0 - for result in result_matches: - # skip hits only differing in length of TSD region 1 - if result.start() > last_motif_start: - counter[counter_pos] += 1 - last_motif_start += result.start() - - kmer2 = seq_target[result.start():result.end()] - - # skip excessive N/X stretches (big black areas) - if kmer2.count(any_residue)*100./wordsize <= max_N_percentage: - diag = idx-(result.start()) - points = set(range(idx+1, idx+wordsize+1)) - if not diag in diag_dict.keys(): - diag_dict[diag] = points - else: - diag_dict[diag].update(points) - - if verbose: - text = "%5.i \tforward matches" % counter[0] - text += "\n%5.i \treverse complementary matches" % counter[1] - logprint(text, start=False, printing=True) - - # convert coordinate points to line start and stop positions - x1 = [] # x values reverse - y1 = [] # y values forward - for diag in diag_dict_for.keys(): - x_values = np.array(sorted(diag_dict_for[diag])) - x1.extend(split_diagonals(x_values)) - y_values = split_diagonals(x_values - diag) - y1.extend(y_values) - - x2 = [] # x values rc - y2 = [] # y values rc - if rc_option: - for diag in diag_dict_rc.keys(): - factor = len_two + diag + 1 - x_values = np.array(sorted(diag_dict_rc[diag])) - x2.extend(split_diagonals(x_values)) - y_values = split_diagonals(factor - x_values, -1) - y2.extend(y_values) - - if verbose: - t1 = time_track(t1) - - if not report_lcs: - return np.array(x1), np.array(y1), np.array(x2), np.array(y2) - else: - # get length of longest common substring based on match lengths - lcs_for = lcs_from_x_values(x1) - lcs_rev = lcs_from_x_values(x2) - return np.array(x1), np.array(y1), np.array(x2), np.array(y2), lcs_for, lcs_rev - - -############################### -# Dot Plot Functions # -############################### - -def selfdotplot(input_fasta, wordsize, prefix=None, plot_size=10, label_size=10, filetype='png', type_nuc=True, convert_wobbles=False, substitution_count=0, alphabetic_sorting=False, mirror_y_axis=False, title_length=float("Inf"), title_clip_pos="B", max_N_percentage=49, verbose=False, multi=True, ncols=4, nrows=5, gff_files=[], gff_color_dict={"others": ("grey", 1, 0)}): - """ - self-against-self dotplot - partially from biopython cookbook - """ - - # read sequences - seq_dict, sequences = read_seq(input_fasta) - if seq_dict == {}: - logprint("\nFailed to load sequences") - return [] - - if alphabetic_sorting: - sequences = sorted(sequences) - - # check if at least one input sequence - if len(sequences) == 0: - text = "\n%s\n\nCreating %s selfdotplot images\n%s\n\n=>" % (50*"=", len(sequences), 28*"-") - text += " No sequences provided for selfdotplot!\n\nTerminating polydotplot!" - logprint(text, start=False, printing=True) - return - elif len(sequences) == 1 and multi: - text = "\n\nCreating collage output for single selfdotplot!" - text += "\nRecommendation: Change to individual mode by using '--collage_output n'!\n\n" - logprint(text, start=False, printing=True) - - if multi and (ncols == 0 or nrows == 0): - ncols = max(ncols, 1) - nrows = max(nrows, 1) - text = "\n\nSelfdotplot Collage: Invalid collage - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - if multi and ncols > len(sequences): - ncols = len(sequences) - nrows = 1 - text = "\n\nSelfdotplot Collage: Few sequences - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - elif multi and ncols*(nrows-1) > len(sequences): - nrows = ((len(sequences)-1) // ncols) + 1 - text = "\n\nSelfdotplot Collage: Few sequences - correcting number of rows:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - if multi and not (nrows == 1 and ncols == 1) and plot_size <= label_size/2: - label_size = plot_size * 3 // 2 - text = "Reducing label size for better visualization to %d\n" % label_size - logprint(text, start=False, printing=True) - - # read gff annotation data if provided for shading - if gff_files != None and gff_files != []: - text = "\n%s\n\nReading %s GFF annotation files\n%s\n\n=> %s\n" % (50*"=", len(gff_files), 28*"-", ", ".join(gff_files)) - logprint(text, start=False, printing=True) - if prefix != None and prefix != "": - legend_prefix = prefix + "-Selfdotplot" - else: legend_prefix = "Selfdotplot" - feat_dict = read_gffs(gff_files, color_dict=gff_color_dict, type_nuc=type_nuc, prefix=legend_prefix, filetype=filetype, verbose=verbose) - - global t1 - - print "\n%s\n\nCreating %s selfdotplot images\n%s\n\n=>" % (50*"=", len(sequences), 28*"-"), - log_txt = "\n%s\n\nCreating %s selfdotplot images\n%s\n\n=>" % (50*"=", len(sequences), 28*"-") - - # preparations for file name - name_graph = "Selfdotplots" - if prefix != None: - if not prefix[-1] == "-": - prefix = prefix + "-" - else: - prefix = "" - suffix = "" - if convert_wobbles: - suffix += "_wobbles" - if substitution_count != 0: - suffix += "_S%d" % substitution_count - if multi: - suffix += "_collage" - - # calculate fig ratios - if not multi: - ncols = 1 - nrows = 1 - figsize_x, figsize_y = calc_fig_ratio(ncols, nrows, plot_size) - - P.cla() # clear any prior graph - if multi: - fig = P.figure(figsize=(figsize_x, figsize_y)) - page_counter = 1 - list_of_png_names = [] - - counter = 0 - for seq_name in sequences: - print seq_name, - log_txt += " " + seq_name - - counter += 1 - if not multi: - P.cla() # clear any prior graph - - # read sequence - seq_record = seq_dict[seq_name] - name_seq = seq_record.id - seq_one = seq_record.seq.upper() - length_seq = len(seq_one) - - # get positions of matches - if substitution_count != 0: - # print "RE" - x_lists, y_lists, x_lists_rc, y_lists_rc = find_match_pos_regex(seq_one, seq_one, wordsize, substitution_count=substitution_count, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, type_nuc=type_nuc, verbose=verbose) - else: - # print "DIAG", - x_lists, y_lists, x_lists_rc, y_lists_rc = find_match_pos_diag(seq_one, seq_one, wordsize, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, type_nuc=type_nuc, verbose=verbose) - - # plotting with matplotlib - ################################# - - # combined plotting - if multi: - # plotting subplot with matplotlib - ax = P.subplot(nrows, ncols, counter) # rows, columns, plotnumber - - # shade annotated regions - if gff_files != None and gff_files != []: - if seq_name in feat_dict.keys(): - features = feat_dict[seq_name] - for item in features: - feat_type, start, stop = item - feat_color, strength, zoom = gff_color_dict[feat_type.lower()] - start = max(0, start - zoom - 0.5) - stop = min(length_seq+1, stop + zoom + 0.5) - width = stop - start - ax.add_patch(patches.Rectangle((start, start), # (x,y) - width, width, # width, height - edgecolor=None, linewidth=line_width+zoom, - fill=True, facecolor=feat_color, - alpha=strength)) - - # collect lines - lines = [] - color_list = [] - for (x_lines, y_lines, col) in [(x_lists_rc, y_lists_rc, line_col_rev), (x_lists, y_lists, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # format axes - # print P.xticks()[0], P.yticks()[0] - P.axis('scaled') # make images quadratic - P.xlim(0, length_seq+1) - if mirror_y_axis: - P.ylim(0, length_seq+1) # rotate y axis (point upwards) - else: - P.ylim(length_seq+1, 0) # rotate y axis (point downwards) - P.xlabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.ylabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - - # # use same tick labels for x and y axis - # tick_locs, tick_labels = P.yticks() - # P.xticks(tick_locs) - # P.xlim(0, length_seq+1) - - P.title(unicode_name(shorten_name(name_seq, max_len=title_length, title_clip_pos=title_clip_pos)), fontsize=label_size, fontweight='bold') - # P.title(unicode_name(name_seq), fontsize=label_size*1.3, fontweight='bold') - - # save figure and reinitiate if page is full - if counter == ncols * nrows: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - P.subplots_adjust(hspace=0.5, wspace=0.5) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' % (prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() - - list_of_png_names.append(fig_name) - - counter = 0 - page_counter += 1 - - fig = P.figure(figsize=(figsize_x, figsize_y)) - - # plotting separate figure files - else: # not multi - - fig = P.figure(figsize=(plot_size, plot_size)) # figure size needs to be a square - ax = P.subplot(1, 1, 1) # rows, columns, plotnumber - - # shade annotated regions - if gff_files != None and gff_files != []: - if seq_name in feat_dict.keys(): - features = feat_dict[seq_name] - for item in features: - feat_type, start, stop = item - feat_color, strength, zoom = gff_color_dict[feat_type.lower()] - start = max(0, start - zoom - 0.5) - stop = min(length_seq+1, stop + zoom + 0.5) - width = stop - start - ax.add_patch(patches.Rectangle((start, start), # (x,y) - width, width, # width, height - edgecolor=None, linewidth=line_width+zoom, - fill=True, facecolor=feat_color, - alpha=strength)) - - # collect lines - lines = [] - number = 0 - color_list = [] - for (x_lines, y_lines, col) in [(x_lists_rc, y_lists_rc, line_col_rev), (x_lists, y_lists, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # format axes - P.axis('scaled') # make images quadratic - P.xlim(0, length_seq+1) - if mirror_y_axis: - P.ylim(0, length_seq+1) # rotate y axis (point upwards) - else: - P.ylim(length_seq+1, 0) # rotate y axis (point downwards) - P.xlabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.ylabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - - # # use same tick labels for x and y axis - # tick_locs, tick_labels = P.yticks() - # P.xticks(tick_locs) - # P.xlim(0, length_seq+1) - - P.title(unicode_name(shorten_name(name_seq, max_len=title_length, title_clip_pos=title_clip_pos)), fontsize=label_size*1.3, fontweight='bold') - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s-%d_%s_wordsize%i%s.%s' %(prefix, name_graph, counter, shorten_name(name_seq, max_len=title_length, title_clip_pos=title_clip_pos), wordsize, suffix, filetype) - P.savefig(fig_name, bbox_inches='tight') - - P.close() - P.cla() # clear any prior graph - - list_of_png_names.append(fig_name) - - if multi and counter >= 1: - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - P.subplots_adjust(hspace=0.5, wspace=0.5) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' %(prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() # clear any prior graph - - list_of_png_names.append(fig_name) - - print "\n\nDrawing selfdotplots done" - log_txt += "\n\nDrawing selfdotplots done" - logprint(log_txt, start=False, printing=False) - - return list_of_png_names - -def pairdotplot(input_fasta, wordsize, prefix=None, plot_size=10, label_size=10, filetype='png', type_nuc=True, convert_wobbles=False, substitution_count=0, alphabetic_sorting=False, mirror_y_axis=False, title_length=float("Inf"), title_clip_pos="B", max_N_percentage=49, verbose=False, multi=True, ncols=4, nrows=5, x_label_pos_top=True, only_vs_first_seq=False, length_scaling=True, scale_delim_col="red"): - """ - pairwise dotplot (all-against-all) - """ - - # read sequences - seq_dict, sequences = read_seq(input_fasta) - if seq_dict == {}: - logprint("\nFailed to load sequences") - return [] - - if alphabetic_sorting: - sequences = sorted(sequences) - - # check if at least two input sequences - if len(sequences) < 2: - text = "\n%s\n\nCreating %d paired dotplot image \n%s\n\n=>" % (50*"=", len(sequences)*(len(sequences)-1)/2, 36*"-") - text += " Please provide at least two sequences for pairdotplot!\n\nTerminating paired dotplot!" - logprint(text, start=False, printing=True) - return - elif len(sequences) == 2 and multi: - text = "\n\nCreating collage output for single pairdotplot!" - text += "\nRecommendation: Change to individual mode by using '--collage_output n'!\n\n" - logprint(text, start=False, printing=True) - - if multi and (ncols == 0 or nrows == 0): - ncols = max(ncols, 1) - nrows = max(nrows, 1) - text = "\n\nPairdotplot Collage: Invalid collage settings - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - if multi and ncols > len(sequences)*(len(sequences)-1): - ncols = len(sequences) - nrows = 1 - text = "\n\nPairdotplot Collage: Few sequences - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - elif multi and ncols*(nrows-1) > len(sequences)*(len(sequences)-1): - nrows = ((len(sequences)-1) // ncols) + 1 - text = "\n\nPairdotplot Collage: Few sequences - correcting number of rows:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - if not only_vs_first_seq: - text = "\n%s\n\nCreating %d paired dotplot image for\n%s\n\n=>" % (50*"=", len(sequences)*(len(sequences)-1)/2, 36*"-") - text += ", ".join(sequences) + "\n" - else: - text = "\n%s\n\nCreating %d paired dotplot images against 1st sequence '%s':\n%s\n\n=>" % (50*"=", len(sequences)-1, sequences[0], 36*"-") - text += ", ".join(sequences[1:]) + "\n" - logprint(text, start=False, printing=True) - - if multi and not (nrows == 1 and ncols == 1) and plot_size <= label_size/2: - label_size = plot_size * 3 // 2 - text = "Reducing label size for better visualization to %d\n" % label_size - logprint(text, start=False, printing=True) - - y_label_rotation = "vertical" - # for cartesian coordinate system with mirrored y-axis: plot x labels below plot - if mirror_y_axis: - x_label_pos_top = False - - # preparations for file name - name_graph = "Pairdotplot" - if prefix != None: - if not prefix[-1] == "-": - prefix = prefix + "-" - else: - prefix = "" - suffix = "" - if convert_wobbles: - suffix += "_wobbles" - if substitution_count != 0: - suffix += "_S%d" % substitution_count - if length_scaling: - suffix += "_scaled" - if multi: - suffix += "_collage" - - # calculate fig ratios - if not multi: - ncols = 1 - nrows = 1 - figsize_x, figsize_y = calc_fig_ratio(ncols, nrows, plot_size) - - P.cla() # clear any prior graph - list_of_png_names = [] - if multi: - fig = P.figure(figsize=(figsize_x, figsize_y)) - page_counter = 1 - - # prepare LCS data file - lcs_data_file = open("%sPairdotplot_wordsize%d_lcs_data_file%s.txt" % (prefix, wordsize, suffix.replace("_scaled", "").replace("_collage", "")), 'w') - lcs_data_file.write("\t".join(["#title1", "title2", "len_seq1", "len_seq2", "len_lcs_for", "%_min_seq_len", "len_lcs_rev", "%_min_seq_len"])+"\n") - - counter, seq_counter = 0, 0 - print "Drawing pairwise dotplot...", - log_txt = "Drawing pairwise dotplot..." - if verbose: - seq_text = "" - for idx in range(len(sequences)-1): - if verbose: - print "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]), - seq_text += "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]) - rec_two = seq_dict[sequences[idx]] - name_two = rec_two.id - seq_two = rec_two.seq - len_two = len(seq_two) - - for jdx in range(idx+1, len(sequences)): - rec_one = seq_dict[sequences[jdx]] - name_one = rec_one.id - seq_one = rec_one.seq - len_one = len(seq_one) - - counter += 1 - seq_counter += 1 - if verbose: - print sequences[jdx], - seq_text += " " + sequences[jdx] - elif not seq_counter % 25: - print seq_counter, - log_txt += " " + str(seq_counter) - - # get positions of matches - if substitution_count != 0: - # print "RE" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_regex(seq_one, seq_two, wordsize, substitution_count=substitution_count, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - else: - # print "DIAG" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_diag(seq_one, seq_two, wordsize, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - - # write LCS data file - lcs_data_file.write("\t".join([name_one, name_two, str(len_one), str(len_two), - str(lcs_for), str(round((lcs_for*100./min(len_one, len_two)), 3)), - str(lcs_rev), str(round((lcs_rev*100./min(len_one, len_two)), 3))]) + "\n") - - - # plotting with matplotlib - ################################# - - # combined plotting - if multi: - # plotting subplot with matplotlib - ax = P.subplot(nrows, ncols, counter) # rows, columns, plotnumber - - else: - # calculate figure size for separate figures - if len_one >= len_two: - sizing = (plot_size, max(2, (plot_size)*len_two*1./len_one)) - # sizing = (plot_size, min(plot_size, max(2, (plot_size-2)*len_two*1./len_one+2))) - else: - sizing = (max(2, (plot_size)*len_one*1./len_two), plot_size) - # sizing = (min(plot_size, max(2, (plot_size-2)*len_one*1./len_two+2)), plot_size) - fig = P.figure(figsize=(plot_size, plot_size)) - - ax = P.subplot(1, 1, 1) - - # collect lines - lines = [] - color_list = [] - for (x_lines, y_lines, col) in [(x2, y2, line_col_rev), (x1, y1, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # format axes - P.xlabel(unicode_name(shorten_name(name_one, max_len=title_length, title_clip_pos=title_clip_pos)) + " [%s]" % aa_bp_unit, fontsize=label_size, fontweight='bold', labelpad=4) - P.ylabel(unicode_name(shorten_name(name_two, max_len=title_length, title_clip_pos=title_clip_pos)) + " [%s]" % aa_bp_unit, fontsize=label_size, fontweight='bold', labelpad=4) - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - - # P.axis('scaled') # make images scaled by size ### optional update ### - if not multi: - if length_scaling: - ax.set_aspect(aspect='equal', adjustable='box', anchor='NW') - P.xlim(0, len_one+1) - # xlimit = [0, len_one+1] - if mirror_y_axis: - P.ylim(0, len_two+1) # rotate y axis (point upwards) - else: - P.ylim(len_two+1, 0) # rotate y axis (point downwards) - elif not length_scaling: - P.xlim(0, len_one+1) - # xlimit = [0, len_one+1] - if mirror_y_axis: - P.ylim(0, len_two+1) # rotate y axis (point upwards) - else: - P.ylim(len_two+1, 0) # rotate y axis (point downwards) - else: - max_len = max(len_one, len_two) - P.xlim(0, max_len+1) - # xlimit = [0, max_len+1] - if mirror_y_axis: - P.ylim(0, max_len+1) # rotate y axis (point upwards) - else: - P.ylim(max_len+1, 0) # rotate y axis (point downwards) - - # plot line deliminating shorter sequence - if max_len != len_one: - ax.plot((len_one+1, len_one+1), (0, len_two), marker="", linestyle="--", color=scale_delim_col, markerfacecolor="r") - if max_len != len_two: - ax.plot((0, len_one), (len_two+1, len_two+1), marker="", linestyle="--", color=scale_delim_col, markerfacecolor="r") - - # # use same tick labels for x and y axis - # if P.xlim() == P.ylim(): - # tick_locs, tick_labels = P.yticks() - # P.xticks(tick_locs) - # P.xlim(xlimit) - - # evtl. switch x axis position - if x_label_pos_top: - ax.xaxis.tick_top() - ax.xaxis.set_label_position('top') - P.setp(ax.get_xticklabels(), fontsize=label_size*.9) - P.setp(ax.get_yticklabels(), fontsize=label_size*.9) - - # save figure and reinitiate if page is full - if multi and counter == ncols * nrows: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - if x_label_pos_top: - P.subplots_adjust(hspace=.5, wspace=.5, top=0.95) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=.5, wspace=.5, bottom=0.05) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' %(prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() - - list_of_png_names.append(fig_name) - - counter = 0 - page_counter += 1 - - fig = P.figure(figsize=(figsize_x, figsize_y)) - - # plotting separate figure files - elif not multi: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - if y_label_rotation == "horizontal": - if x_label_pos_top: - P.subplots_adjust(hspace=0.02, wspace=0.02, left=0.13, top=0.95) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=0.02, wspace=0.02, left=0.13, bottom=0.05) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=0.02, wspace=0.02) # space between rows - def 0.4 - - # name and create output files - fig_name = '%s%s-%d_wordsize%i%s.%s' % (prefix, name_graph, counter, wordsize, suffix, filetype) - P.savefig(fig_name) - P.close() - P.cla() - - list_of_png_names.append(fig_name) - fig = P.figure() - - if only_vs_first_seq: - break - - # save figure - if multi and counter >= 1: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - if x_label_pos_top: - P.subplots_adjust(hspace=0.5, wspace=0.5, top=0.95) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=0.5, wspace=0.5, bottom=0.05) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' %(prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() - - list_of_png_names.append(fig_name) - - if not verbose: - print seq_counter, "done" - log_txt += str(seq_counter) + " done" - else: - print "\n%d done" % seq_counter - log_txt += "\n%d done" % seq_counter - logprint(log_txt, start=False, printing=False) - - if verbose: - print - logprint(seq_text, start=False, printing=False) - - return list_of_png_names - -def polydotplot(input_fasta, wordsize, prefix=None, plot_size=10, label_size=10, filetype='png', type_nuc=True, convert_wobbles=False, substitution_count=0, alphabetic_sorting=False, mirror_y_axis=False, title_length=float("Inf"), title_clip_pos="B", max_N_percentage=49, verbose=False, gff_files=[], gff_color_dict={"others": ("grey", 1, 0)}, x_label_pos_top=True, lcs_shading=True, lcs_shading_ref=0, lcs_shading_interval_len=100, lcs_shading_ori=0, lcs_shading_num=5, spacing=0.04, input_user_matrix_file="", user_matrix_print=True, rotate_labels=False): - """ - all-against-all dotplot - derived from dotplot function - - lcs_shading_refs: - 0 color relative to maximum lcs observed in dataset [default] - 1 color by coverage of shorter sequence (e.g. lcs = 70% of seq1) - lcs_shading_ori - 0 forward only - 1 reverse only - 2 both orientations (in opposite plot) - """ - - # read sequences - seq_dict, sequences = read_seq(input_fasta) - if seq_dict == {}: - logprint("\nFailed to load sequences") - return [] - - if alphabetic_sorting: - sequences = sorted(sequences) - - if len(sequences) == 0: - text = "\n%s\n\nCreating %dx%d polydotplot image\n%s\n\n=>" % (50*"=", len(sequences), len(sequences), 30*"-") - text += " No sequences provided for polydotplot!\n\nTerminating polydotplot!" - logprint(text, start=False, printing=True) - return - elif len(sequences) == 1: - text = "\n\nCreating polydotplot for single sequence!" - text += "\nRecommendation: Use selfdotplot via '--plotting_mode 0'!\n\n" - logprint(text, start=False, printing=True) - - text = "\n%s\n\nCreating %dx%d polydotplot image\n%s\n\n=>" % (50*"=", len(sequences), len(sequences), 30*"-") - text += " " + " ".join(sequences) + "\n" - logprint(text, start=False, printing=True) - - # read gff annotation data if provided for shading - if gff_files != None and gff_files != []: - text = "\n%s\n\nReading %s GFF annotation files\n%s\n\n=> %s\n" % (50*"=", len(gff_files), 28*"-", ", ".join(gff_files)) - logprint(text, start=False, printing=True) - if prefix != None and prefix != "": - legend_prefix = prefix + "-Polydotplot" - else: legend_prefix = "Polydotplot" - feat_dict = read_gffs(gff_files, color_dict=gff_color_dict, type_nuc=type_nuc, prefix=legend_prefix, filetype=filetype, verbose=verbose) - - if lcs_shading and not type_nuc: - if lcs_shading_ori != 0: - lcs_shading_ori = 0 - text = "Protein shading does not support reverse complementary matching!\n" - logprint(text, start=False, printing=True) - - # read custom shading matrix & match names of sequences to fasta - if input_user_matrix_file != "" and input_user_matrix_file != None: - logprint("Reading user matrix file: %s" % input_user_matrix_file) - # lcs_shading_ori = 2 - custom_dict = read_matrix(input_user_matrix_file) - if custom_dict != {}: - custom_shading = True - custom_similarity_dict = {} - invalid_entries = [] - custom_max = 0 - custom_min = float("Inf") - for key in custom_dict.keys(): - number_key = [] - - # convert number into float - try: - value = float(custom_dict[key]) - if not "." in custom_dict[key]: - value = int(custom_dict[key]) - custom_max = max(custom_max, value) - custom_min = min(custom_min, value) - except: - value = custom_dict[key] - if value == "": - value = None - invalid_entries.append(key) - # match matrix names with sequence names - for item in key: - if item in sequences: - number_key.append(sequences.index(item)) - else: - number_key.append(-1) - # dictionary with tuple of sorted sequence indices as key and number as value - custom_similarity_dict[tuple(sorted(number_key))] = value - if len(invalid_entries) != 0: - text = "No valid number in custom similarity matrix for %d entries: \n\t" % (len(invalid_entries)) - for key in invalid_entries: - text += str(key) + " - " + str(custom_dict[key]) + "; " - logprint(text[:-2]+"\n") - - text = "Custom user matrix given: min %.2f, max %.2f\n" % (custom_min, custom_max) - - # artificially rounding intervals if likely identity/divergence percentages - if 0 <= custom_min < 1 and 0 < custom_max <= 1: - rounding_factor = 5 - multi_factor = 100 - text += " > artificially rounding custom shading intervals: old (%.2f, %.2f) - " % (custom_min, custom_max) - custom_min = max(0, (multi_factor*custom_min // rounding_factor) * (1.*rounding_factor/multi_factor)) - custom_max = min((multi_factor*custom_max // rounding_factor) * (1.*rounding_factor/multi_factor), 1) - text += "new (%.2f, >%2f)\n" % (custom_min, custom_max) - - elif 0 <= custom_min < 100 and 0 < custom_max <= 100: - rounding_factor = 5 - text += " > artificially rounding custom shading intervals: old (%.2f, %.2f) - " % (custom_min, custom_max) - custom_min = max(0, (custom_min // rounding_factor) * rounding_factor) - custom_max = min((custom_max // rounding_factor) * rounding_factor, 100) - text += "new (%d, >%d)\n" % (custom_min, custom_max) - - logprint(text) - - else: - custom_shading = False - - name_graph = "Polydotplot" - suffix = "" - if convert_wobbles: - suffix += "_wobbles" - if substitution_count != 0: - suffix += "_S%d" % substitution_count - if custom_shading: - suffix += "_matrix" - if lcs_shading: - suffix += "_%dshades_ref%d_ori%s" % (lcs_shading_num+1, lcs_shading_ref, lcs_shading_ori) - if "ref2" in suffix and type_nuc: - suffix = suffix.replace("ref2", "%dbp" % lcs_shading_interval_len) - elif "ref2" in suffix: - suffix = suffix.replace("ref2", "%daa" % lcs_shading_interval_len) - - - # name and create output files (names derived from SEQNAME) - if prefix != None and str(prefix) != "": - prefix = str(prefix) + "-" - else: - prefix = "" - - # preparations for background shading - if lcs_shading or custom_shading: - # create color range white to grey - colors = create_color_list(lcs_shading_num+1, color_map=None, logging=True) - colors_2 = create_color_list(lcs_shading_num+1, color_map="OrRd", logging=True) - - if custom_shading: - text = "Custom Matrix Colors: " + ", ".join(colors_2) - - # write lcs lengths to file - lcs_data_file = open("%sPolydotplot_lcs_data_file%s.txt" % (prefix, suffix.replace("_scaled", "").replace("_collage", "")), 'w') - lcs_data_file.write("\t".join(["#title1", "title2", "len_seq1", "len_seq2", "len_lcs_for", "%_min_seq_len", "len_lcs_rev", "%_min_seq_len"])+"\n") - - # compare sequences pairwise - save lcs and line information in dictionary for plotting - data_dict = {} # keys = tuple(idx, jdx), value = x1, y1, x2, y2 (line positions) - lcs_dict = {} # keys = tuple(idx, jdx), value = length of lcs: lcs_len or (lcs_for, lcs_rev) - for_lcs_set = set([]) # keep lengths to calculate max (excluding self comparisons) - rev_lcs_set = set([]) # keep lengths to calculate max (all) - - text = "\nTotal plot count: %d" % (len(sequences)*(len(sequences))) - text += "\nTotal calculations: %d" % (len(sequences)*(len(sequences)+1)/2) - logprint(text, start=False, printing=True) - - print "\nCalculating shared regions and lengths of longest_common_substring...", - log_txt = "\nCalculating shared regions and lengths of longest_common_substring..." - # determine matches and length of lcs by comparing all sequence pairs - if verbose: - seq_text = "" - counter = 0 - for idx in range(len(sequences)): - if verbose: - print "\n%d\t%s vs." % ((counter+1), sequences[idx]), - seq_text += "\n%d\t%s vs." % ((counter+1), sequences[idx]) - rec_two = seq_dict[sequences[idx]] - name_two = rec_two.id - seq_two = rec_two.seq - len_two = len(seq_two) - - for jdx in range(idx, len(sequences)): - rec_one = seq_dict[sequences[jdx]] - name_one = rec_one.id - seq_one = rec_one.seq - len_one = len(seq_one) - - counter += 1 - if verbose: - print sequences[jdx], - seq_text += " " + sequences[jdx] - elif len(sequences) < 5: - print "\t%s (%d %s), %s (%d %s)" % (name_one, len_one, aa_bp_unit, name_two, len_two, aa_bp_unit) - log_txt += "\t%s (%d %s), %s (%d %s)\n" % (name_one, len_one, aa_bp_unit, name_two, len_two, aa_bp_unit) - else: - if not counter % 25: - print counter, - log_txt += str(counter) - - # get positions of matches & length of longest common substring based on match lengths - if substitution_count != 0: - # print "RE" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_regex(seq_one, seq_two, wordsize, substitution_count=substitution_count, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - else: - # print "DIAG" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_diag(seq_one, seq_two, wordsize, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - data_dict[(idx, jdx)] = x1[:], y1[:], x2[:], y2[:] - lcs_dict[idx, jdx] = lcs_for, lcs_rev - - if idx != jdx: - for_lcs_set.add(lcs_for) - rev_lcs_set.add(lcs_rev) - - lcs_data_file.write("\t".join([name_one, name_two, str(len_one), str(len_two), - str(lcs_for), str(round((lcs_for*100./min(len_one, len_two)), 3)), - str(lcs_rev), str(round((lcs_rev*100./min(len_one, len_two)), 3))]) + "\n") - - if not verbose: - print len(sequences)*(len(sequences)+1)/2, " done\n" - log_txt += str(len(sequences)*(len(sequences)+1)/2) + " done\n" - else: - print "\n%d done" % (len(sequences)*(len(sequences)+1)/2) - log_txt += "\n%d done" % (len(sequences)*(len(sequences)+1)/2) - logprint(log_txt, start=False, printing=False) - - if verbose: - logprint ("\n\nlcs_dict\n" + str(lcs_dict)) - if custom_shading: - logprint ("\ncustom_dict\n" + str(custom_dict)) - logprint ("\ncustom_similarity_dict\n\n" + str(custom_similarity_dict)) - - if verbose: - print - logprint(seq_text+"\n", start=False, printing=False) - - if lcs_shading_ref == 2: - color_bins = [] - text = "\nLCS lengh bins: " - for idx in range(lcs_shading_num): - color_bins.append(lcs_shading_interval_len*(idx+1)) - text += " " + str(lcs_shading_interval_len*(idx+1)) - logprint(text, start=False, printing=True) - - # calculate maximum lcs length - if lcs_shading_ori == 0: # forward only - if len(for_lcs_set) != 0: - max_lcs = max(for_lcs_set) - else: - max_lcs = None - elif lcs_shading_ori == 1: # reverse complement only - if len(rev_lcs_set) != 0: - max_lcs = max(rev_lcs_set) - else: - max_lcs = None - else: # both orientations - if len(rev_lcs_set) != 0 and len(for_lcs_set) != 0: - max_lcs = max(max(rev_lcs_set), max(for_lcs_set)) - elif len(rev_lcs_set) != 0: - max_lcs = max(rev_lcs_set) - elif len(for_lcs_set) != 0: - max_lcs = max(for_lcs_set) - else: - max_lcs = None - - if not max_lcs == None: - text = "Maximum LCS: %d %s" % (max_lcs, aa_bp_unit) - logprint(text, start=False, printing=True) - if custom_shading: - text = "Maximum custom value: %d\n" % custom_max - logprint(text, start=False, printing=True) - - # count sequences - ncols = len(sequences); nrows = len(sequences) - - # get sequence lengths to scale plot widths and heights accordingly - size_ratios = [] - for item in sequences: - size_ratios.append(len(seq_dict[item].seq)) - - P.cla() # clear any prior graph - # use GridSpec to resize plots according to sequence length - if mirror_y_axis: - height_ratios = size_ratios[::-1] - else: - height_ratios = size_ratios[:] - gs = gridspec.GridSpec(nrows, ncols, - width_ratios=size_ratios, - height_ratios=height_ratios) - fig = P.figure(figsize=(plot_size, plot_size)) - - # for cartesian coordinate system with mirrored y-axis: plot x labels below plot - if mirror_y_axis and representation == 1: - x_label_pos_top = True - elif mirror_y_axis or representation == 2: - x_label_pos_top = False - - # print y labels on the right, if upper right triangle is displayed - if (representation == 1 and not mirror_y_axis) or (representation == 2 and mirror_y_axis): - y_label_pos = 0 # last column - else: # left y label - y_label_pos = 1 # first column - - # determine label orientations - if len(sequences) > 5 or rotate_labels: - x_label_rotation = 45 - y_label_rotation = "horizontal" - if x_label_pos_top: - xhalign = 'left' - xvalign = 'bottom' - else: - xhalign = 'right' - xvalign = 'top' - yhalign = "right" - else: - x_label_rotation = "horizontal" - y_label_rotation = "vertical" - xvalign = "center" - xhalign = "center" - yhalign = "center" - yvalign = 'center' - - # check combination of shading parameters for triangular output - if representation != 0 and lcs_shading and custom_shading: # both directions in triangle - logprint("\nAttention: For triangular output custom-shading and LCS shading cannot be combined!\n") - elif representation != 0 and lcs_shading and lcs_shading_ori == 2: # both directions in triangle - logprint("\nAttention: For triangular output LCS shading for both orientations is combined to max of both orientations!\n") - - print "\nDrawing polydotplot...", - log_txt = "\nDrawing polydotplot..." - - # draw subplots - if verbose: - if lcs_shading and custom_shading: - lcs_text = "\n" + "\t".join(["#Seq1", "Seq2", "LCS for [%s]" %aa_bp_unit, "LCS for [%s]" %aa_bp_unit, "Custom matrix value", "Matrix color index", "LCS color index"]) + "\n" - elif lcs_shading: - lcs_text = "\n" + "\t".join(["#Seq1", "Seq2", "LCS for [%s]" %aa_bp_unit, "LCS for [%s]" %aa_bp_unit, "LCS color index for", "LCS color index rev"]) + "\n" - elif custom_shading: - lcs_text = "\n" + "\t".join(["#Seq1", "Seq2", "Custom matrix value", "Color index for", "Color index rev"]) + "\n" - - if verbose: - seq_text = "" - counter, seq_counter = 0, 0 - for idx in range(len(sequences)): - if verbose: - print "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]), - seq_text += "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]) - rec_two = seq_dict[sequences[idx]] - len_two = len(rec_two.seq) - name_two = rec_two.id - - for jdx in range(idx, len(sequences)): - rec_one = seq_dict[sequences[jdx]] - len_one = len(rec_one.seq) - name_one = rec_one.id - - counter += 1 - seq_counter += 1 - if verbose: - print sequences[jdx], - seq_text += " " + sequences[jdx] - elif not seq_counter % 25: - print seq_counter, - log_txt += str(seq_counter) - - # optional shade background according to length of LCS and/or user matrix - ######################################################################### - - # get interval based on LCS - background_colors = [None, None] - if lcs_shading and (lcs_shading_ref==1 or lcs_shading_ref==2 or max_lcs!=None): # self plot max_lcs_for == None - lcs_len = lcs_dict[(idx, jdx)] - l1 = lcs_len[0] # forward - l2 = lcs_len[1] # reverse complement - - lcs_shading_bool = True - - # calculate shading acc. to chosen option - if lcs_shading_ref == 1: # percentage of shorter sequence - color_idx0 = min(len(colors)-1, l1*lcs_shading_num // min(len_one, len_two)) - color_idx1 = min(len(colors)-1, l2*lcs_shading_num // min(len_one, len_two)) - elif lcs_shading_ref == 2: # by given interval size - color_idx0 = min(len(colors)-1, l1 // lcs_shading_interval_len) - color_idx1 = min(len(colors)-1, l2 // lcs_shading_interval_len) - if color_idx0 >= len(colors): - color_idx0 = len(colors) - if color_idx1 >= len(colors): - color_idx1 = len(colors) - else: # percentage of maximum lcs length - color_idx0 = min(len(colors)-1, l1*lcs_shading_num // max_lcs) - color_idx1 = min(len(colors)-1, l2*lcs_shading_num // max_lcs) - else: - lcs_shading_bool = False - - # get interval based on custom matrix - if custom_shading: - # matrix value - try: - custom_value = custom_similarity_dict[(idx, jdx)] - except: - custom_value = "" - - # bottom left triangle = LCS forward/reverse or best of both - if lcs_shading_bool: - if lcs_shading_ori == 0: # forward - color_idx1 = color_idx0 - elif lcs_shading_ori == 2: # both directions - color_idx1 = max(color_idx0, color_idx1) - - # top right triangle = custom value (not colored if text matrix provided) - if type(custom_value) == int or type(custom_value) == float: - color_idx0 = int((custom_value-custom_min)*lcs_shading_num // (custom_max-custom_min)) - # no color if string is proviced - else: - color_idx0 = 0 - - # use best LCS of both orientations for coloring triangle with two-ori-LCS - if representation != 0 and lcs_shading_ori == 2: # both directions in triangle - color_idx0, color_idx1 = max(color_idx0, color_idx1), max(color_idx0, color_idx1) - - # set colors dependent on lcs dependent on orientation - if lcs_shading_bool and not custom_shading: - if idx != jdx: - if lcs_shading_ori == 0: - color_idx1 = color_idx0 - elif lcs_shading_ori == 1: - color_idx0 = color_idx1 - background_colors[0] = colors[color_idx0] - background_colors[1] = colors[color_idx1] - # for selfcomparison, only color reverse complement - elif lcs_shading_ori != 0 and not custom_shading: - background_colors[0] = colors[color_idx1] - # set different colors for shading by LCS + user matrix - elif lcs_shading_bool and custom_shading: - # print colors, background_colors, color_idx0, color_idx1 - background_colors[0] = colors_2[color_idx0] - background_colors[1] = colors[color_idx1] - # set grey color range for user matrix if no LCS shading - elif custom_shading: - background_colors[0] = colors[color_idx0] - background_colors[1] = colors[color_idx0] - - if verbose: - if custom_shading and lcs_shading_bool: - lcs_text += "\t".join([name_one, name_two, str(lcs_len[0]), str(lcs_len[1]), str(custom_value), str(color_idx0), str(color_idx1)]) + "\n" - elif lcs_shading_bool: - lcs_text += "\t".join([name_one, name_two, str(lcs_len[0]), str(lcs_len[1]), str(color_idx0), str(color_idx1)]) + "\n" - elif custom_shading: - lcs_text += "\t".join([name_one, name_two, str(custom_value), str(color_idx0), str(color_idx1)]) + "\n" - - # calculate figure position in polyplot - # diagonal (self-dotplots) - if idx == jdx: - if mirror_y_axis: - seq_num = sequences.index(name_one)+1 - counter1 = seq_num + len(sequences) * (len(sequences)-seq_num) - counter = counter + (counter - 1) // (nrows) - else: - # skip positions below diagonal - counter1 = counter + (counter - 1) // (nrows) # + row_pos - counter = counter1 - counters = [counter1] - - # draw both graphs at once (due to symmetry) - else: - if mirror_y_axis: - col_pos = sequences.index(name_two)+1 - row_pos = len(sequences) - (sequences.index(name_one)+1) - counter1 = row_pos * ncols + col_pos - counter2 = (ncols - col_pos) * ncols + ncols - row_pos - else: - counter1 = counter - col_pos = (counter - 1) % ncols - row_pos = (counter - 1) // (nrows) - counter2 = col_pos * ncols + row_pos + 1 - counters = [counter1, counter2] # lower, upper - - if len(counters) == 2: - seq_counter += 1 - if not verbose and not seq_counter % 25: - print seq_counter, - log_txt += str(seq_counter) - - x_lists, y_lists, x_lists_rc, y_lists_rc = data_dict[(idx, jdx)] - - # plot diagram(s) - for kdx in range(len(counters)): - - if representation == 0 or len(counters) == 1 or (representation == 1 and kdx == 0) or (representation == 2 and kdx == 1): - - fig_pos = counters[kdx] - # plotting subplot with matplotlib - ax = P.subplot(gs[fig_pos-1]) # rows, columns, plotnumber - - # shade annotated regions if gff file(s) provided - if idx == jdx and gff_files != None and gff_files != []: - if name_one in feat_dict.keys(): - features = feat_dict[name_one] - if len_two != len_one: - logprint("Polydot GFF shading for diagonal fields - nequal length error!") - return - for item in features: - feat_type, start, stop = item - feat_color, strength, zoom = gff_color_dict[feat_type.lower()] - start = max(0, start - zoom - 0.5) - stop = min(len_one+1, stop + zoom + 0.5) - width = stop - start - ax.add_patch(patches.Rectangle((start, start), # (x,y) - width, width, # width, height - edgecolor=None, linewidth=line_width+zoom, - fill=True, facecolor=feat_color, - alpha=strength)) - - # if custom matrix value printed into upper matrix triangle, skip data plotting - # text print in top triangle - if user_matrix_print and custom_shading and kdx==0 and idx!=jdx: - data_plotting = False - # dotplot in bottom triangle - else: - data_plotting = True - - # mirror plot, if plotting below diagonal - if kdx == 0: - l1, l2 = len_one, len_two - n1, n2 = name_one, name_two - x1, y1 = x_lists, y_lists - x2, y2 = x_lists_rc, y_lists_rc - else: - l2, l1 = len_one, len_two - n2, n1 = name_one, name_two - x1, y1 = y_lists, x_lists - x2, y2 = y_lists_rc, x_lists_rc - - if mirror_y_axis: - x1, y1, x2, y2 = y1, x1, y2, x2 - n1, n2 = n2, n1 - - if data_plotting: - # collect lines - lines = [] - color_list = [] - for (x_lines, y_lines, col) in [(x2, y2, line_col_rev), (x1, y1, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # plot value provided by customer instead of dotplot - else: - alignment = {'horizontalalignment': 'center', 'verticalalignment': 'center'} - # P.text(0.5, 0.5, custom_value, size='medium', transform=ax.transAxes, **alignment) - P.text(0.5, 0.5, custom_value, size=label_size*1.5, transform=ax.transAxes, **alignment) - # P.text(0.5, 0.5, custom_value, size=label_size*1.5, transform=ax.transAxes, - # horizontalalignment='center', verticalalignment='center', color="black") - - if custom_shading: - # omit diagonal - if idx == jdx: - ax.set_facecolor("white") - # use white background for text fields (top right triangle only [kdx 0]) - elif type(custom_value) != int and type(custom_value) != float and kdx == 0: - ax.set_facecolor("white") - else: - ax.set_facecolor(background_colors[kdx]) - # set background color if lcs shading - elif lcs_shading_bool and background_colors[kdx] != None: - ax.set_facecolor(background_colors[kdx]) - - # set axis limits - # P.xlim(0, l1+1) - if mirror_y_axis: - P.xlim(0, l2+1) - P.ylim(0, l1+1) # rotate y axis (point upwards) - else: - P.xlim(0, l1+1) - P.ylim(l2+1, 0) # rotate y axis (point downwards) - - ## axis labelling - ################## - - # determine axis positions - if x_label_pos_top: - ax.xaxis.tick_top() - ax.xaxis.set_label_position('top') - x_label_bool = fig_pos <= ncols - x_tick_bool = fig_pos > ncols*(ncols-1) - else: - x_label_bool = fig_pos > ncols*(ncols-1) - x_tick_bool = fig_pos <= ncols - - # settings for y labels on right side - if y_label_pos == 0: # right label - ax.yaxis.tick_right() - ax.yaxis.set_label_position("right") - label_dist = 30 - else: - label_dist = 8 - - # x axis labels dependent on plot position/number - if x_label_bool: # x title and labels on top or bottom - P.xlabel(unicode_name(shorten_name(n1, max_len=title_length, title_clip_pos=title_clip_pos)), fontsize=label_size, rotation=x_label_rotation, verticalalignment=xvalign, horizontalalignment=xhalign, fontweight='bold', labelpad=8) # axis naming - if not x_label_rotation in ["horizontal", "vertical"]: - P.setp(ax.get_xticklabels(), fontsize=label_size*.9, rotation="vertical") - else: - P.setp(ax.get_xticklabels(), fontsize=label_size*.9, rotation=x_label_rotation) - elif x_tick_bool and x_label_pos_top: # x ticks on bottom row - ax.xaxis.tick_bottom() # ticks without labels on bottom - P.setp(ax.get_xticklabels(), fontsize=label_size, rotation=x_label_rotation, visible=False) - elif x_tick_bool: # x ticks on top row - ax.xaxis.tick_top() # # ticks without labels on top - P.setp(ax.get_xticklabels(), fontsize=label_size, rotation=x_label_rotation, visible=False) # inner diagrams without labelling - elif idx == jdx and representation != 0: - if not mirror_y_axis and representation == 1: # upper - ax.xaxis.tick_bottom() - elif mirror_y_axis and representation == 2: # lower - ax.xaxis.tick_top() - elif mirror_y_axis and representation == 1: # upper - ax.xaxis.tick_bottom() - elif not mirror_y_axis and representation == 2: # lower - ax.xaxis.tick_top() - P.setp(ax.get_xticklabels(), visible=False) # inner diagrams without labelling - else: # no x ticks on internal rows - ax.axes.get_xaxis().set_visible(False) - - # y axis labels dependent on plot position/number - if fig_pos % ncols == y_label_pos or (ncols == 1 and nrows == 1): # y title and labels in 1st column - P.ylabel(unicode_name(shorten_name(n2, max_len=title_length, title_clip_pos=title_clip_pos)), fontsize=label_size, rotation=y_label_rotation, verticalalignment=yvalign, horizontalalignment=yhalign, fontweight='bold', labelpad=label_dist) - P.setp(ax.get_yticklabels(), fontsize=label_size*.9) # axis naming - elif fig_pos % ncols == 0: # y ticks in last column - ax.yaxis.tick_right() - P.setp(ax.get_yticklabels(), visible=False) # inner diagrams without labelling - elif idx == jdx and representation != 0: - if not mirror_y_axis and representation == 1: # upper - ax.yaxis.tick_left() - elif mirror_y_axis and representation == 2: # lower - ax.yaxis.tick_left() - elif mirror_y_axis and representation == 1: # upper - ax.yaxis.tick_right() - elif not mirror_y_axis and representation == 2: # lower - ax.yaxis.tick_right() - P.setp(ax.get_yticklabels(), visible=False) # inner diagrams without labelling - else: - ax.axes.get_yaxis().set_visible(False) - - if not verbose: - print seq_counter, "done" - log_txt += str(seq_counter) + " done" - else: - print "\n%d done" % seq_counter - log_txt += "\n%d done" % seq_counter - logprint(log_txt, start=False, printing=False) - - if verbose: - try: - logprint(lcs_text, start=False, printing=True) - except: - pass - - # finalize layout - margins & spacing between plots - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - # gs.tight_layout(fig, h_pad=.02, w_pad=.02) # less overlapping tick labels, but also disturbingly large spacing - if y_label_rotation == "horizontal": - if x_label_pos_top: - P.subplots_adjust(hspace=spacing, wspace=spacing, left=0.13, top=0.87) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=spacing, wspace=spacing, left=0.13, bottom=0.13) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=spacing, wspace=spacing) # space between rows - def 0.4 - - # save figure and close instance - fig_name = '%s%s_wordsize%i%s.%s' % (prefix, name_graph, wordsize, suffix, filetype) - P.savefig(fig_name) - P.close() - P.cla() - - - # create figure color legend - if lcs_shading: - if lcs_shading_ref == 1: # percentage of shorter sequence - legend_file_name = legend_figure(colors, lcs_shading_num, unit="%", filetype=filetype, prefix=prefix) - elif lcs_shading_ref == 2: # interval sizes - legend_file_name = legend_figure(colors, lcs_shading_num, unit=aa_bp_unit, filetype=filetype, prefix=prefix, bins=color_bins) - else: # relative of maximum lcs - legend_file_name = legend_figure(colors, lcs_shading_num, unit=aa_bp_unit, filetype=filetype, prefix=prefix, max_len=max_lcs) - - if custom_shading: - custom_prefix = "custom-matrix-" + prefix - legend_file_name_custom = legend_figure(colors_2, lcs_shading_num, unit="%", filetype=filetype, prefix=custom_prefix, max_len=custom_max, min_len=custom_min) - - if lcs_shading and custom_shading: - return [fig_name, legend_file_name, legend_file_name_custom] - elif lcs_shading: - return [fig_name, legend_file_name] - elif custom_shading: - return [fig_name, legend_file_name_custom] - else: - return [fig_name] - - -############################### -# Function Call # -############################### - -def main(seq_list, wordsize, modes=[0, 1, 2], prefix=None, plot_size=10, label_size=10, filetype="png", type_nuc=True, convert_wobbles=False, substitution_count=0, rc_option=True, alphabetic_sorting=False, only_vs_first_seq=False, gff=None, multi=True, ncols=1, nrows=1, lcs_shading=True, lcs_shading_num=5, lcs_shading_ref=0, lcs_shading_interval_len=100, lcs_shading_ori=0, gff_color_config_file="", input_user_matrix_file="", user_matrix_print=False, length_scaling=True, title_length=50, title_clip_pos="B", spacing=0.04, max_N_percentage=49, mirror_y_axis=False, verbose=False): - - global t1, line_col_rev - - # check input variables - if convert_wobbles and max_N_percentage > 49: - max_N_percentage = 49 - if type_nuc: - ambiq_res = "N" - else: - ambiq_res = "X" - text = "Provide valid max_N_percentage, kmers with >50%% %ss are ignored\n" % (ambiq_res) - logprint(text, start=False, printing=True) - - if filetype not in ["png", "pdf", "svg"]: - text = "Provide valid file type - png, pdf, or svg - given:%s\n" % filetype - logprint(text, start=False, printing=True) - filetype = "png" - - # read gff color config file if provided - if len(input_gff_files) != 0 and input_gff_files != None: - if gff_color_config_file not in ["", None]: - text = "\n%s\n\nReading GFF color configuration file\n%s\n\n=> %s\n" % (50*"=", 28*"-", gff_color_config_file) - logprint(text, start=False, printing=True) - gff_feat_colors = read_gff_color_config(gff_color_config_file) - else: - gff_feat_colors = {} - if gff_color_config_file not in ["", None]: - text = "Please provide GFF annotation files to use configuration file", gff_color_config_file - logprint(text, start=False, printing=True) - - # if color is set to white, reverse complementary matches are skipped - if not rc_option: - line_col_rev = "white" # reverse matches not calculated - elif not type_nuc: - logprint("Reverse complement deactivated for proteins!") - line_col_rev = "white" # reverse matches not calculated - - mode_text = [] - for item in modes: - mode_text.append(str(item)) - text = "%s\n\nRunning plotting modes %s" % (50*"=", ", ".join(mode_text)) - logprint(text, start=False, printing=True) - - - # create dotplots - ########################################## - - # self dotplots - t1 = time.time() - if 0 in modes: - list_of_png_names = selfdotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, title_clip_pos=title_clip_pos, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, multi=multi, ncols=ncols, nrows=nrows, gff_files=gff, gff_color_dict=gff_feat_colors, mirror_y_axis=mirror_y_axis, max_N_percentage=max_N_percentage, verbose=verbose) - t1 = time_track(t1) - if list_of_png_names != [] and list_of_png_names != None: - text = "-> Image file(s): %s\n" % ", ".join(list_of_png_names) - else: - text = "No image files were created!\n" - logprint(text, start=False, printing=True) - logprint(50*"=") - - # paired dotplots - if 1 in modes: - if multi: - list_of_png_names = pairdotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, title_clip_pos=title_clip_pos, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, only_vs_first_seq=only_vs_first_seq, multi=multi, ncols=ncols, nrows=nrows, length_scaling=length_scaling, mirror_y_axis=mirror_y_axis, max_N_percentage=max_N_percentage, verbose=verbose) - t1 = time_track(t1) - else: - if not length_scaling: - text = "\nPairwise dotplot with individual output files scaled by sequence length automatically!" - logprint(text, start=False, printing=True) - list_of_png_names = pairdotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, title_clip_pos=title_clip_pos, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, only_vs_first_seq=only_vs_first_seq, multi=multi, ncols=ncols, nrows=nrows, length_scaling=True, mirror_y_axis=mirror_y_axis, max_N_percentage=max_N_percentage, verbose=verbose) - t1 = time_track(t1) - if list_of_png_names != [] and list_of_png_names != None: - text = "-> Image file(s): %s\n" % ", ".join(list_of_png_names) - else: - text = "No image files were created!\n" - logprint(text, start=False, printing=True) - logprint(50*"=") - - # all-against-all dotplot - if 2 in modes: - list_of_png_names = polydotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, title_clip_pos=title_clip_pos, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, lcs_shading=lcs_shading, lcs_shading_num=lcs_shading_num, lcs_shading_ref=lcs_shading_ref, lcs_shading_interval_len=lcs_shading_interval_len, lcs_shading_ori=lcs_shading_ori, input_user_matrix_file=input_user_matrix_file, user_matrix_print=user_matrix_print, spacing=spacing, gff_files=gff, gff_color_dict=gff_feat_colors, mirror_y_axis=mirror_y_axis, max_N_percentage=max_N_percentage, verbose=verbose) - t1 = time_track(t1) - if list_of_png_names != [] and list_of_png_names != None: - text = "-> Image file(s): %s\n" % ", ".join(list_of_png_names) - else: - text = "No image files were created!\n" - logprint(text, start=False, printing=True) - logprint(50*"=") - - text = "\n" + 50 * "#" + "\n" + 50 * "#" - text += "\n\nThank you for using FlexiDot!\n" - logprint(text, start=False, printing=True) - - -load_modules() - -# testing mode for debugging -trial_mode = True -trial_mode = False - -# parameters = check_input(sys.argv) -parameters = check_input(sys.argv, trial_mode=trial_mode) - -# read out parameters -commandline, auto_fas, input_fasta, output_file_prefix, collage_output, m_col, n_row, filetype, type_nuc, input_gff_files, gff_color_config_file, wordsize, plotting_modes, wobble_conversion, substitution_count, rc_option, alphabetic_sorting, only_vs_first_seq, lcs_shading, lcs_shading_num, lcs_shading_ref, lcs_shading_interval_len, lcs_shading_ori, input_user_matrix_file, user_matrix_print, plot_size, line_width, line_col_for, line_col_rev, x_label_pos_top, label_size, spacing, length_scaling, title_length, title_clip_pos, max_N_percentage, mirror_y_axis, representation, verbose = parameters - -# evtl. overwrite parameters for testing purposes in trial mode -if trial_mode: - input_fasta = ["test-sequences-8.fas"] - input_gff_files = ["Seq2_annotations.gff3"] - # input_user_matrix_file = "matrix.txt" - # user_matrix_print = True - output_file_prefix = "#Test" - plot_size = 10 - plotting_modes = [0,1,2] - plotting_modes = [2] - lcs_shading = False - lcs_shading = True - lcs_shading_ref = 2 - lcs_shading_num = 4 - lcs_shading_ori = 0 - lcs_shading_interval_len = 15 - wordsize = 10 - wordsize = 7 - x_label_pos_top = True - filetype = "pdf" - filetype = "png" - mirror_y_axis = False - mirror_y_axis = True - - output_file_prefix = "#R-upper" - representation = 0 # both - representation = 1 # upper - representation = 2 # lower - - wobble_conversion = False - wobble_conversion = True - - substitution_count = 0 - - rc_option = True - rc_option = False - label_size = 10 - - verbose = False - verbose = True - -if auto_fas: - path = os.path.dirname(os.path.abspath(__file__)) - files_long = glob.glob(path+"/*.fasta") - files_long.extend(glob.glob(path+"/*.fas")) - files_long.extend(glob.glob(path+"/*.fa")) - files_long.extend(glob.glob(path+"/*.fna")) - input_fasta = [] - for i in files_long: - if not "combined" in i: - filename = i[i.rfind('\\')+1:] - input_fasta.append(filename) - -if trial_mode: - # start logging file - logprint(commandline, start=True, printing=False, prefix=output_file_prefix) - - - - - -main(input_fasta, wordsize, modes=plotting_modes, prefix=output_file_prefix, plot_size=plot_size, label_size=label_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=wobble_conversion, substitution_count=substitution_count, rc_option=rc_option, alphabetic_sorting=alphabetic_sorting, only_vs_first_seq=only_vs_first_seq, gff=input_gff_files, multi=collage_output, ncols=m_col, nrows=n_row, lcs_shading=lcs_shading, lcs_shading_num=lcs_shading_num, lcs_shading_ref=lcs_shading_ref, lcs_shading_interval_len=lcs_shading_interval_len, lcs_shading_ori=lcs_shading_ori, gff_color_config_file=gff_color_config_file, input_user_matrix_file=input_user_matrix_file, user_matrix_print=user_matrix_print, length_scaling=length_scaling, title_length=title_length, title_clip_pos=title_clip_pos, spacing=spacing, max_N_percentage=max_N_percentage, mirror_y_axis=mirror_y_axis, verbose=verbose) - - diff --git a/code/flexidot_v1.06.py b/code/flexidot_v1.06.py deleted file mode 100644 index cb223c0..0000000 --- a/code/flexidot_v1.06.py +++ /dev/null @@ -1,3403 +0,0 @@ -#!/usr/bin/python2.7 -# -*- coding: utf-8 -*- - -""" -FlexiDot Version 1.06 - -FlexiDot: Highly customizable ambiguity-aware dotplots for visual sequence investigation - -Kathrin M. Seibt, Thomas Schmidt and Tony Heitkam -Institute of Botany, TU Dresden, Dresden, 01277, Germany - -Bioinformatics (2018) Vol. 34 (20), 3575–3577, doi 10.1093/bioinformatics/bty395 -""" - - -############################### -# Requirements # -############################### - -# import system modules -import os, glob -import time, datetime -import sys -import shutil, getopt -import unicodedata - -def module_install_command(module_name, upgrade=False): - """ - create installation commands for Python modules and print information - """ - if upgrade: - load_command = "python -m pip install --upgrade %s" % module_name - else: - load_command = "python -m pip install %s" % module_name - - try: - logprint("Installing Python module: %s\n\t%s\n" % (module_name, load_command)) - except: - print "Installing Python module: %s\n\t%s\n" % (module_name, load_command) - - return load_command - -def load_modules(): - """ - load Python modules, if possible - otherwise try to install them - """ - # make module names global - global cllct, gridspec, patches, rcParams, mplrc, P, Color, SeqIO, np, mcolors, rgb2hex, regex - - # matplotlib - try: - import matplotlib.collections as cllct - except: - command = module_install_command("matplotlib", upgrade=True) - try: - os.system(command) - print "\n" - import matplotlib.collections as cllct - except: - print "Please install module matplotlib manually" - import matplotlib.colors as mcolors - import matplotlib.gridspec as gridspec - import matplotlib.patches as patches - import pylab as P - P.switch_backend('agg') # bugfix for _tkinter.TclError on CentOs 7 servers, see Github Issue #5 - - # specify matplotlib font settings - from matplotlib import rc as mplrc - mplrc('pdf', fonttype=42, compression=0) - from matplotlib import rcParams - rcParams['font.family'] = 'sans-serif' - rcParams['font.sans-serif'] = ['Helvetica', 'Verdana', 'Tahoma' , 'DejaVu Sans', 'Droid Sans Mono', 'Sans', 'Liberation', 'Ubuntu', 'Arial', ] - - # colour for color gradient palette - try: - from colour import Color - except: - command = module_install_command("colour") - try: - os.system(command) - print "\n" - from colour import Color - except: - print "Please install module colour manually" - - # color converter - try: - from colormap import rgb2hex - except: - command = module_install_command("colormap") - # additional module easydev.tools required by colormap - command2 = module_install_command("easydev") - try: - os.system(command) - os.system(command2) - print "\n" - from colormap import rgb2hex - except: - print "Please install module colormap manually" - - # biopython - try: - from Bio import SeqIO - except: - command = module_install_command("biopython") - try: - os.system(command) - print "\n" - from Bio import SeqIO - except: - print "Please install module biopython manually" - - # numpy - try: - import numpy as np - except: - command = module_install_command("numpy") - try: - os.system(command) - print "\n" - import numpy as np - except: - print "Please install module numpy manually" - - # regex for pattern matching - try: - import regex - except: - command = module_install_command("regex") - try: - os.system(command) - print "\n" - import regex - except: - print "Please install module regex manually" - - - -############################### -# Usage & Input # -############################### - -def usage(): - """ - usage and help - """ - - print """\n\n FLEXIDOT - ------------------------------------------------------------------- - - Version: - 1.06 - - Citation: - Kathrin M. Seibt, Thomas Schmidt, Tony Heitkam (2018) - "FlexiDot: Highly customizable ambiguity-aware dotplots for visual sequence investigation" - Bioinformatics 34 (20), 3575–3577, doi: 10.1093/bioinformatics/bty395 - - - General usage: - $ python flexidot.py -a [ARGUMENTS] - $ python flexidot.py -i [ARGUMENTS] - - - ARGUMENTS - ------------------------------------------------------------------- - - - INPUT/OUTPUT OPTIONS... required are [-a] OR [-i] - - -a, --auto_fas Imports all fasta files from current directory (*.fasta, *.fas, *.fa, *.fna) - -i is not needed, if -a is activated - [inactive by default] - - -i, --in_file Input fasta file (fasta file name or comma-separated file list) - > Provide multiple files: Recall -i or provide comma-separated file names - - -o, --output_file_prefix File prefix to be added to the generated filenames [default = NONE] - - -c, --collage_output Multiple dotplots are combined in a collage - Y or 1 = ON [default] - N or 0 = OFF - - -m, --m_col Number of columns per page [default = 4] (only if --collage_output is ON) - - -n, --n_row Number of rows per page [default = 5] (only if --collage_output is ON) - - -f, --filetype Output file format - 0 = PNG [default] - 1 = PDF - 2 = SVG - - -s, --alphabetic_sorting Sort sequences alphabetically according to titles - Y or 1 = ON - N or 0 = OFF [default] - - - CALCULATION PARAMETERS... - - -k, --wordsize Wordsize (kmer length) for dotplot comparison [default = 10] - - -p, --plotting_mode Mode of FlexiDot dotplotting - 0 = self [default] - 1 = paired - 2 = poly (matrix with all-against-all dotplots) - > Run multiple plotting modes: Recall -p or provide comma-separated numbers - - -t, --type_nuc Type of residue is nucleotide - Y or 1 = nucleotide [default] - N or 0 = amino acid - - -w, --wobble_conversion Ambiguity handling for relaxed matching - Y or 1 = ON - N or 0 = OFF [default] - - -S, --substitution_count Number of substitutions (mismatches) allowed per window for relaxed matching - [default = 0] - - -r, --rc_option Find reverse complementary matches (only if type_nuc=y) - Y or 1 = ON [default] - N or 0 = OFF - - -O, --only_vs_first_seq Limit pairwise comparisons to match all sequences to 1st sequence only - (only if --plotting_mode=1) - Y or 1 = ON - N or 0 = OFF [default] - - GRAPHIC FORMATTING... - - -A, --line_width Line width [default = 1] - - -B, --line_col_for Line color [default = black] - - -C, --line_col_rev Reverse line color [default = green] - - -D, --x_label_pos Position of the X-label - Y or 1 = top [default] - N or 0 = bottom - - -E, --label_size Font size [default = 10] - - -F, --spacing Spacing between all-against-all dotplots (only if --plotting_mode=2) - [default = 0.04] - - -L, --length_scaling Scale plot size for pairwise comparison (only if --plotting_mode=1) - Y or 1 = Scaling ON (axes scaled according to sequence length) - N or 0 = Scaling OFF (squared plots) [default] - - -M, --mirror_y_axis Flip y-axis bottom to top (cartesian coordinate system) - Y or 1 = y-axis bottom to top - N or 0 = y-axis top to bottom [default] - - -P, --plot_size Plotsize [default = 10] - - -R, --representation Region of plot to display (only if --plotting_mode=2) - 0 = full [default] - 1 = upper - 2 = lower - - -T, --title_length Limit title length for dotplot comparisons - [default = 20] - Position of selection can be specified by appending a letter (e.g. -T 20E) - B = beginning [default] - E = end - - - GFF SHADING (for -p/--plotting_mode=0 only)... - - -g, --input_gff_files GFF3 file used for markup in self-dotplots - (provide multiple files: Recall -g or provide comma-separated file names) - - -G, --gff_color_config_file Tab-delimited config file for custom gff shading - column 1: feature type - column 2: color - column 3: alpha - column 4: zoom factor (for small regions) - - - LCS SHADING OPTIONS (for -p/--plotting_mode=2 only)... - - -x, --lcs_shading Shade subdotplot based on the length of the longest common substring (LCS) - Y or 1 = ON - N or 0 = OFF [default] - - -X, --lcs_shading_num Number of shading intervals (hues) for LCS (-x) and user matrix shading (-u) - [default = 5] - - -y, --lcs_shading_ref Reference for LCS shading - 0 = maximal LCS length [default] - 1 = maximally possible length (length of shorter sequence in pairwise comparison) - 2 = given interval sizes - DNA [default 100 bp] or proteins [default 10 aa] - see -Y - - -Y, --lcs_shading_interval_len Length of intervals for LCS shading (only if --lcs_shading_ref=2) - [default for nucleotides = 50; default for amino acids = 10] - - -z, --lcs_shading_ori Shade subdotplots according to LCS on - 0 = forward [default], - 1 = reverse, or - 2 = both strands (forward shading above diagonal, reverse shading on diagonal and below; - if using --input_user_matrix_file, best LCS is used below diagonal) - - - CUSTOM USER MATRIX SHADING OPTIONS (for -p/--plotting_mode=2 only)... - - -u, --input_user_matrix_file Shading above diagonal according to values in matrix file specified by the user - (tab-delimited or comma-separated matrix with sequence name in column 1 and numbers in columns 2-n - e.g. identity matrix from multiple sequence alignment - strings are ignored) - - -U, --user_matrix_print Display provided matrix entries in the fields above diagonal of all-against-all dotplot - Y or 1 = ON - N or 0 = OFF [default] - - - OTHERS... - - -h, --help Help screen - - -v, --verbose Verbose - - - - - """ - -def check_input(argv, trial_mode=False): - """ - commandline argument parsing - """ - - global log_txt, aa_bp_unit - - # helpers for argument parsing - ###################################### - - arguments = ["-a", "--auto_fas", "a", "auto_fas", - "-i", "--input_fasta", "i:", "input_fasta=", - "-o", "--output_file_prefix", "o:", "output_file_prefix=", - "-c", "--collage_output", "c:", "collage_output=", - "-m", "--m_col", "m:", "m_col=", - "-n", "--n_row", "n:", "n_row=", - "-f", "--filetype", "f:", "filetype=", - "-t", "--type_nuc", "t:", "type_nuc=", - "-g", "--input_gff_files", "g:", "input_gff_files", - "-G", "--gff_color_config_file", "G:", "gff_color_config_file", - "-k", "--wordsize", "k:", "wordsize=", - "-p", "--plotting_mode", "p:", "plotting_mode=", - "-w", "--wobble_conversion", "w:", "wobble_conversion=", - "-S", "--substitution_count", "S:", "substitution_count=", - "-r", "--rc_option", "r:", "rc_option=", - "-O", "--only_vs_first_seq", "O:", "only_vs_first_seq=", - "-s", "--alphabetic_sorting", "s:", "alphabetic_sorting=", - "-x", "--lcs_shading", "x:", "lcs_shading=", - "-X", "--lcs_shading_num", "X:", "lcs_shading_num=", - "-y", "--lcs_shading_ref", "y:", "lcs_shading_ref=", - "-Y", "--lcs_shading_interval_len", "Y:", "lcs_shading_interval_len=", - "-z", "--lcs_shading_ori", "z:", "lcs_shading_ori=", - "-u", "--input_user_matrix_file", "u:", "input_user_matrix_file=", - "-U", "--user_matrix_print", "U:", "user_matrix_print=", - "-P", "--plot_size", "P:", "plot_size=", - "-A", "--line_width", "A:", "line_width=", - "-B", "--line_col_for", "B:", "line_col_for=", - "-C", "--line_col_rev", "C:", "line_col_rev=", - "-D", "--x_label_pos", "D:", "x_label_pos=", - "-E", "--label_size", "E:", "label_size=", - "-F", "--spacing", "F:", "spacing=", - "-L", "--length_scaling", "L:", "length_scaling=", - "-M", "--mirror_y_axis", "M:", "mirror_y_axis=", - "-R", "--representation", "R:", "representation=", - "-T", "--title_length", "T:", "title_length=", - "-h", "--help", "h", "help", - "-v", "--verbose", "v", "verbose"] - - arguments_sysargv = tuple(arguments[0::4] + arguments[1::4]) - arguments_opts = "".join(arguments[2::4]) - arguments_args = arguments[3::4] - - - # setting defaults - ###################################### - - auto_fas = False # 0 - input_fasta = [] - output_file_prefix = None - collage_output = True # 1 - m_col = 4 - n_row = 5 - filetype = 0 - type_nuc = True - input_gff_files = [] - gff_color_config_file = "" - - wordsize = 10 - plotting_modes = [0] - wobble_conversion = False # 0 - substitution_count = 0 - rc_option = True # 1 - alphabetic_sorting = False # 0 - only_vs_first_seq = False # 0 - - lcs_shading = False # 0 - lcs_shading_num = 4 - lcs_shading_ref = 0 - lcs_shading_interval_len = 50 # interval default changes to "10" for amino acids [type_nuc = n] - lcs_shading_ori = 0 - - input_user_matrix_file = "" - user_matrix_print = False - - plot_size = 10 - line_width = 1 - line_col_for = "black" - line_col_rev = "#009243" - x_label_pos = True # 0 - label_size = 10 - spacing = 0.04 - length_scaling = False # 0 - title_length = 20 # float("Inf") - title_clip_pos = "B" # B (begin), E (end) - max_N_percentage = 49 # fixed value, no user input - mirror_y_axis = False - representation = 0 - - aa_bp_unit = "bp" - - verbose = False # 0 - - filetype_dict = {0: "png", 1: "pdf", 2: "svg"} - lcs_shading_ref_dict = {0: "maximal LCS length", 1: "maximally possible length", 2: "given interval sizes"} - plotting_mode_dict = {0: "self", 1: "paired", 2: "all-against-all"} - lcs_shading_ori_dict = {0: "forward", 1: "reverse complement", 2: "both"} - representation_dict = {0: "full", 1: "upper", 2: "lower"} - - # return default parameters for testing purposes - if trial_mode: - print "ATTENTION: YOU ARE IN THE TRIAL MODE!!!\n\n" - - commandline = "trial_mode\n" - - parameters = [commandline, auto_fas, input_fasta, output_file_prefix, collage_output, m_col, n_row, filetype_dict[filetype], type_nuc, input_gff_files, gff_color_config_file, wordsize, plotting_modes, wobble_conversion, substitution_count, rc_option, alphabetic_sorting, only_vs_first_seq, lcs_shading, lcs_shading_num, lcs_shading_ref, lcs_shading_interval_len, lcs_shading_ori, input_user_matrix_file, user_matrix_print, plot_size, line_width, line_col_for, line_col_rev, x_label_pos, label_size, spacing, length_scaling, title_length, title_clip_pos, max_N_percentage, mirror_y_axis, representation, verbose] - return parameters - - - # read arguments - ###################################### - - commandline = "" - for arg in sys.argv: - commandline += arg + " " - - log_txt = "\n...reading input arguments..." - print log_txt - - if len(sys.argv) < 2: - print "\nERROR: More arguments are needed. Exit..." - log_txt += "\nERROR: More arguments are needed. Exit..." - usage() - sys.exit() - - elif sys.argv[1] not in arguments_sysargv: - print "\nINPUT ERROR: Input argument %s unknown. Please check the help screen." % sys.argv[1] - log_txt += "\nINPUT ERROR: Input argument %s unknown. Please check the help screen." % sys.argv[1] - # usage() - sys.exit() - - try: - opts, args = getopt.getopt(sys.argv[1:], arguments_opts, arguments_args) - - except getopt.GetoptError: - print "\nINPUT ERROR (getopt): Input argument %s unknown. Please check the help screen." % sys.argv[1:] - log_txt += "\nINPUT ERROR (getopt): Input argument %s unknown. Please check the help screen." % sys.argv[1:] - # usage() - sys.exit() - - for opt, arg in opts: - - if opt in ("-h", "--help"): - print "...fetch help screen" - log_txt += "\n...fetch help screen" - usage(), sys.exit() - - if opt in ("-v", "--verbose"): - print "...verbose output" - log_txt += "\n...verbose output" - verbose = True - - elif opt in ("-i", "--input_fasta"): - if "," in arg: - arg_list = arg.split(",") - for temp_file in arg_list: - if not os.path.exists(str(temp_file)): - message = "\nERROR: fasta_file '%s' was not found!" % str(temp_file) - sys.exit(message) - else: - input_fasta.append(str(temp_file)) - print "fasta file #%i: %s" % (len(input_fasta), str(temp_file)) - log_txt += "\nfasta file #%i: %s" % (len(input_fasta), str(temp_file)) - else: - if not os.path.exists(str(arg)): - message = "\nERROR: fasta_file '%s' was not found!" % str(arg) - log_txt += message - sys.exit(message) - else: - input_fasta.append(str(arg)) - print "fasta file #%i: %s" % (len(input_fasta), str(arg)) - log_txt += "\nfasta file #%i: %s" % (len(input_fasta), str(arg)) - - - elif opt in ("-a", "--auto_fas"): - auto_fas = True - - - # multiple gff files: reads them into a list - elif opt in ("-g", "--input_gff_files"): - - # append gff file only if existing - if "," in arg: - arg_list = arg.split(",") - for temp_file in arg_list: - if not os.path.exists(str(temp_file)): - message = "\nERROR: gff_file '%s' was not found!" % str(temp_file) - print message - log_txt += message - print " -->Running FlexiDot without this gff file!" - log_txt += "\n -->Running FlexiDot without this gff file!" - else: - print "GFF file #%i: %s" %(len(input_gff_files), str(temp_file)) - log_txt += "\nGFF file #%i: %s" %(len(input_gff_files), str(temp_file)) - input_gff_files.append(str(temp_file)) - else: - if not os.path.exists(str(arg)): - message = "\nERROR: gff_file '%s' was not found!" % str(arg) - print message - log_txt += message - print " -->Running FlexiDot without this gff file!" - log_txt += "\n -->Running FlexiDot without this gff file!" - else: - input_gff_files.append(str(arg)) - print "GFF file #%i: %s" %(len(input_gff_files), str(arg)) - log_txt += "\nGFF file #%i: %s" %(len(input_gff_files), str(arg)) - - - elif opt in ("-G", "--gff_color_config_file"): - if not os.path.exists(str(arg)): - message = "\nERROR: gff_color_config_file '%s' was not found!" % str(arg) - print message + "\n -->Running FlexiDot with default gff coloring specification!" - log_txt += message + "\n -->Running FlexiDot with default gff coloring specification!" - else: - gff_color_config_file = str(arg) - - - elif opt in ("-u", "--input_user_matrix_file"): - if not os.path.exists(str(arg)): - message = "\nERROR: input_user_matrix_file '%s' was not found!" % str(arg) - print message + "\n -->Running FlexiDot without input_user_matrix_file %s!" % arg - log_txt += message + "\n -->Running FlexiDot withdefault matrix shading file!" - else: - input_user_matrix_file = str(arg) - - elif opt in ("-U", "--user_matrix_print"): - user_matrix_print = check_bools(str(arg), default=user_matrix_print) - - elif opt in ("-o", "--output_file_prefix"): - output_file_prefix = arg - - elif opt in ("-c", "--collage_output"): - collage_output = check_bools(str(arg), default=collage_output) - - elif opt in ("-m", "--m_col"): - try: m_col = int(arg) - except: - print "m_col - invalid argument - using default value" - log_txt += "\nm_col - invalid argument - using default value" - - elif opt in ("-n", "--n_row"): - try: n_row = int(arg) - except: - print "n_row - invalid argument - using default value" - log_txt += "\nn_row - invalid argument - using default value" - - elif opt in ("-f", "--filetype"): - if 0 <= int(arg) <= 2: - filetype = int(arg) - else: - print "\nERROR: Please provide valid filetype argument. %s is out of range. It will be set to -f 0 [default]." %(filetype) - log_txt += "\nERROR: Please provide valid filetype argument. %s is out of range. It will be set to -f 0 [default]." %(filetype) - - elif opt in ("-t", "--type_nuc"): - type_nuc = check_bools(str(arg), default=type_nuc) - - if type_nuc == False: - # interval default changed for amino acids - lcs_shading_interval_len = 10 - aa_bp_unit = "aa" - - elif opt in ("-k", "--wordsize"): - try: wordsize = int(arg) - except: - print "wordsize - invalid argument - using default value" - log_txt += "\nwordsize - invalid argument - using default value" - - elif opt in ("-p", "--plotting_mode"): - if "," in arg: - temp_modes = arg.split(",") - for item in temp_modes: - if item in ["0","1","2"]: - plotting_modes.append(int(item)) - elif arg in ["0","1","2"]: - plotting_modes = [int(arg)] - else: - print "Please provide valid plotting_modes argument - e.g. 1 or 0,1,2 - using default [0]" - log_txt += "\nPlease provide valid plotting_modes argument - e.g. 1 or 0,1,2 - using default [0]" - - elif opt in ("-w", "--wobble_conversion"): - wobble_conversion = check_bools(str(arg), default=wobble_conversion) - - elif opt in ("-S", "--substitution_count"): - try: substitution_count = int(arg) - except: - print "substitution_count - invalid argument - using default value" - log_txt += "\nsubstitution_count - invalid argument - using default value" - - elif opt in ("-r", "--rc_option"): - rc_option = check_bools(str(arg), default=rc_option) - - elif opt in ("-s", "--alphabetic_sorting"): - alphabetic_sorting = check_bools(str(arg), default=alphabetic_sorting) - - elif opt in ("-O", "--only_vs_first_seq"): - only_vs_first_seq = check_bools(str(arg), default=only_vs_first_seq) - - elif opt in ("-x", "--lcs_shading"): - lcs_shading = check_bools(str(arg), default=lcs_shading) - - elif opt in ("-X", "--lcs_shading_num"): - try: lcs_shading_num = int(arg) - 1 - except: - print "lcs_shading_num - invalid argument - using default value" - log_txt += "\nlcs_shading_num - invalid argument - using default value" - - elif opt in ("-y", "--lcs_shading_ref"): - try: - if 0 <= int(arg) <= 2: - lcs_shading_ref = int(arg) - else: - print "\nERROR: lcs_shading_ref %s out of range. It will be set to -y 0 [default]." %(lcs_shading_ref) - log_txt += "\nERROR: lcs_shading_ref %s out of range. It will be set to -y 0 [default]." %(lcs_shading_ref) - except: - print "lcs_shading_ref - invalid argument - using default value" - log_txt += "\nlcs_shading_ref - invalid argument - using default value" - - elif opt in ("-Y", "--lcs_shading_interval_len"): - try: lcs_shading_interval_len = int(arg) - except: - print "lcs_shading_interval_len - invalid argument - using default value" - log_txt += "\nlcs_shading_interval_len - invalid argument - using default value" - - elif opt in ("-z", "--lcs_shading_ori"): - if 0 <= int(arg) <= 2: - lcs_shading_ori = int(arg) - else: - print "\nERROR: Please provide valid lcs_shading_ori argument. %s is out of range. It will be set to -z 0 [default]." %(lcs_shading_ori) - log_txt += "\nERROR: Please provide valid lcs_shading_ori argument. %s is out of range. It will be set to -z 0 [default]." %(lcs_shading_ori) - - elif opt in ("-P", "--plot_size"): - try: plot_size = float(arg) - except: - print "plot_size - invalid argument - using default value" - log_txt += "\nplot_size - invalid argument - using default value" - - - elif opt in ("-A", "--line_width"): - try: line_width = float(arg) - except: - print "line_width - invalid argument - using default value" - log_txt += "\nline_width - invalid argument - using default value" - - elif opt in ("-B", "--line_col_for"): - if mcolors.is_color_like(arg): - line_col_for = arg - else: - print "line_col_for - invalid argument - using default value" - log_txt += "\nline_col_for - invalid argument - using default value" - - elif opt in ("-C", "--line_col_rev"): - if mcolors.is_color_like(arg): - line_col_rev = arg - else: - print "line_col_rev - invalid argument - using default value" - log_txt += "\nline_col_rev - invalid argument - using default value" - - elif opt in ("-D", "--x_label_pos"): - x_label_pos = check_bools(str(arg), default=x_label_pos) - - elif opt in ("-E", "--label_size"): - try: label_size = float(arg) - except: - print "label_size - invalid argument - using default value" - log_txt += "\nlabel_size - invalid argument - using default value" - - elif opt in ("-F", "--spacing"): - try: spacing = float(arg) - except: - print "spacing - invalid argument - using default value" - log_txt += "\nspacing - invalid argument - using default value" - - elif opt in ("-L", "--length_scaling"): - length_scaling = check_bools(str(arg), default=length_scaling) - - elif opt in ("-M", "--mirror_y_axis"): - mirror_y_axis = check_bools(str(arg), default=mirror_y_axis) - - elif opt in ("-R", "--representation"): - if 0 <= int(arg) <= 2: - representation = int(arg) - else: - print "\nERROR: Please provide valid representation argument. %s is out of range. It will be set to -R 0 [default]." %(representation) - log_txt += "\nERROR: Please provide valid representation argument. %s is out of range. It will be set to -R 0 [default]." %(representation) - - elif opt in ("-T", "--title_length"): - try: title_length = int(arg) - except: - try: - title_length = int(str(arg)[:-1]) - if arg[-1].upper() in ["B", "E"]: # B (beginning), E (end) - title_clip_pos = arg[-1].upper() - else: - print "title_length position information invalid - using default value" - log_txt += "\ntitle_length position information invalid - using default value" - except: - print "title_length - invalid argument - using default value" - log_txt += "\ntitle_length - invalid argument - using default value" - - # start logging file - logprint(commandline, start=True, printing=False, prefix=output_file_prefix) - logprint(log_txt, start=False, printing=False) - - - # print chosen arguments - ###################################### - - text = "\n%s\n" % (70 * "-") - text += "\n" + "INPUT/OUTPUT OPTIONS...\n" - text += "\n" + "Input fasta file: " + ", ".join(input_fasta) - text += "\n" + "Automatic fasta collection from current directory: " + str(auto_fas) - text += "\n" + "Collage output: " + str(collage_output) - text += "\n" + "Number of columns per page: " + str(m_col) - text += "\n" + "Number of rows per page: " + str(n_row) - text += "\n" + "File format: " + filetype_dict[filetype] - text += "\n" + "Residue type is nucleotide: " + str(type_nuc) - - text += "\n" + "\n\nCALCULATION PARAMETERS...\n" - text += "\n" + "Wordsize: " + str(wordsize) - text += "\n" + "Sustitution count: " + str(substitution_count) - text += "\n" + "Plotting mode: " + str(plotting_modes).replace("[", "").replace("]", "") + "\n" + 51 * " " - for item in plotting_modes: - text += plotting_mode_dict[item] + " " - text += "\n" + "Ambiguity handling: " + str(wobble_conversion) - text += "\n" + "Reverse complement scanning: " + str(rc_option) - text += "\n" + "Alphabetic sorting: " + str(alphabetic_sorting) - - if 1 in plotting_modes: - text += "\n" + "Only matching sequences to first entry: " + str(only_vs_first_seq) - - if 0 in plotting_modes and input_gff_files != []: - text += "\n" + "Input gff files: " + ", ".join(input_gff_files) - if gff_color_config_file != "": - text += "\n" + "GFF color config file: " + gff_color_config_file - text += "\n" + "Prefix for output files: " + str(output_file_prefix) - - if 2 in plotting_modes: - text += "\n" + "\n\nLCS SHADING OPTIONS (plotting_mode 'all-against-all' only)...\n" - text += "\n" + "LCS shading: " + str(lcs_shading) - text += "\n" + "LCS shading interval number: " + str(lcs_shading_num + 1) - text += "\n" + "LCS shading reference: " + lcs_shading_ref_dict[lcs_shading_ref] - if lcs_shading_ref == 2: - text += "\n" + "LCS shading interval size [%s]: " % (aa_bp_unit) + str(lcs_shading_interval_len) - text += "\n" + "LCS shading orientation: " + lcs_shading_ori_dict[lcs_shading_ori] - if input_user_matrix_file != "": - text += "\n" + "Custom user shading matrix file: " + input_user_matrix_file - text += "\n" + "Print user matrix values (instead of dotplot): " + str(user_matrix_print) - text += "\n" + "Displayed plot region: " + representation_dict[representation] - - text += "\n" + "\n\nGRAPHIC FORMATTING...\n" - text += "\n" + "Plot size: " + str(plot_size) - text += "\n" + "Line width: " + str(line_width) - text += "\n" + "Line color: " + line_col_for - text += "\n" + "Reverse line color: " + line_col_rev - text += "\n" + "X label position: " + str(x_label_pos) - text += "\n" + "Label size: " + str(label_size) - text += "\n" + "Spacing: " + str(spacing) - if mirror_y_axis: - text += "\n" + "Y-axis mirrored (bottom to top) " + str(mirror_y_axis) - if title_clip_pos == "E": - text += "\n" + "Title length (limit number of characters): " + "last" + str(title_length) + "characters" - else: - text += "\n" + "Title length (limit number of characters): " + "first" + str(title_length) + "characters" - text += "\n" + "Length scaling: " + str(length_scaling) - text += "\n%s\n" % (70 * "-") - logprint(text) - - - # collect settings - parameters = [commandline, auto_fas, input_fasta, output_file_prefix, collage_output, m_col, n_row, filetype_dict[filetype], type_nuc, input_gff_files, gff_color_config_file, wordsize, plotting_modes, wobble_conversion, substitution_count, rc_option, alphabetic_sorting, only_vs_first_seq, lcs_shading, lcs_shading_num, lcs_shading_ref, lcs_shading_interval_len, lcs_shading_ori, input_user_matrix_file, user_matrix_print, plot_size, line_width, line_col_for, line_col_rev, x_label_pos, label_size, spacing, length_scaling, title_length, title_clip_pos, max_N_percentage, mirror_y_axis, representation, verbose] - - return parameters - - -############################### -# Helper Functions # -############################### - -def alphabets(type_nuc=True): - """ - provide ambiguity code for sequences - """ - - nucleotide_alphabet = ["A", "C", "G", "T"] - - nucleotide_alphabet_full = ["A", "C", "G", "T", "N", "B", "D", "H", - "V", "Y", "R", "W", "S", "K", "M"] - - nucleotide_ambiguity_code = {"N": ["A", "C", "G", "T"], # any - "B": ["C", "G", "T"], # not A - "D": ["A", "G", "T"], # not C - "H": ["A", "C", "T"], # not G - "V": ["A", "C", "G"], # not T - "Y": ["C", "T"], # pyrimidine - "R": ["A", "G"], # purine - "W": ["A", "T"], # weak - "S": ["C", "G"], # strong - "K": ["G", "T"], # keto - "M": ["A", "C"]} # amino - - nucleotide_match_dict = {"N": "[ACGTNBDHVYRWSKM]", # any - "B": "[CGTNBDHVYRWSKM]", # not A - "D": "[AGTNBDHVYRWSKM]", # not C - "H": "[ACTNBDHVYRWSKM]", # not G - "V": "[ACGNBDHVYRWSKM]", # not T - "K": "[GTNBDHVYRWSK]", # keto - not A,C,M - "M": "[ACNBDHVYRWSM]", # amino - not G,T,K - "W": "[ATNBDHVYRWKM]", # weak - not C,G,S - "S": "[CGNBDHVYRSKM]", # strong - not A,G,W - "Y": "[CTNBDHVYWSKM]", # pyrimidine - not A,G,R - "R": "[AGNBDHVRWSKM]", # purine - not C,T,Y - "A": "[ANDHVRWM]", - "C": "[CNBHVYSM]", - "G": "[GNBDVRSK]", - "T": "[TNBDHYWK]"} - - # nucleotide_match_dict = {"N": ".", # any - # "B": "[^A]", # not A - # "D": "[^C]", # not C - # "H": "[^G]", # not G - # "V": "[^T]", # not T - # "K": "[^ACM]", # keto - not A,C,M - # "M": "[^GTK]", # amino - not G,T,K - # "W": "[^CGS]", # weak - not C,G,S - # "S": "[^AGW]", # strong - not A,G,W - # "Y": "[^AGR]", # pyrimidine - not A,G,R - # "R": "[^CTY]", # purine - not C,T,Y - # "A": "[ANDHVRWM]", - # "C": "[CNBHVYSM]", - # "G": "[GNBDVRSK]", - # "T": "[TNBDHYWK]"} - - aminoacid_alphabet = ["A", "R", "N", "D", "C", "E", "Q", "G", - "H", "I", "L", "K", "M", "F", "P", "S", - "T", "W", "Y", "V", "U", "O", "*"] - - aminoacid_alphabet_full = ["A", "R", "N", "D", "C", "E", "Q", "G", - "H", "I", "L", "K", "M", "F", "P", "S", - "T", "W", "Y", "V", "U", "O", "*", "J", - "Z", "B", "X"] - - aminoacid_ambiguity_code = {"J": ["I", "L"], - "Z": ["Q", "E"], - "B": ["N", "D"], - "X": ["A", "R", "N", "D", "C", "E", "Q", "G", - "H", "I", "L", "K", "M", "F", "P", "S", - "T", "W", "Y", "V", "U", "O", "*"]} # any - - aminoacid_match_dict = {"J": "[ILJ]", - "Z": "[QEZ]", - "B": "[NDB]", - # "X": ".", - "X": "[ARNDCEQGHILKMFPSTWYVUO*XBZJ]", - "A": "[AX]", - "R": "[RX]", - "N": "[NXB]", - "D": "[DXB]", - "C": "[CX]", - "E": "[EXZ]", - "Q": "[QXZ]", - "G": "[GX]", - "H": "[HX]", - "I": "[IXJ]", - "L": "[LXJ]", - "K": "[KX]", - "M": "[MX]", - "F": "[FX]", - "P": "[PX]", - "S": "[SX]", - "T": "[TX]", - "W": "[WX]", - "Y": "[YX]", - "V": "[VX]", - "U": "[UX]", - "O": "[OX]", - "*": "[*X]"} - - aa_only = set(['E', 'F', 'I', 'J', 'L', 'O', 'Q', 'P', 'U', 'X', 'Z', '*']) - # return nucleotide_alphabet, nucleotide_alphabet_full, nucleotide_ambiguity_code, aminoacid_alphabet, aminoacid_alphabet_full, aminoacid_ambiguity_code, aa_only - - if type_nuc: - return nucleotide_alphabet, nucleotide_alphabet_full, nucleotide_ambiguity_code, nucleotide_match_dict - else: - return aminoacid_alphabet, aminoacid_alphabet_full, aminoacid_ambiguity_code, aminoacid_match_dict - -def logprint(text, start=False, printing=True, prefix=""): - """ - log output to log_file and optionally print - """ - - # define log file name and open file - global log_file_name - if start and trial_mode: - log_file_name = "log_file.txt" - if prefix != "" and prefix != None: - if not prefix.endswith("-"): - prefix = prefix + "-" - log_file_name = prefix + log_file_name - log_file = open(log_file_name, 'w') - log_file.write("Date: %s\n\n" % str(datetime.datetime.now())) - elif start: - date = datetime.date.today() - time = str(datetime.datetime.now()).split(" ")[1].split(".")[0].replace(":", "-") - log_file_name = "%s_%s_log_file.txt" % (date, time) - if prefix != "" and prefix != None: - if not prefix.endswith("-"): - prefix = prefix + "-" - log_file_name = prefix + log_file_name - log_file = open(log_file_name, 'w') - log_file.write("Date: %s\n\n" % str(datetime.datetime.now())) - else: - log_file = open(log_file_name, 'a') - - # write log (and print) - log_file.write(text + "\n") - if printing: - print text - log_file.close() - -def time_track(starting_time, show=True): - """ - calculate time passed since last time measurement - """ - now = time.time() - delta = now - starting_time - if show: - text = "\n\t %s seconds\n" % str(delta) - logprint(text, start=False, printing=True) - return now - -def calc_fig_ratio(ncols, nrows, plot_size, verbose=False): - """ - calculate size ratio for given number of columns (ncols) and rows (nrows) - with plot_size as maximum width and length - """ - ratio = ncols*1./nrows - if verbose: - text = " ".join([ncols, nrows, ratio]) - logprint(text, start=False, printing=True) - if ncols >= nrows: - figsize_x = plot_size - figsize_y = plot_size / ratio - else: - figsize_x = plot_size * ratio - figsize_y = plot_size - return figsize_x, figsize_y - -def shorten_name(seq_name, max_len=20, title_clip_pos="B"): #, delim="_"): - """ - shorten sequence names (for diagram titles) - """ - - if len(seq_name) <= max_len: - return seq_name - - # take last characters - if title_clip_pos == "E": - name = seq_name[len(seq_name)-max_len:] - - # take first characters - else: - name = seq_name[:max_len] - - """# keep first and last part if multiple parts separated by delimiter (e.g. species_prefix + sequence_id) - if delim in seq_name: - if seq_name.count(delim) >= 2: - name = "%s..." % delim.join(seq_name.split(delim)[:1]) + seq_name.split(delim)[-1] # .replace("_000", "-") - else: - name = seq_name[:((max_len-2)//2)] + "..." + seq_name[((max_len-2)//2):] - - if len(name) > max_len: - name = name[:((max_len-2)//2)] + "..." + name[((max_len-2)//2):] - else: - name = seq_name[:((max_len-2)//2)] + "..." + seq_name[((max_len-2)//2):] - """ - - return name - -def unicode_name(name): - """ - replace non-ascii characters in string (e.g. for use in matplotlib) - """ - unicode_string = eval('u"%s"' % name) - return unicodedata.normalize('NFKD', unicode_string).encode('ascii','ignore') - -def check_bools(arg, update_log_txt = True, default=None): - """ - converts commandline arguments into boolean - """ - - - # convert valid arguments - if str(arg).lower() == "y" or str(arg) == "1": - return True - elif str(arg).lower() == "n" or str(arg) == "0": - return False - - # use default in case of invalid argument - else: - if update_log_txt: - global log_txt - log_txt += "using default for " + str(arg) - else: - try: - logprint("using default for " + str(arg)) - except: - print "using default for " + str(arg) - return default - -def create_color_list(number, color_map=None, logging=False, max_grey="#595959"): - """ - create color list with given number of entries - grey by default, matplotlib color_map can be provided - """ - - try: - # create pylab colormap - cmap = eval("P.cm." + color_map) - # get descrete color list from pylab - cmaplist = [cmap(i) for i in range(cmap.N)] # extract colors from map - # determine positions for number of colors required - steps = (len(cmaplist)-1)/(number) - numbers = range(0, len(cmaplist), steps) - - # extract color and convert to hex code - colors = [] - for idx in numbers[:-1]: - rgb_color = cmaplist[idx] - col = rgb2hex(rgb_color[0]*255, rgb_color[1]*255, rgb_color[2]*255) - colors.append(col) - - # grey - except: - if not color_map == None: - logprint("Invalid color_map (%s) provided! - Examples: jet, Blues, OrRd, bwr,..." % color_map) - logprint("See https://matplotlib.org/users/colormaps.html\n") - old_max_grey = "#373737" - old_max_grey = "#444444" - colors = list(Color("#FFFFFF").range_to(Color(max_grey), number)) # grey - for idx in range(len(colors)): - colors[idx] = str(colors[idx]).replace("Color ", "") - if "#" in colors[idx] and len(colors[idx]) != 7: - # print colors[idx] - colors[idx] = colors[idx] + colors[idx][-(7-len(colors[idx])):] - - text = "%d Colors: %s" % (len(colors), ", ".join(colors)) - if logging: logprint(text, start=False, printing=True) - - if len(colors) < number: - logprint("\nError in color range definition! %d colors missing\n" % (number - len(colors))) - - return colors - - -############################### -# File Handling # -############################### - -def read_seq(input_fasta, verbose=False): - """ - read fasta sequences from (all) file(s) - """ - - # check if file provided - if input_fasta == [] or input_fasta == "": - text = "Attention: No valid file names provided: >%s<" % input_fasta - logprint(text, start=False, printing=True) - return {}, [] - - # combine sequence files, if required - if type(input_fasta) == list: - # concatenate fasta files - if len(input_fasta) > 1: - if verbose: - print "concatenating fastas...", - text = "concatenating fastas..." - input_fasta_combi = concatenate_files(input_fasta) - if verbose: - print "done" - text += "done" - logprint(text, start=False, printing=False) - else: - input_fasta_combi = input_fasta[0] - else: - input_fasta_combi = input_fasta - - # read sequences - if verbose: - print "reading fasta...", - text = "reading fasta...", - try: - seq_dict = SeqIO.index(input_fasta_combi, "fasta") - except ValueError: - logprint("Error reading fasta sequences - please check input files, e.g. for duplicate names!") - return {}, [] - except: - logprint("Error reading fasta sequences - please check input files!") - return {}, [] - - if verbose: - print "done" - text += "done" - logprint(text, start=False, printing=False) - - for seq in seq_dict: - if "-" in seq_dict[seq].seq: - # ungapped = seq_dict[seq].seq.ungap("-") # cannot be assigned back to sequence record - text = "\nSequences degapped prior Analysis!!!" - logprint(text, start=False, printing=True) - return read_seq(degap_fasta(input_fasta), verbose=verbose) - - # get ordered sequence names - sequences = [] - for item in SeqIO.parse(input_fasta_combi, "fasta"): - sequences.append(item.id) - return seq_dict, sequences - -def read_gff_color_config(gff_color_config_file=""): - """ - define coloring options for gff-based color shading of self-dotplots - """ - - # default aestetics for annotation shading (e.g. if no user config file is provided) - # dictionary with feature_type as key and tuple(color, transparency, zoom) as value - gff_feat_colors = {"orf": ("#b41a31", 0.2, 0), - "orf_rev": ("#ff773b", 0.3, 0), - "gene": ("#b41a31", 0.2, 0), - "cds": ("darkorange", 0.2, 0), - "exon": ("orange", 0.2, 0), - "intron": ("lightgrey", 0.2, 0), - "utr": ("lightblue", 0.2, 0), - "repeat_region": ("green", 0.3, 0), - "repeat": ("green", 0.3, 0), - "tandem_repeat": ("red", 0.3, 0), - "transposable_element": ("blue", 0.3, 0), - "ltr_retrotransposon": ("#cccccc", 0.5, 0), - "ltr-retro": ("#cccccc", 0.5, 0), - "long_terminal_repeat": ("#2dd0f0", 0.75, 2), - "ltr": ("#2dd0f0", 0.75, 2), - "pbs": ("purple", 0.75, 2), - "ppt": ("#17805a", 0.5, 2), - "target_site_duplication": ("red", 0.75, 2), - "misc_feature": ("grey", 0.3, 0), - "misc_feat": ("grey", 0.3, 0), - "misc": ("grey", 0.3, 0), - "others": ("grey", 0.5, 0)} - if gff_color_config_file in ["", None] or not os.path.exists(str(gff_color_config_file)): - return gff_feat_colors - - text = "Updating GFF color configuration with custom specifications\n" - logprint(text, start=False, printing=True) - - # read custom gff_color_config_file - in_file = open(gff_color_config_file, 'rb') - overwritten = set([]) - for line in in_file: - if not line.startswith("#") and len(line.strip().split("\t")) >= 4: - data = line.strip().split("\t") - feat = data[0].lower() - color = data[1].lower() - - # check, if settings are valid - if not mcolors.is_color_like(color): - color = "grey" - text = "Invalid color specified for %s: %s - default grey" % (data[0], data[1]) - logprint(text) - try: - alpha = float(data[2]) - except: - alpha = 0.75 - text = "Invalid alpha specified for %s: %s - default 0.75" % (data[0], data[2]) - logprint(text) - try: - zoom = float(data[3]) - except: - zoom = 0 - text = "Invalid zoom specified for %s: %s - default 0" % (data[0], data[3]) - logprint(text) - - # track changes of predefined settings - if feat in gff_feat_colors.keys(): - overwritten.add(data[0].lower()) - - gff_feat_colors[feat] = (color, alpha, zoom) - in_file.close() - - # default coloring for unknown annotations - if not "others" in gff_feat_colors.keys(): - gff_feat_colors["others"] = ("grey", 0.5, 0) - - if verbose: - # print configuration - text = "\n\nGFF color specification:\n%s\n" % (60 * ".") - for item in sorted(gff_feat_colors.keys()): - text += "%-30s\t%-10s\t%-5s\t%s\n" % (item, str(gff_feat_colors[item][0]), str(gff_feat_colors[item][1]), str(gff_feat_colors[item][2])) - logprint (text, printing=True) - - # print overwritting feature type specifications - if len(overwritten) != 0: - text = "%d feature type specifications overwritten:" % len(overwritten) - text += "\n\t"+ ", ".join(overwritten) + "\n" - logprint(text, start=False, printing=True) - - text = "GFF color specification updated acc. to %s\n\t%s\n\n" % (gff_color_config_file, ", ".join(gff_feat_colors)) - logprint(text, start=False, printing=True) - - return gff_feat_colors - -def read_gffs(input_gff_files, color_dict={"others": ("grey", 1, 0)}, type_nuc=True, prefix="", filetype='png', verbose=False): - """ - create feature dictionary from input_gff - sequence name as key and (feature type, start, stop) as value - """ - if type(input_gff_files) != list: - input_gff_files = [input_gff_files] - - # create dictionary with seq_name as key and (type, start and stop) as value - unknown_feats = set([]) - used_feats = set([]) - feat_dict = {} - for input_gff in input_gff_files: - text = "...reading " + input_gff - logprint(text, start=False, printing=True) - - in_file = open(input_gff, 'rb') - for line in in_file: - if not line.startswith("#") and line.strip() != "": - data = line.strip().split("\t") - feat_type = data[2].lower() - if data[6] == "-": - feat_type += "_rev" - if not feat_type.lower() in color_dict.keys(): - if feat_type.lower().replace("_rev", "") in color_dict.keys(): - feat_type = feat_type.replace("_rev", "") - else: - unknown_feats.add(feat_type) - feat_type = "others" - used_feats.add(feat_type) - if not data[0] in feat_dict.keys(): - feat_dict[data[0]] = [(feat_type, int(data[3]), int(data[4]))] # feature type, start, stop - else: - feat_dict[data[0]].append((feat_type, int(data[3]), int(data[4]))) # feature type, start, stop - if verbose: - text = "\nAnnotations for: %s\n" % ", ".join(feat_dict.keys()[:10]) - if len(feat_dict.keys()) > 10: - text = text[:-1] + ", ...\n" - logprint(text, start=False, printing=True) - in_file.close() - - # print feature types without specific shading settings - if len(unknown_feats) != 0: - text = "Missing shading specification for %d feature type(s):\n\t%s\n" % (len(unknown_feats), ", ".join(sorted(unknown_feats))) - logprint(text, start=False, printing=True) - - # create color legend - colors, alphas = [], [] - for item in sorted(used_feats): - colors.append(color_dict[item][0]) - alphas.append(color_dict[item][1]) - legend_figure(colors=colors, lcs_shading_num=len(used_feats), type_nuc=type_nuc, bins=sorted(used_feats), alphas=alphas, gff_legend=True, prefix=prefix, filetype=filetype) - - # print settings - text = "GFF Feature Types: %s\nGFF Colors: %s" % (", ".join(sorted(used_feats)), ", ".join(sorted(colors))) - logprint(text, start=False, printing=True) - - return feat_dict - -def read_matrix(matrix_file_name, delim="\t", symmetric=True, recursion=False, verbose=False): - input_file = open(matrix_file_name, 'rb') - - # read sequence names from first column - names = [] - for line in input_file: - if not line.startswith("#") and not line.startswith(delim) and delim in line: - names.append(line.strip().split(delim)[0]) - logprint("Delimiter '%s': %d names - %s\n" % (delim, len(names), ", ".join(names))) - - # check if names were found - otherwise try another delimiter - if names == [] and not recursion: - if delim == "\t": - new_delim = "," - else: - new_delim = "\t" - logprint("\nMatrix file not containing data delimited by '%s' - trying to read matrix with delimiter '%s'" % (delim.replace("\t", "\\t"), new_delim)) - info_dict = read_matrix(matrix_file_name, delim=new_delim, symmetric=symmetric, recursion=True, verbose=verbose) - return info_dict - elif names == []: - logprint("Empty matrix file with alternative delimiter!") - return info_dict - input_file.close() - - input_file = open(matrix_file_name, 'rb') - # read matrix entries as values in dictionary with tuple(names) as key - info_dict = {} - contradictory_entries = [] - for line in input_file: - if not line.startswith("#") and not line.startswith(delim) and delim in line: - data = line.strip().split(delim) - for idx in range(len(data[1:])): - # print tuple(sorted([data[0], names[idx]])), data[idx+1] - if symmetric: - key = tuple(sorted([names[idx], data[0]])) - else: - key = tuple(names[idx], data[0]) - if key in info_dict.keys(): - if symmetric and info_dict[key] != data[idx+1] and data[idx+1] not in ["", "-"] and info_dict[key] not in ["", "-"]: - contradictory_entries.append(key) - info_dict[key] = data[idx+1] - input_file.close() - - if len(contradictory_entries) != 0: - try: - logprint("\nContradictory entries in matrix file %s:\n\t%s" % (matrix_file_name, ", ".join(contradictory_entries))) - except: - log_txt = "\nContradictory entries in matrix file %s:\n\t" % (matrix_file_name) - for item in contradictory_entries: - log_txt += str(item).replace("'", "") + ", " - log_txt = log_txt[:-2] - logprint(log_txt) - logprint("Using value from bottom left triangle!") - if verbose: - logprint("\nMatrix information for Sequences named: " % ", ".join(names)) - - return info_dict - -def concatenate_files(file_list, combi_filename="temp_combined.fasta", verbose=False): - """ - concatenate content of all files in file_list into a combined file named combi_filename - """ - out_file = open(combi_filename, 'w') - text = "" - for item in file_list: - if verbose: - text += item + " " - print item, - # read in_file linewise and write to out_file - in_file = open(item, 'rb') - for line in in_file: - out_file.write(line.strip()+"\n") - in_file.close() - out_file.close() - if verbose: - logprint(text, start=False, printing=False) - return combi_filename - -def degap_fasta(input_fasta): - """ - remove gaps from fasta - new degapped sequence file created - """ - - # degap all sequence files - output_fastas = [] - if type(input_fasta) != list: - input_fasta = list(input_fasta) - for input_fas in input_fasta: - output_fas = input_fas[:input_fas.rfind(".")] + "_degapped.fas" - in_file = open(input_fas, 'rb') - out_file = open(output_fas, 'w') - for line in in_file: - if line.startswith(">"): - out_file.write(line.strip()+"\n") - else: - out_file.write(line.strip().replace("-", "")+"\n") - out_file.close() - in_file.close() - output_fastas.append(output_fas) - return output_fastas - -def legend_figure(colors, lcs_shading_num, type_nuc=True, unit="%", filetype="png", max_len=None, min_len=0, bins=[], alphas=[], gff_legend=False, prefix="", verbose=False): - """ - create figure color legend - """ - max_legend_length_row = 8 - max_legend_length_col = 4 - - # define output file - if filetype not in ["png", "pdf", "svg"]: - text = "Provide valid file type - png, pdf, or svg" - logprint(text, start=False, printing=True) - filetype="png" - - # check if length of information fit - if not gff_legend and ((bins != [] and len(colors) != lcs_shading_num+1) or (bins != [] and len(colors) != len(bins)+1)): - if bins != [] and len(colors) != lcs_shading_num+1: - text = "**Attention**\nlcs_shading_num (%d) does not match number of colors (%d)!\n"% (lcs_shading_num, len(bins)) - elif bins != [] and len(colors) != len(bins)+1: - text = "**Attention**\nnumber of LCS length bins (%d) does not match number of colors (%d)!\n" % (len(colors), len(bins)) - logprint(text, start=False, printing=True) - elif gff_legend and len(bins) != len(colors): - text = "**Attention**\nnumber of GFF Feature Types (%d) does not match number of colors (%d)!\n" % (len(colors), len(bins)) - logprint(text, start=False, printing=True) - - # set alpha values to opaque if none are provided - if alphas == []: - for item in colors: - alphas.append(1) - - # legend data points - data_points = range(len(colors)) - if not gff_legend: - - # specify intervals, if max_len provided - if max_len != None: - multi_factor = 100 # one digit - if max_len <= 1: - multi_factor = 1000 # two digits - # len_interval_size = (max_len-min_len) * multi_factor *1. // lcs_shading_num * (1./ multi_factor) - len_interval_size = (max_len-min_len) * 1. / lcs_shading_num - len_pos = [float("%.2f" % (min_len))] - # calculate interval positions - for idx in range(lcs_shading_num): - len_pos.append(float("%.2f" % (len_pos[-1] + len_interval_size))) - - if prefix.startswith("custom-matrix") and (0 <= max_len <= 100 and 0 <= min_len <= 100): - unit = "%" - elif prefix.startswith("custom-matrix"): - unit = "" - - text = "\n%d Legend intervals from %.2f to %.2f: \n\t%s - number: %d, step: %.2f, unit: %s\n" % (lcs_shading_num+1, min_len, max_len, str(len_pos), len(len_pos), len_interval_size, unit) - logprint(text, start=False, printing=True) - pos = len_pos - interval_size = len_interval_size - # generate legend labels acc. to standard interval notation - else: - # use default max_len = 100 and min_len = 0 - len_interval_size = 100. / lcs_shading_num - pos = [float("%.2f" % (0))] - # calculate interval positions - for idx in range(lcs_shading_num): - pos.append(float("%.2f" % (pos[-1] + len_interval_size))) - - # interval_size = 100 // lcs_shading_num - # pos = range(interval_size, 101+interval_size, interval_size) - - # remove unneccessary zeros in decimal places (i.e. if x.x00 in all entries) - while True: - last_digit_all_zero = True - no_delim = False - for idx in range(len(pos)): - # only process if fraction with decimal places - if not "." in str(pos[idx]): - no_delim = True - break - # only process when all entries end in zero - elif str(pos[idx])[-1] != "0": - last_digit_all_zero = False - break - if not last_digit_all_zero or no_delim: - break - # remove last decimal place (== 0) from all entries - else: - temp_pos = pos[:] - for idx in range(len(pos)): - if not str(pos[idx])[-2] == ".": - pos[idx] = float(str(pos[idx])[:-1]) - else: - pos[idx] = int(str(pos[idx])[:-2]) - logprint("Shortening legend entries: %s - %s" % (temp_pos, pos)) - - # eliminate fractions if unit == bp/aa - if unit in ["aa", "bp"]: - for idx in range(len(pos)): - temp_pos = pos[:] - rounded_unit = False - if "." in str(pos[idx]): - rounded_unit = True - # round values up to next integer (keep integer, if not a fraction) - pos[idx] = int(pos[idx] / 1) + int(pos[idx] % 1 > 0) - if idx == len(pos) - 1 and pos[idx] == 101: - pos[idx] = 100 - if rounded_unit: - logprint("Fractions not permitted for unit '%s': %s -> %s" % (unit, temp_pos, pos)) - - if bins != []: # labels provided - legend_labels = bins[:] - legend_labels.append("max") - legend_labels_lengths = [] - for item in bins: - legend_labels_lengths.append("[%d %s, %d %s)" % (item - min(bins), unit, item, unit)) - if len(bins) == len(colors) - 1: - legend_labels_lengths.append("[%d %s, %s]" % (max(bins), unit, u"\u221E")) # infinite - - else: - legend_labels = [] - legend_labels_lengths = [] - for idx in range(len(pos)): - num = pos[idx] - try: - legend_labels.append("[%d%%, %d%%)" % (num - interval_size, num)) - except: - legend_labels.append("[%d%%, %d%%)" % (num - len_interval_size, num)) - if max_len != None: - num = len_pos[idx] - # as int or float - if num == int(num) and int(len_interval_size) == len_interval_size: - legend_labels_lengths.append("[%d %s, %d %s)" % (num, unit, num + len_interval_size, unit)) - else: - legend_labels_lengths.append("[%.2f %s, %.2f %s)" % (num, unit, num + len_interval_size, unit)) - legend_labels[-1] = "100" + unit - if max_len != None: - if num == int(num) and int(len_interval_size) == len_interval_size: - legend_labels_lengths[-1] = u"[%d %s, \u221E]" % (max_len, unit) - else: - legend_labels_lengths[-1] = u"[%.2f %s, \u221E]" % (max_len, unit) - - # set labels and choose file name - if gff_legend: - label_text = bins[:] - edge_col = None - legend_file_name = "GFF_Shading_Legend_n%d." % lcs_shading_num + filetype - elif max_len != None: - label_text = legend_labels_lengths[:] - edge_col = "black" - legend_file_name = "Polydotplot_LCS_Shading_Legend_max%d%s_n%d." % (max_len, unit, lcs_shading_num+1) + filetype - elif bins != []: - label_text = legend_labels_lengths[:] - edge_col = "black" - legend_file_name = "Polydotplot_LCS_Shading_Legend_%d%s_n%d." % (bins[0], unit, lcs_shading_num+1) + filetype - else: - label_text = legend_labels[:] - edge_col = "black" - legend_file_name = "Polydotplot_LCS_Shading_Legend_%%len_n%d." % (lcs_shading_num+1) + filetype - - if prefix != None and prefix != "": - if not prefix.endswith("-"): - prefix = prefix + "-" - legend_type = "LCS" - if prefix.startswith("custom-matrix"): - prefix = prefix.replace("custom-matrix", "")[1:] - legend_type = "CustomMatrix" - legend_file_name = prefix + legend_file_name.replace("LCS", legend_type) - - # plot legend figure - fig, ax = P.subplots(3, 1, figsize=(len(colors)*2, len(colors)*2)) - for idx in range(len(colors)): - ax[0].bar(data_points[idx]+1, data_points[idx]+1, color=colors[idx], label=label_text[idx], - alpha=alphas[idx], edgecolor=edge_col) - ax[1].bar(data_points[idx]+1, 0, color=colors[idx], label=label_text[idx], - alpha=alphas[idx], edgecolor=edge_col) - ax[2].bar(data_points[idx]+1, 0, color=colors[idx], label=label_text[idx], - alpha=alphas[idx], edgecolor=edge_col) - ax[1].set_ylim(0,1) - ax[2].set_ylim(0,1) - ax[1].legend(ncol=((len(colors)-1)//max_legend_length_row)+1, framealpha=1) # vertical legend - col_num = len(colors) - if len(colors) > max_legend_length_col: - remainder = 0 - if len(colors) % max_legend_length_col != 0: - remainder = 1 - row_num = len(colors) // max_legend_length_col + remainder - remainder = 0 - if len(colors) % row_num != 0: - remainder = 1 - col_num = len(colors) // row_num + remainder - ax[2].legend(ncol=col_num, framealpha=1) # horizontal legend - - P.savefig(legend_file_name) - - return legend_file_name - - -############################### -# Analysis Functions # -############################### - -def wobble_replacement(sequence, general_ambiguity_code, verbose=False): - """ - get all degenerated sequences for sequence with ambiguous residues - (only residues considered that are keys in wobble_dictionary) - """ - - # get positions of ambiguous residues - wobble_pos = [] - for idx in range(len(sequence)): - letter = sequence[idx] - if letter in general_ambiguity_code.keys(): - wobble_pos.append(idx) - - if verbose: - text = "\t%d wobbles" % len(wobble_pos) - logprint(text, start=False, printing=True) - - # replace one wobble through each iteration by all possible residues - # repeat if still wobbles in new kmers - kmer_variants = [sequence] - while True: - if verbose: - text = "\t\t%d kmer variants" % len(kmer_variants) - logprint(text, start=False, printing=True) - temp_kmers = set([]) - for kmer in kmer_variants: - for idx in wobble_pos: - letter = kmer[idx] - if letter in general_ambiguity_code.keys(): - for base in general_ambiguity_code[kmer[idx]]: - newkmer = kmer[:idx] + base + kmer[idx+1:] - temp_kmers.add(newkmer) - wobble = False - for kmer in temp_kmers: - for idx in range(len(kmer)): - letter = kmer[idx] - if letter in general_ambiguity_code.keys(): - wobble = True - break - if wobble: - break - kmer_variants = set(list(temp_kmers)[:]) - if not wobble: - break - - return kmer_variants - -def split_diagonals(data, stepsize=1): - """ - split array if point difference exceeds stepsize - data = sorted list of numbers - """ - return np.split(data, np.where(np.diff(data) != stepsize)[0]+1) - -def longest_common_substring(s1, s2): - m = [[0] * (1 + len(s2)) for i in xrange(1 + len(s1))] - longest, x_longest = 0, 0 - for x in xrange(1, 1 + len(s1)): - for y in xrange(1, 1 + len(s2)): - if s1[x - 1] == s2[y - 1]: - m[x][y] = m[x - 1][y - 1] + 1 - if m[x][y] > longest: - longest = m[x][y] - x_longest = x - else: - m[x][y] = 0 - return longest - -def lcs_from_x_values(x_values): - """ - calculate length of longest common substring based on nested list of numbers - """ - if len(x_values) == 0: - return 0 - # get lengths of each subarray data - lengths = np.array([len(i) for i in x_values]) - return max(lengths) - - -############################### -# Matching Functions # -############################### - -def find_match_pos_diag(seq1, seq2, wordsize, report_lcs=False, rc_option=True, convert_wobbles=False, max_N_percentage=49, type_nuc=True, verbose=False): - """ - find all matching positions with matches >= wordsize - convert matching points into lines of the length of the match - (+ optional handling of ambiguities) - """ - global t1 # timer - - # look for Ns in DNA or Xs in proeins (minimum word size) - if type_nuc == True: - any_residue = "N" - else: - any_residue = "X" - - # read sequences - seq_one = seq1.upper(); len_one = len(seq_one) - seq_two = seq2.upper(); len_two = len(seq_two) - - # set ambiguity code for wobble replacement - general_ambiguity_code = alphabets(type_nuc)[2] # nucleotide_ambiguity_code or aminoacid_ambiguity_code - - # forward - ################################# - kmer_pos_dict_one = {}; kmer_pos_dict_two = {} # dictionaries for both sequences - - # reverse complement - ################################# - kmer_pos_dict_three = {}; kmer_pos_dict_four = {} # dictionaries for both sequences - - # create dictionaries with kmers (wordsize) and there position(s) in the sequence - if rc_option: - data_list = [(str(seq_one), kmer_pos_dict_one), - (str(seq_two), kmer_pos_dict_two), - (str(seq_one), kmer_pos_dict_three), - (str(seq_two.reverse_complement()), kmer_pos_dict_four)] - else: - data_list = [(str(seq_one), kmer_pos_dict_one), - (str(seq_two), kmer_pos_dict_two)] - for (seq, kmer_pos_dict) in data_list: - for i in range(len(seq)-wordsize+1): - kmer = seq[i:i+wordsize] - # discard kmer, if too many Ns included - if kmer.count(any_residue)*100./wordsize <= max_N_percentage: - if not convert_wobbles: - try: - kmer_pos_dict[kmer].append(i) - except KeyError: - kmer_pos_dict[kmer] = [i] - else: - wobbles = False - for item in general_ambiguity_code.keys(): - if item in kmer: - wobbles = True - break - if not wobbles: - try: - kmer_pos_dict[kmer].append(i) - except KeyError: - kmer_pos_dict[kmer] = [i] - else: - kmer_variants = wobble_replacement(kmer, general_ambiguity_code) - for new_kmer in kmer_variants: - # print "\t", new_kmer - try: - kmer_pos_dict[new_kmer].append(i) - except KeyError: - kmer_pos_dict[new_kmer] = [i] - - # find kmers shared between both sequences - matches_for = set(kmer_pos_dict_one).intersection(kmer_pos_dict_two) # forward - matches_rc = set(kmer_pos_dict_three).intersection(kmer_pos_dict_four) # reverse complement - - if verbose: - text = "[matches: %i for; %.i rc]" % (len(matches_for), len(matches_rc)) - logprint(text, start=False, printing=True) - - # create lists of x and y co-ordinates for scatter plot - # keep all coordinates of all shared kmers (may match multiple times) - diag_dict_for = {} - diag_dict_rc = {} - for (match_list, pos_dict1, pos_dict2, diag_dict) in [(matches_for, kmer_pos_dict_one, kmer_pos_dict_two, diag_dict_for), - (matches_rc, kmer_pos_dict_three, kmer_pos_dict_four, diag_dict_rc)]: - for kmer in match_list: - for i in pos_dict1[kmer]: - for j in pos_dict2[kmer]: - diag = i-j - points = set(range(i+1, i+wordsize+1)) - if not diag in diag_dict.keys(): - diag_dict[diag] = points - else: - diag_dict[diag].update(points) - - # convert coordinate points to line start and stop positions - x1 = [] # x values reverse - y1 = [] # y values forward - for diag in diag_dict_for.keys(): - x_values = np.array(sorted(diag_dict_for[diag])) - x1.extend(split_diagonals(x_values)) - y_values = split_diagonals(x_values - diag) - y1.extend(y_values) - - x2 = [] # x values rc - y2 = [] # y values rc - if rc_option: - for diag in diag_dict_rc.keys(): - factor = len_two + diag + 1 - x_values = np.array(sorted(diag_dict_rc[diag])) - x2.extend(split_diagonals(x_values)) - y_values = split_diagonals(factor - x_values, -1) - y2.extend(y_values) - - if verbose: - t1 = time_track(t1) - - if not report_lcs: - return np.array(x1), np.array(y1), np.array(x2), np.array(y2) - else: - # get length of longest common substring based on match lengths - lcs_for = lcs_from_x_values(x1) - lcs_rev = lcs_from_x_values(x2) - return np.array(x1), np.array(y1), np.array(x2), np.array(y2), lcs_for, lcs_rev - -def find_match_pos_regex(seq1, seq2, wordsize, substitution_count=0, report_lcs=False, rc_option=True, convert_wobbles=False, max_N_percentage=49, type_nuc=True, verbose=False): - """ - find all matching positions with matches >= wordsize via regular expression search - fuzzy matching - allow up to substitution_count substitutions - convert matching points into lines of the length of the match - (+ optional handling of ambiguities) - """ - global t1 # timer - - # read sequences - seq_one = seq1.upper(); len_one = len(seq_one) - seq_two = seq2.upper(); len_two = len(seq_two) - - # set ambiguity code for wobble replacement - general_ambiguity_code = alphabets(type_nuc)[2] # nucleotide_ambiguity_code or aminoacid_ambiguity_code - ambiguity_match_dict = alphabets(type_nuc)[3] - - ambiq_residues = "[%s]" % "".join(general_ambiguity_code.keys()) - - # look for Ns in DNA or Xs in proeins (minimum word size) - if type_nuc == True: - any_residue = "N" - else: - any_residue = "X" - - # check for wobble presence - if not (regex.search(ambiq_residues, str(seq_one)) == None and regex.search(ambiq_residues, str(seq_two)) == None): - wobble_found = True - else: - wobble_found = False - - # dictionary for matches - diag_dict_for = {} - diag_dict_rc = {} - counter = [0, 0] - - # one-way matching - if rc_option: - data_list = [(str(seq_one), str(seq_two), diag_dict_for, 0), - (str(seq_one), str(seq_two.reverse_complement()), diag_dict_rc, 1)] - else: - data_list = [(str(seq_one), str(seq_two), diag_dict_for, 0)] - - for seq_query, seq_target, diag_dict, counter_pos in data_list: - # split query sequence into kmers - if not rc_option and counter_pos == 1: - break - - for idx in range(len(str(seq_query))-wordsize+1): - kmer = str(seq_query)[idx:idx+wordsize] - - # skip excessive N/X stretches (big black areas) - if kmer.count(any_residue)*100./wordsize <= max_N_percentage: - # convert kmer to regular expression for wobble_matching - if convert_wobbles and wobble_found: - kmer_string = "" - # replace each residue with matching residues or wobbles - for jdx in range(len(kmer)): - kmer_string += ambiguity_match_dict[kmer[jdx]] - else: - kmer_string = kmer - - # convert to regular expression tolerating substitution errors - if type(substitution_count) == int and substitution_count != 0: - kmer_string = "(%s){s<=%d}" % (kmer_string, substitution_count) - - # search for regular expression in target sequence - kdx = 0 - start = True - if regex.search(kmer_string, seq_target[kdx:]) != None: - counter[counter_pos] += 1 - while regex.search(kmer_string, seq_target[kdx:]) != None: - # search for regular expression pattern in target sequence - result = regex.search(kmer_string, seq_target[kdx:]) - - kmer2 = seq_target[kdx:][result.start():result.end()] - - # skip excessive N/X stretches (big black areas) - if kmer2.count(any_residue)*100./wordsize <= max_N_percentage: - diag = idx-(kdx+result.start()) - points = set(range(idx+1, idx+wordsize+1)) - if not diag in diag_dict.keys(): - diag_dict[diag] = points - else: - diag_dict[diag].update(points) - - kdx += result.start() + 1 - if kdx >= len(seq_target): - break - elif regex.search(kmer_string, seq_target[kdx:]) != None: - counter[counter_pos] += 1 - - if verbose: - text = "%5.i \tforward matches" % counter[0] - text += "\n%5.i \treverse complementary matches" % counter[1] - logprint(text, start=False, printing=True) - - # convert coordinate points to line start and stop positions - x1 = [] # x values reverse - y1 = [] # y values forward - for diag in diag_dict_for.keys(): - x_values = np.array(sorted(diag_dict_for[diag])) - x1.extend(split_diagonals(x_values)) - y_values = split_diagonals(x_values - diag) - y1.extend(y_values) - - x2 = [] # x values rc - y2 = [] # y values rc - if rc_option: - for diag in diag_dict_rc.keys(): - factor = len_two + diag + 1 - x_values = np.array(sorted(diag_dict_rc[diag])) - x2.extend(split_diagonals(x_values)) - y_values = split_diagonals(factor - x_values, -1) - y2.extend(y_values) - - if verbose: - t1 = time_track(t1) - - if not report_lcs: - return np.array(x1), np.array(y1), np.array(x2), np.array(y2) - else: - # get length of longest common substring based on match lengths - lcs_for = lcs_from_x_values(x1) - lcs_rev = lcs_from_x_values(x2) - return np.array(x1), np.array(y1), np.array(x2), np.array(y2), lcs_for, lcs_rev - - -############################### -# Dot Plot Functions # -############################### - -def selfdotplot(input_fasta, wordsize, prefix=None, plot_size=10, label_size=10, filetype='png', type_nuc=True, convert_wobbles=False, substitution_count=0, alphabetic_sorting=False, mirror_y_axis=False, title_length=float("Inf"), title_clip_pos="B", max_N_percentage=49, verbose=False, multi=True, ncols=4, nrows=5, gff_files=[], gff_color_dict={"others": ("grey", 1, 0)}): - """ - self-against-self dotplot - partially from biopython cookbook - """ - - # read sequences - seq_dict, sequences = read_seq(input_fasta) - if seq_dict == {}: - logprint("\nFailed to load sequences") - return [] - - if alphabetic_sorting: - sequences = sorted(sequences) - - # check if at least one input sequence - if len(sequences) == 0: - text = "\n%s\n\nCreating %s selfdotplot images\n%s\n\n=>" % (50*"=", len(sequences), 28*"-") - text += " No sequences provided for selfdotplot!\n\nTerminating polydotplot!" - logprint(text, start=False, printing=True) - return - elif len(sequences) == 1 and multi: - text = "\n\nCreating collage output for single selfdotplot!" - text += "\nRecommendation: Change to individual mode by using '--collage_output n'!\n\n" - logprint(text, start=False, printing=True) - - if multi and (ncols == 0 or nrows == 0): - ncols = max(ncols, 1) - nrows = max(nrows, 1) - text = "\n\nSelfdotplot Collage: Invalid collage - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - if multi and ncols > len(sequences): - ncols = len(sequences) - nrows = 1 - text = "\n\nSelfdotplot Collage: Few sequences - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - elif multi and ncols*(nrows-1) > len(sequences): - nrows = ((len(sequences)-1) // ncols) + 1 - text = "\n\nSelfdotplot Collage: Few sequences - correcting number of rows:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - if multi and not (nrows == 1 and ncols == 1) and plot_size <= label_size/2: - label_size = plot_size * 3 // 2 - text = "Reducing label size for better visualization to %d\n" % label_size - logprint(text, start=False, printing=True) - - # read gff annotation data if provided for shading - if gff_files != None and gff_files != []: - text = "\n%s\n\nReading %s GFF annotation files\n%s\n\n=> %s\n" % (50*"=", len(gff_files), 28*"-", ", ".join(gff_files)) - logprint(text, start=False, printing=True) - if prefix != None and prefix != "": - legend_prefix = prefix + "-Selfdotplot" - else: legend_prefix = "Selfdotplot" - feat_dict = read_gffs(gff_files, color_dict=gff_color_dict, type_nuc=type_nuc, prefix=legend_prefix, filetype=filetype, verbose=verbose) - - global t1 - - print "\n%s\n\nCreating %s selfdotplot images\n%s\n\n=>" % (50*"=", len(sequences), 28*"-"), - log_txt = "\n%s\n\nCreating %s selfdotplot images\n%s\n\n=>" % (50*"=", len(sequences), 28*"-") - - # preparations for file name - name_graph = "Selfdotplots" - if prefix != None: - if not prefix[-1] == "-": - prefix = prefix + "-" - else: - prefix = "" - suffix = "" - if convert_wobbles: - suffix += "_wobbles" - if substitution_count != 0: - suffix += "_S%d" % substitution_count - if multi: - suffix += "_collage" - - # calculate fig ratios - if not multi: - ncols = 1 - nrows = 1 - figsize_x, figsize_y = calc_fig_ratio(ncols, nrows, plot_size) - - P.cla() # clear any prior graph - if multi: - fig = P.figure(figsize=(figsize_x, figsize_y)) - page_counter = 1 - list_of_png_names = [] - - counter = 0 - for seq_name in sequences: - print seq_name, - log_txt += " " + seq_name - - counter += 1 - if not multi: - P.cla() # clear any prior graph - - # read sequence - seq_record = seq_dict[seq_name] - name_seq = seq_record.id - seq_one = seq_record.seq.upper() - length_seq = len(seq_one) - - # get positions of matches - if substitution_count != 0: - # print "RE" - x_lists, y_lists, x_lists_rc, y_lists_rc = find_match_pos_regex(seq_one, seq_one, wordsize, substitution_count=substitution_count, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, type_nuc=type_nuc, verbose=verbose) - else: - # print "DIAG", - x_lists, y_lists, x_lists_rc, y_lists_rc = find_match_pos_diag(seq_one, seq_one, wordsize, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, type_nuc=type_nuc, verbose=verbose) - - # plotting with matplotlib - ################################# - - # combined plotting - if multi: - # plotting subplot with matplotlib - ax = P.subplot(nrows, ncols, counter) # rows, columns, plotnumber - - # shade annotated regions - if gff_files != None and gff_files != []: - if seq_name in feat_dict.keys(): - features = feat_dict[seq_name] - for item in features: - feat_type, start, stop = item - feat_color, strength, zoom = gff_color_dict[feat_type.lower()] - start = max(0, start - zoom - 0.5) - stop = min(length_seq+1, stop + zoom + 0.5) - width = stop - start - ax.add_patch(patches.Rectangle((start, start), # (x,y) - width, width, # width, height - edgecolor=None, linewidth=line_width+zoom, - fill=True, facecolor=feat_color, - alpha=strength)) - - # collect lines - lines = [] - color_list = [] - for (x_lines, y_lines, col) in [(x_lists_rc, y_lists_rc, line_col_rev), (x_lists, y_lists, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # format axes - # print P.xticks()[0], P.yticks()[0] - P.axis('scaled') # make images quadratic - P.xlim(0, length_seq+1) - if mirror_y_axis: - P.ylim(0, length_seq+1) # rotate y axis (point upwards) - else: - P.ylim(length_seq+1, 0) # rotate y axis (point downwards) - P.xlabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.ylabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - - # # use same tick labels for x and y axis - # tick_locs, tick_labels = P.yticks() - # P.xticks(tick_locs) - # P.xlim(0, length_seq+1) - - P.title(unicode_name(shorten_name(name_seq, max_len=title_length, title_clip_pos=title_clip_pos)), fontsize=label_size, fontweight='bold') - # P.title(unicode_name(name_seq), fontsize=label_size*1.3, fontweight='bold') - - # save figure and reinitiate if page is full - if counter == ncols * nrows: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - P.subplots_adjust(hspace=0.5, wspace=0.5) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' % (prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() - - list_of_png_names.append(fig_name) - - counter = 0 - page_counter += 1 - - fig = P.figure(figsize=(figsize_x, figsize_y)) - - # plotting separate figure files - else: # not multi - - fig = P.figure(figsize=(plot_size, plot_size)) # figure size needs to be a square - ax = P.subplot(1, 1, 1) # rows, columns, plotnumber - - # shade annotated regions - if gff_files != None and gff_files != []: - if seq_name in feat_dict.keys(): - features = feat_dict[seq_name] - for item in features: - feat_type, start, stop = item - feat_color, strength, zoom = gff_color_dict[feat_type.lower()] - start = max(0, start - zoom - 0.5) - stop = min(length_seq+1, stop + zoom + 0.5) - width = stop - start - ax.add_patch(patches.Rectangle((start, start), # (x,y) - width, width, # width, height - edgecolor=None, linewidth=line_width+zoom, - fill=True, facecolor=feat_color, - alpha=strength)) - - # collect lines - lines = [] - number = 0 - color_list = [] - for (x_lines, y_lines, col) in [(x_lists_rc, y_lists_rc, line_col_rev), (x_lists, y_lists, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # format axes - P.axis('scaled') # make images quadratic - P.xlim(0, length_seq+1) - if mirror_y_axis: - P.ylim(0, length_seq+1) # rotate y axis (point upwards) - else: - P.ylim(length_seq+1, 0) # rotate y axis (point downwards) - P.xlabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.ylabel("[%s]" % aa_bp_unit, fontsize=label_size) - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - - # # use same tick labels for x and y axis - # tick_locs, tick_labels = P.yticks() - # P.xticks(tick_locs) - # P.xlim(0, length_seq+1) - - P.title(unicode_name(shorten_name(name_seq, max_len=title_length, title_clip_pos=title_clip_pos)), fontsize=label_size*1.3, fontweight='bold') - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s-%d_%s_wordsize%i%s.%s' %(prefix, name_graph, counter, shorten_name(name_seq, max_len=title_length, title_clip_pos=title_clip_pos), wordsize, suffix, filetype) - P.savefig(fig_name, bbox_inches='tight') - - P.close() - P.cla() # clear any prior graph - - list_of_png_names.append(fig_name) - - if multi and counter >= 1: - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - P.subplots_adjust(hspace=0.5, wspace=0.5) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' %(prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() # clear any prior graph - - list_of_png_names.append(fig_name) - - print "\n\nDrawing selfdotplots done" - log_txt += "\n\nDrawing selfdotplots done" - logprint(log_txt, start=False, printing=False) - - return list_of_png_names - -def pairdotplot(input_fasta, wordsize, prefix=None, plot_size=10, label_size=10, filetype='png', type_nuc=True, convert_wobbles=False, substitution_count=0, alphabetic_sorting=False, mirror_y_axis=False, title_length=float("Inf"), title_clip_pos="B", max_N_percentage=49, verbose=False, multi=True, ncols=4, nrows=5, x_label_pos_top=True, only_vs_first_seq=False, length_scaling=True, scale_delim_col="red"): - """ - pairwise dotplot (all-against-all) - """ - - # read sequences - seq_dict, sequences = read_seq(input_fasta) - if seq_dict == {}: - logprint("\nFailed to load sequences") - return [] - - if alphabetic_sorting: - sequences = sorted(sequences) - - # check if at least two input sequences - if len(sequences) < 2: - text = "\n%s\n\nCreating %d paired dotplot image \n%s\n\n=>" % (50*"=", len(sequences)*(len(sequences)-1)/2, 36*"-") - text += " Please provide at least two sequences for pairdotplot!\n\nTerminating paired dotplot!" - logprint(text, start=False, printing=True) - return - elif len(sequences) == 2 and multi: - text = "\n\nCreating collage output for single pairdotplot!" - text += "\nRecommendation: Change to individual mode by using '--collage_output n'!\n\n" - logprint(text, start=False, printing=True) - - if multi and (ncols == 0 or nrows == 0): - ncols = max(ncols, 1) - nrows = max(nrows, 1) - text = "\n\nPairdotplot Collage: Invalid collage settings - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - if multi and ncols > len(sequences)*(len(sequences)-1): - ncols = len(sequences) - nrows = 1 - text = "\n\nPairdotplot Collage: Few sequences - correcting number of rows and columns:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - elif multi and ncols*(nrows-1) > len(sequences)*(len(sequences)-1): - nrows = ((len(sequences)-1) // ncols) + 1 - text = "\n\nPairdotplot Collage: Few sequences - correcting number of rows:\n\tncols=%d, nrows=%d\n" % (ncols, nrows) - logprint(text, start=False, printing=True) - - if not only_vs_first_seq: - text = "\n%s\n\nCreating %d paired dotplot image for\n%s\n\n=>" % (50*"=", len(sequences)*(len(sequences)-1)/2, 36*"-") - text += ", ".join(sequences) + "\n" - else: - text = "\n%s\n\nCreating %d paired dotplot images against 1st sequence '%s':\n%s\n\n=>" % (50*"=", len(sequences)-1, sequences[0], 36*"-") - text += ", ".join(sequences[1:]) + "\n" - logprint(text, start=False, printing=True) - - if multi and not (nrows == 1 and ncols == 1) and plot_size <= label_size/2: - label_size = plot_size * 3 // 2 - text = "Reducing label size for better visualization to %d\n" % label_size - logprint(text, start=False, printing=True) - - y_label_rotation = "vertical" - # for cartesian coordinate system with mirrored y-axis: plot x labels below plot - if mirror_y_axis: - x_label_pos_top = False - - # preparations for file name - name_graph = "Pairdotplot" - if prefix != None: - if not prefix[-1] == "-": - prefix = prefix + "-" - else: - prefix = "" - suffix = "" - if convert_wobbles: - suffix += "_wobbles" - if substitution_count != 0: - suffix += "_S%d" % substitution_count - if length_scaling: - suffix += "_scaled" - if multi: - suffix += "_collage" - - # calculate fig ratios - if not multi: - ncols = 1 - nrows = 1 - figsize_x, figsize_y = calc_fig_ratio(ncols, nrows, plot_size) - - P.cla() # clear any prior graph - list_of_png_names = [] - if multi: - fig = P.figure(figsize=(figsize_x, figsize_y)) - page_counter = 1 - - # prepare LCS data file - lcs_data_file = open("%sPairdotplot_wordsize%d_lcs_data_file%s.txt" % (prefix, wordsize, suffix.replace("_scaled", "").replace("_collage", "")), 'w') - lcs_data_file.write("\t".join(["#title1", "title2", "len_seq1", "len_seq2", "len_lcs_for", "%_min_seq_len", "len_lcs_rev", "%_min_seq_len"])+"\n") - - counter, seq_counter = 0, 0 - print "Drawing pairwise dotplot...", - log_txt = "Drawing pairwise dotplot..." - if verbose: - seq_text = "" - for idx in range(len(sequences)-1): - if verbose: - print "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]), - seq_text += "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]) - rec_two = seq_dict[sequences[idx]] - name_two = rec_two.id - seq_two = rec_two.seq - len_two = len(seq_two) - - for jdx in range(idx+1, len(sequences)): - rec_one = seq_dict[sequences[jdx]] - name_one = rec_one.id - seq_one = rec_one.seq - len_one = len(seq_one) - - counter += 1 - seq_counter += 1 - if verbose: - print sequences[jdx], - seq_text += " " + sequences[jdx] - elif not seq_counter % 25: - print seq_counter, - log_txt += " " + str(seq_counter) - - # get positions of matches - if substitution_count != 0: - # print "RE" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_regex(seq_one, seq_two, wordsize, substitution_count=substitution_count, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - else: - # print "DIAG" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_diag(seq_one, seq_two, wordsize, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - - # write LCS data file - lcs_data_file.write("\t".join([name_one, name_two, str(len_one), str(len_two), - str(lcs_for), str(round((lcs_for*100./min(len_one, len_two)), 3)), - str(lcs_rev), str(round((lcs_rev*100./min(len_one, len_two)), 3))]) + "\n") - - - # plotting with matplotlib - ################################# - - # combined plotting - if multi: - # plotting subplot with matplotlib - ax = P.subplot(nrows, ncols, counter) # rows, columns, plotnumber - - else: - # calculate figure size for separate figures - if len_one >= len_two: - sizing = (plot_size, max(2, (plot_size)*len_two*1./len_one)) - # sizing = (plot_size, min(plot_size, max(2, (plot_size-2)*len_two*1./len_one+2))) - else: - sizing = (max(2, (plot_size)*len_one*1./len_two), plot_size) - # sizing = (min(plot_size, max(2, (plot_size-2)*len_one*1./len_two+2)), plot_size) - fig = P.figure(figsize=(plot_size, plot_size)) - - ax = P.subplot(1, 1, 1) - - # collect lines - lines = [] - color_list = [] - for (x_lines, y_lines, col) in [(x2, y2, line_col_rev), (x1, y1, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # format axes - P.xlabel(unicode_name(shorten_name(name_one, max_len=title_length, title_clip_pos=title_clip_pos)) + " [%s]" % aa_bp_unit, fontsize=label_size, fontweight='bold', labelpad=4) - P.ylabel(unicode_name(shorten_name(name_two, max_len=title_length, title_clip_pos=title_clip_pos)) + " [%s]" % aa_bp_unit, fontsize=label_size, fontweight='bold', labelpad=4) - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - - # P.axis('scaled') # make images scaled by size ### optional update ### - if not multi: - if length_scaling: - ax.set_aspect(aspect='equal', adjustable='box', anchor='NW') - P.xlim(0, len_one+1) - # xlimit = [0, len_one+1] - if mirror_y_axis: - P.ylim(0, len_two+1) # rotate y axis (point upwards) - else: - P.ylim(len_two+1, 0) # rotate y axis (point downwards) - elif not length_scaling: - P.xlim(0, len_one+1) - # xlimit = [0, len_one+1] - if mirror_y_axis: - P.ylim(0, len_two+1) # rotate y axis (point upwards) - else: - P.ylim(len_two+1, 0) # rotate y axis (point downwards) - else: - max_len = max(len_one, len_two) - P.xlim(0, max_len+1) - # xlimit = [0, max_len+1] - if mirror_y_axis: - P.ylim(0, max_len+1) # rotate y axis (point upwards) - else: - P.ylim(max_len+1, 0) # rotate y axis (point downwards) - - # plot line deliminating shorter sequence - if max_len != len_one: - ax.plot((len_one+1, len_one+1), (0, len_two), marker="", linestyle="--", color=scale_delim_col, markerfacecolor="r") - if max_len != len_two: - ax.plot((0, len_one), (len_two+1, len_two+1), marker="", linestyle="--", color=scale_delim_col, markerfacecolor="r") - - # # use same tick labels for x and y axis - # if P.xlim() == P.ylim(): - # tick_locs, tick_labels = P.yticks() - # P.xticks(tick_locs) - # P.xlim(xlimit) - - # evtl. switch x axis position - if x_label_pos_top: - ax.xaxis.tick_top() - ax.xaxis.set_label_position('top') - P.setp(ax.get_xticklabels(), fontsize=label_size*.9) - P.setp(ax.get_yticklabels(), fontsize=label_size*.9) - - # save figure and reinitiate if page is full - if multi and counter == ncols * nrows: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - if x_label_pos_top: - P.subplots_adjust(hspace=.5, wspace=.5, top=0.95) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=.5, wspace=.5, bottom=0.05) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' %(prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() - - list_of_png_names.append(fig_name) - - counter = 0 - page_counter += 1 - - fig = P.figure(figsize=(figsize_x, figsize_y)) - - # plotting separate figure files - elif not multi: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - if y_label_rotation == "horizontal": - if x_label_pos_top: - P.subplots_adjust(hspace=0.02, wspace=0.02, left=0.13, top=0.95) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=0.02, wspace=0.02, left=0.13, bottom=0.05) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=0.02, wspace=0.02) # space between rows - def 0.4 - - # name and create output files - fig_name = '%s%s-%d_wordsize%i%s.%s' % (prefix, name_graph, counter, wordsize, suffix, filetype) - P.savefig(fig_name) - P.close() - P.cla() - - list_of_png_names.append(fig_name) - fig = P.figure() - - if only_vs_first_seq: - break - - # save figure - if multi and counter >= 1: - - # finalize layout - margins & spacing between plots - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - if x_label_pos_top: - P.subplots_adjust(hspace=0.5, wspace=0.5, top=0.95) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=0.5, wspace=0.5, bottom=0.05) # space between rows - def 0.4 - - # name and create output files (names derived from SEQNAME) - fig_name = '%s%s_wordsize%i%s-%.3d.%s' %(prefix, name_graph, wordsize, suffix, page_counter, filetype) - P.savefig(fig_name, bbox_inches='tight') - P.close() - P.cla() - - list_of_png_names.append(fig_name) - - if not verbose: - print seq_counter, "done" - log_txt += str(seq_counter) + " done" - else: - print "\n%d done" % seq_counter - log_txt += "\n%d done" % seq_counter - logprint(log_txt, start=False, printing=False) - - if verbose: - print - logprint(seq_text, start=False, printing=False) - - return list_of_png_names - -def polydotplot(input_fasta, wordsize, prefix=None, plot_size=10, label_size=10, filetype='png', type_nuc=True, convert_wobbles=False, substitution_count=0, alphabetic_sorting=False, mirror_y_axis=False, title_length=float("Inf"), title_clip_pos="B", max_N_percentage=49, verbose=False, gff_files=[], gff_color_dict={"others": ("grey", 1, 0)}, x_label_pos_top=True, lcs_shading=True, lcs_shading_ref=0, lcs_shading_interval_len=100, lcs_shading_ori=0, lcs_shading_num=5, spacing=0.04, input_user_matrix_file="", user_matrix_print=True, rotate_labels=False): - """ - all-against-all dotplot - derived from dotplot function - - lcs_shading_refs: - 0 color relative to maximum lcs observed in dataset [default] - 1 color by coverage of shorter sequence (e.g. lcs = 70% of seq1) - lcs_shading_ori - 0 forward only - 1 reverse only - 2 both orientations (in opposite plot) - """ - - # read sequences - seq_dict, sequences = read_seq(input_fasta) - if seq_dict == {}: - logprint("\nFailed to load sequences") - return [] - - if alphabetic_sorting: - sequences = sorted(sequences) - - if len(sequences) == 0: - text = "\n%s\n\nCreating %dx%d polydotplot image\n%s\n\n=>" % (50*"=", len(sequences), len(sequences), 30*"-") - text += " No sequences provided for polydotplot!\n\nTerminating polydotplot!" - logprint(text, start=False, printing=True) - return - elif len(sequences) == 1: - text = "\n\nCreating polydotplot for single sequence!" - text += "\nRecommendation: Use selfdotplot via '--plotting_mode 0'!\n\n" - logprint(text, start=False, printing=True) - - text = "\n%s\n\nCreating %dx%d polydotplot image\n%s\n\n=>" % (50*"=", len(sequences), len(sequences), 30*"-") - text += " " + " ".join(sequences) + "\n" - logprint(text, start=False, printing=True) - - # read gff annotation data if provided for shading - if gff_files != None and gff_files != []: - text = "\n%s\n\nReading %s GFF annotation files\n%s\n\n=> %s\n" % (50*"=", len(gff_files), 28*"-", ", ".join(gff_files)) - logprint(text, start=False, printing=True) - if prefix != None and prefix != "": - legend_prefix = prefix + "-Polydotplot" - else: legend_prefix = "Polydotplot" - feat_dict = read_gffs(gff_files, color_dict=gff_color_dict, type_nuc=type_nuc, prefix=legend_prefix, filetype=filetype, verbose=verbose) - - if lcs_shading and not type_nuc: - if lcs_shading_ori != 0: - lcs_shading_ori = 0 - text = "Protein shading does not support reverse complementary matching!\n" - logprint(text, start=False, printing=True) - - # read custom shading matrix & match names of sequences to fasta - if input_user_matrix_file != "" and input_user_matrix_file != None: - logprint("Reading user matrix file: %s" % input_user_matrix_file) - # lcs_shading_ori = 2 - custom_dict = read_matrix(input_user_matrix_file) - if custom_dict != {}: - custom_shading = True - custom_similarity_dict = {} - invalid_entries = [] - custom_max = 0 - custom_min = float("Inf") - for key in custom_dict.keys(): - number_key = [] - - # convert number into float - try: - value = float(custom_dict[key]) - if not "." in custom_dict[key]: - value = int(custom_dict[key]) - custom_max = max(custom_max, value) - custom_min = min(custom_min, value) - except: - value = custom_dict[key] - if value == "": - value = None - invalid_entries.append(key) - # match matrix names with sequence names - for item in key: - if item in sequences: - number_key.append(sequences.index(item)) - else: - number_key.append(-1) - # dictionary with tuple of sorted sequence indices as key and number as value - custom_similarity_dict[tuple(sorted(number_key))] = value - if len(invalid_entries) != 0: - text = "No valid number in custom similarity matrix for %d entries: \n\t" % (len(invalid_entries)) - for key in invalid_entries: - text += str(key) + " - " + str(custom_dict[key]) + "; " - logprint(text[:-2]+"\n") - - text = "Custom user matrix given: min %.2f, max %.2f\n" % (custom_min, custom_max) - - # artificially rounding intervals if likely identity/divergence percentages - if 0 <= custom_min < 1 and 0 < custom_max <= 1: - rounding_factor = 5 - multi_factor = 100 - text += " > artificially rounding custom shading intervals: old (%.2f, %.2f) - " % (custom_min, custom_max) - custom_min = max(0, (multi_factor*custom_min // rounding_factor) * (1.*rounding_factor/multi_factor)) - custom_max = min((multi_factor*custom_max // rounding_factor) * (1.*rounding_factor/multi_factor), 1) - text += "new (%.2f, >%2f)\n" % (custom_min, custom_max) - - elif 0 <= custom_min < 100 and 0 < custom_max <= 100: - rounding_factor = 5 - text += " > artificially rounding custom shading intervals: old (%.2f, %.2f) - " % (custom_min, custom_max) - custom_min = max(0, (custom_min // rounding_factor) * rounding_factor) - custom_max = min((custom_max // rounding_factor) * rounding_factor, 100) - text += "new (%d, >%d)\n" % (custom_min, custom_max) - - logprint(text) - - else: - custom_shading = False - - name_graph = "Polydotplot" - suffix = "" - if convert_wobbles: - suffix += "_wobbles" - if substitution_count != 0: - suffix += "_S%d" % substitution_count - if custom_shading: - suffix += "_matrix" - if lcs_shading: - suffix += "_%dshades_ref%d_ori%s" % (lcs_shading_num+1, lcs_shading_ref, lcs_shading_ori) - if "ref2" in suffix and type_nuc: - suffix = suffix.replace("ref2", "%dbp" % lcs_shading_interval_len) - elif "ref2" in suffix: - suffix = suffix.replace("ref2", "%daa" % lcs_shading_interval_len) - - - # name and create output files (names derived from SEQNAME) - if prefix != None and str(prefix) != "": - prefix = str(prefix) + "-" - else: - prefix = "" - - # preparations for background shading - if lcs_shading or custom_shading: - # create color range white to grey - colors = create_color_list(lcs_shading_num+1, color_map=None, logging=True) - colors_2 = create_color_list(lcs_shading_num+1, color_map="OrRd", logging=True) - - if custom_shading: - text = "Custom Matrix Colors: " + ", ".join(colors_2) - - # write lcs lengths to file - lcs_data_file = open("%sPolydotplot_lcs_data_file%s.txt" % (prefix, suffix.replace("_scaled", "").replace("_collage", "")), 'w') - lcs_data_file.write("\t".join(["#title1", "title2", "len_seq1", "len_seq2", "len_lcs_for", "%_min_seq_len", "len_lcs_rev", "%_min_seq_len"])+"\n") - - # compare sequences pairwise - save lcs and line information in dictionary for plotting - data_dict = {} # keys = tuple(idx, jdx), value = x1, y1, x2, y2 (line positions) - lcs_dict = {} # keys = tuple(idx, jdx), value = length of lcs: lcs_len or (lcs_for, lcs_rev) - for_lcs_set = set([]) # keep lengths to calculate max (excluding self comparisons) - rev_lcs_set = set([]) # keep lengths to calculate max (all) - - text = "\nTotal plot count: %d" % (len(sequences)*(len(sequences))) - text += "\nTotal calculations: %d" % (len(sequences)*(len(sequences)+1)/2) - logprint(text, start=False, printing=True) - - print "\nCalculating shared regions and lengths of longest_common_substring...", - log_txt = "\nCalculating shared regions and lengths of longest_common_substring..." - # determine matches and length of lcs by comparing all sequence pairs - if verbose: - seq_text = "" - counter = 0 - for idx in range(len(sequences)): - if verbose: - print "\n%d\t%s vs." % ((counter+1), sequences[idx]), - seq_text += "\n%d\t%s vs." % ((counter+1), sequences[idx]) - rec_two = seq_dict[sequences[idx]] - name_two = rec_two.id - seq_two = rec_two.seq - len_two = len(seq_two) - - for jdx in range(idx, len(sequences)): - rec_one = seq_dict[sequences[jdx]] - name_one = rec_one.id - seq_one = rec_one.seq - len_one = len(seq_one) - - counter += 1 - if verbose: - print sequences[jdx], - seq_text += " " + sequences[jdx] - elif len(sequences) < 5: - print "\t%s (%d %s), %s (%d %s)" % (name_one, len_one, aa_bp_unit, name_two, len_two, aa_bp_unit) - log_txt += "\t%s (%d %s), %s (%d %s)\n" % (name_one, len_one, aa_bp_unit, name_two, len_two, aa_bp_unit) - else: - if not counter % 25: - print counter, - log_txt += str(counter) - - # get positions of matches & length of longest common substring based on match lengths - if substitution_count != 0: - # print "RE" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_regex(seq_one, seq_two, wordsize, substitution_count=substitution_count, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - else: - # print "DIAG" - x1, y1, x2, y2, lcs_for, lcs_rev = find_match_pos_diag(seq_one, seq_two, wordsize, convert_wobbles=convert_wobbles, max_N_percentage=max_N_percentage, report_lcs=True, type_nuc=type_nuc, verbose=verbose) - data_dict[(idx, jdx)] = x1[:], y1[:], x2[:], y2[:] - lcs_dict[idx, jdx] = lcs_for, lcs_rev - - if idx != jdx: - for_lcs_set.add(lcs_for) - rev_lcs_set.add(lcs_rev) - - lcs_data_file.write("\t".join([name_one, name_two, str(len_one), str(len_two), - str(lcs_for), str(round((lcs_for*100./min(len_one, len_two)), 3)), - str(lcs_rev), str(round((lcs_rev*100./min(len_one, len_two)), 3))]) + "\n") - - if not verbose: - print len(sequences)*(len(sequences)+1)/2, " done\n" - log_txt += str(len(sequences)*(len(sequences)+1)/2) + " done\n" - else: - print "\n%d done" % (len(sequences)*(len(sequences)+1)/2) - log_txt += "\n%d done" % (len(sequences)*(len(sequences)+1)/2) - logprint(log_txt, start=False, printing=False) - - if verbose: - logprint ("\n\nlcs_dict\n" + str(lcs_dict)) - if custom_shading: - logprint ("\ncustom_dict\n" + str(custom_dict)) - logprint ("\ncustom_similarity_dict\n\n" + str(custom_similarity_dict)) - - if verbose: - print - logprint(seq_text+"\n", start=False, printing=False) - - if lcs_shading_ref == 2: - color_bins = [] - text = "\nLCS lengh bins: " - for idx in range(lcs_shading_num): - color_bins.append(lcs_shading_interval_len*(idx+1)) - text += " " + str(lcs_shading_interval_len*(idx+1)) - logprint(text, start=False, printing=True) - - # calculate maximum lcs length - if lcs_shading_ori == 0: # forward only - if len(for_lcs_set) != 0: - max_lcs = max(for_lcs_set) - else: - max_lcs = None - elif lcs_shading_ori == 1: # reverse complement only - if len(rev_lcs_set) != 0: - max_lcs = max(rev_lcs_set) - else: - max_lcs = None - else: # both orientations - if len(rev_lcs_set) != 0 and len(for_lcs_set) != 0: - max_lcs = max(max(rev_lcs_set), max(for_lcs_set)) - elif len(rev_lcs_set) != 0: - max_lcs = max(rev_lcs_set) - elif len(for_lcs_set) != 0: - max_lcs = max(for_lcs_set) - else: - max_lcs = None - - if not max_lcs == None: - text = "Maximum LCS: %d %s" % (max_lcs, aa_bp_unit) - logprint(text, start=False, printing=True) - if custom_shading: - text = "Maximum custom value: %d\n" % custom_max - logprint(text, start=False, printing=True) - - # count sequences - ncols = len(sequences); nrows = len(sequences) - - # get sequence lengths to scale plot widths and heights accordingly - size_ratios = [] - for item in sequences: - size_ratios.append(len(seq_dict[item].seq)) - - P.cla() # clear any prior graph - # use GridSpec to resize plots according to sequence length - if mirror_y_axis: - height_ratios = size_ratios[::-1] - else: - height_ratios = size_ratios[:] - gs = gridspec.GridSpec(nrows, ncols, - width_ratios=size_ratios, - height_ratios=height_ratios) - fig = P.figure(figsize=(plot_size, plot_size)) - - # for cartesian coordinate system with mirrored y-axis: plot x labels below plot - if mirror_y_axis and representation == 1: - x_label_pos_top = True - elif mirror_y_axis or representation == 2: - x_label_pos_top = False - - # print y labels on the right, if upper right triangle is displayed - if (representation == 1 and not mirror_y_axis) or (representation == 2 and mirror_y_axis): - y_label_pos = 0 # last column - else: # left y label - y_label_pos = 1 # first column - - # determine label orientations - if len(sequences) > 5 or rotate_labels: - x_label_rotation = 45 - y_label_rotation = "horizontal" - if x_label_pos_top: - xhalign = 'left' - xvalign = 'bottom' - else: - xhalign = 'right' - xvalign = 'top' - yhalign = "right" - else: - x_label_rotation = "horizontal" - y_label_rotation = "vertical" - xvalign = "center" - xhalign = "center" - yhalign = "center" - yvalign = 'center' - - # check combination of shading parameters for triangular output - if representation != 0 and lcs_shading and custom_shading: # both directions in triangle - logprint("\nAttention: For triangular output custom-shading and LCS shading cannot be combined!\n") - elif representation != 0 and lcs_shading and lcs_shading_ori == 2: # both directions in triangle - logprint("\nAttention: For triangular output LCS shading for both orientations is combined to max of both orientations!\n") - - print "\nDrawing polydotplot...", - log_txt = "\nDrawing polydotplot..." - - # draw subplots - if verbose: - if lcs_shading and custom_shading: - lcs_text = "\n" + "\t".join(["#Seq1", "Seq2", "LCS for [%s]" %aa_bp_unit, "LCS for [%s]" %aa_bp_unit, "Custom matrix value", "Matrix color index", "LCS color index"]) + "\n" - elif lcs_shading: - lcs_text = "\n" + "\t".join(["#Seq1", "Seq2", "LCS for [%s]" %aa_bp_unit, "LCS for [%s]" %aa_bp_unit, "LCS color index for", "LCS color index rev"]) + "\n" - elif custom_shading: - lcs_text = "\n" + "\t".join(["#Seq1", "Seq2", "Custom matrix value", "Color index for", "Color index rev"]) + "\n" - - if verbose: - seq_text = "" - counter, seq_counter = 0, 0 - for idx in range(len(sequences)): - if verbose: - print "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]), - seq_text += "\n%d\t%s vs." % ((seq_counter+1), sequences[idx]) - rec_two = seq_dict[sequences[idx]] - len_two = len(rec_two.seq) - name_two = rec_two.id - - for jdx in range(idx, len(sequences)): - rec_one = seq_dict[sequences[jdx]] - len_one = len(rec_one.seq) - name_one = rec_one.id - - counter += 1 - seq_counter += 1 - if verbose: - print sequences[jdx], - seq_text += " " + sequences[jdx] - elif not seq_counter % 25: - print seq_counter, - log_txt += str(seq_counter) - - # optional shade background according to length of LCS and/or user matrix - ######################################################################### - - # get interval based on LCS - background_colors = [None, None] - if lcs_shading and (lcs_shading_ref==1 or lcs_shading_ref==2 or max_lcs!=None): # self plot max_lcs_for == None - lcs_len = lcs_dict[(idx, jdx)] - l1 = lcs_len[0] # forward - l2 = lcs_len[1] # reverse complement - - lcs_shading_bool = True - - # calculate shading acc. to chosen option - if lcs_shading_ref == 1: # percentage of shorter sequence - color_idx0 = min(len(colors)-1, l1*lcs_shading_num // min(len_one, len_two)) - color_idx1 = min(len(colors)-1, l2*lcs_shading_num // min(len_one, len_two)) - elif lcs_shading_ref == 2: # by given interval size - color_idx0 = min(len(colors)-1, l1 // lcs_shading_interval_len) - color_idx1 = min(len(colors)-1, l2 // lcs_shading_interval_len) - if color_idx0 >= len(colors): - color_idx0 = len(colors) - if color_idx1 >= len(colors): - color_idx1 = len(colors) - else: # percentage of maximum lcs length - color_idx0 = min(len(colors)-1, l1*lcs_shading_num // max_lcs) - color_idx1 = min(len(colors)-1, l2*lcs_shading_num // max_lcs) - else: - lcs_shading_bool = False - - # get interval based on custom matrix - if custom_shading: - # matrix value - try: - custom_value = custom_similarity_dict[(idx, jdx)] - except: - custom_value = "" - - # bottom left triangle = LCS forward/reverse or best of both - if lcs_shading_bool: - if lcs_shading_ori == 0: # forward - color_idx1 = color_idx0 - elif lcs_shading_ori == 2: # both directions - color_idx1 = max(color_idx0, color_idx1) - - # top right triangle = custom value (not colored if text matrix provided) - if type(custom_value) == int or type(custom_value) == float: - color_idx0 = int((custom_value-custom_min)*lcs_shading_num // (custom_max-custom_min)) - # no color if string is proviced - else: - color_idx0 = 0 - - # use best LCS of both orientations for coloring triangle with two-ori-LCS - if representation != 0 and lcs_shading_ori == 2: # both directions in triangle - color_idx0, color_idx1 = max(color_idx0, color_idx1), max(color_idx0, color_idx1) - - # set colors dependent on lcs dependent on orientation - if lcs_shading_bool and not custom_shading: - if idx != jdx: - if lcs_shading_ori == 0: - color_idx1 = color_idx0 - elif lcs_shading_ori == 1: - color_idx0 = color_idx1 - background_colors[0] = colors[color_idx0] - background_colors[1] = colors[color_idx1] - # for selfcomparison, only color reverse complement - elif lcs_shading_ori != 0 and not custom_shading: - background_colors[0] = colors[color_idx1] - # set different colors for shading by LCS + user matrix - elif lcs_shading_bool and custom_shading: - # print colors, background_colors, color_idx0, color_idx1 - background_colors[0] = colors_2[color_idx0] - background_colors[1] = colors[color_idx1] - # set grey color range for user matrix if no LCS shading - elif custom_shading: - background_colors[0] = colors[color_idx0] - background_colors[1] = colors[color_idx0] - - if verbose: - if custom_shading and lcs_shading_bool: - lcs_text += "\t".join([name_one, name_two, str(lcs_len[0]), str(lcs_len[1]), str(custom_value), str(color_idx0), str(color_idx1)]) + "\n" - elif lcs_shading_bool: - lcs_text += "\t".join([name_one, name_two, str(lcs_len[0]), str(lcs_len[1]), str(color_idx0), str(color_idx1)]) + "\n" - elif custom_shading: - lcs_text += "\t".join([name_one, name_two, str(custom_value), str(color_idx0), str(color_idx1)]) + "\n" - - # calculate figure position in polyplot - # diagonal (self-dotplots) - if idx == jdx: - if mirror_y_axis: - seq_num = sequences.index(name_one)+1 - counter1 = seq_num + len(sequences) * (len(sequences)-seq_num) - counter = counter + (counter - 1) // (nrows) - else: - # skip positions below diagonal - counter1 = counter + (counter - 1) // (nrows) # + row_pos - counter = counter1 - counters = [counter1] - - # draw both graphs at once (due to symmetry) - else: - if mirror_y_axis: - col_pos = sequences.index(name_two)+1 - row_pos = len(sequences) - (sequences.index(name_one)+1) - counter1 = row_pos * ncols + col_pos - counter2 = (ncols - col_pos) * ncols + ncols - row_pos - else: - counter1 = counter - col_pos = (counter - 1) % ncols - row_pos = (counter - 1) // (nrows) - counter2 = col_pos * ncols + row_pos + 1 - counters = [counter1, counter2] # lower, upper - - if len(counters) == 2: - seq_counter += 1 - if not verbose and not seq_counter % 25: - print seq_counter, - log_txt += str(seq_counter) - - x_lists, y_lists, x_lists_rc, y_lists_rc = data_dict[(idx, jdx)] - - # plot diagram(s) - for kdx in range(len(counters)): - - if representation == 0 or len(counters) == 1 or (representation == 1 and kdx == 0) or (representation == 2 and kdx == 1): - - fig_pos = counters[kdx] - # plotting subplot with matplotlib - ax = P.subplot(gs[fig_pos-1]) # rows, columns, plotnumber - - # shade annotated regions if gff file(s) provided - if idx == jdx and gff_files != None and gff_files != []: - if name_one in feat_dict.keys(): - features = feat_dict[name_one] - if len_two != len_one: - logprint("Polydot GFF shading for diagonal fields - nequal length error!") - return - for item in features: - feat_type, start, stop = item - feat_color, strength, zoom = gff_color_dict[feat_type.lower()] - start = max(0, start - zoom - 0.5) - stop = min(len_one+1, stop + zoom + 0.5) - width = stop - start - ax.add_patch(patches.Rectangle((start, start), # (x,y) - width, width, # width, height - edgecolor=None, linewidth=line_width+zoom, - fill=True, facecolor=feat_color, - alpha=strength)) - - # if custom matrix value printed into upper matrix triangle, skip data plotting - # text print in top triangle - if user_matrix_print and custom_shading and kdx==0 and idx!=jdx: - data_plotting = False - # dotplot in bottom triangle - else: - data_plotting = True - - # mirror plot, if plotting below diagonal - if kdx == 0: - l1, l2 = len_one, len_two - n1, n2 = name_one, name_two - x1, y1 = x_lists, y_lists - x2, y2 = x_lists_rc, y_lists_rc - else: - l2, l1 = len_one, len_two - n2, n1 = name_one, name_two - x1, y1 = y_lists, x_lists - x2, y2 = y_lists_rc, x_lists_rc - - if mirror_y_axis: - x1, y1, x2, y2 = y1, x1, y2, x2 - n1, n2 = n2, n1 - - if data_plotting: - # collect lines - lines = [] - color_list = [] - for (x_lines, y_lines, col) in [(x2, y2, line_col_rev), (x1, y1, line_col_for)]: - if col != "white": - for ldx in range(len(x_lines)): - lines.append([(x_lines[ldx][0], y_lines[ldx][0]), (x_lines[ldx][-1], y_lines[ldx][-1])]) - color_list.append(col) - color_list = np.array(color_list) - - # draw lines - lc = cllct.LineCollection(lines, colors=color_list, linewidths=line_width) - ax.add_collection(lc) - - # plot value provided by customer instead of dotplot - else: - alignment = {'horizontalalignment': 'center', 'verticalalignment': 'center'} - # P.text(0.5, 0.5, custom_value, size='medium', transform=ax.transAxes, **alignment) - P.text(0.5, 0.5, custom_value, size=label_size*1.5, transform=ax.transAxes, **alignment) - # P.text(0.5, 0.5, custom_value, size=label_size*1.5, transform=ax.transAxes, - # horizontalalignment='center', verticalalignment='center', color="black") - - if custom_shading: - # omit diagonal - if idx == jdx: - ax.set_facecolor("white") - # use white background for text fields (top right triangle only [kdx 0]) - elif type(custom_value) != int and type(custom_value) != float and kdx == 0: - ax.set_facecolor("white") - else: - ax.set_facecolor(background_colors[kdx]) - # set background color if lcs shading - elif lcs_shading_bool and background_colors[kdx] != None: - ax.set_facecolor(background_colors[kdx]) - - # set axis limits - # P.xlim(0, l1+1) - if mirror_y_axis: - P.xlim(0, l2+1) - P.ylim(0, l1+1) # rotate y axis (point upwards) - else: - P.xlim(0, l1+1) - P.ylim(l2+1, 0) # rotate y axis (point downwards) - - ## axis labelling - ################## - - # determine axis positions - if x_label_pos_top: - ax.xaxis.tick_top() - ax.xaxis.set_label_position('top') - x_label_bool = fig_pos <= ncols - x_tick_bool = fig_pos > ncols*(ncols-1) - else: - x_label_bool = fig_pos > ncols*(ncols-1) - x_tick_bool = fig_pos <= ncols - - # settings for y labels on right side - if y_label_pos == 0: # right label - ax.yaxis.tick_right() - ax.yaxis.set_label_position("right") - label_dist = 30 - else: - label_dist = 8 - - # x axis labels dependent on plot position/number - if x_label_bool: # x title and labels on top or bottom - P.xlabel(unicode_name(shorten_name(n1, max_len=title_length, title_clip_pos=title_clip_pos)), fontsize=label_size, rotation=x_label_rotation, verticalalignment=xvalign, horizontalalignment=xhalign, fontweight='bold', labelpad=8) # axis naming - if not x_label_rotation in ["horizontal", "vertical"]: - P.setp(ax.get_xticklabels(), fontsize=label_size*.9, rotation="vertical") - else: - P.setp(ax.get_xticklabels(), fontsize=label_size*.9, rotation=x_label_rotation) - elif x_tick_bool and x_label_pos_top: # x ticks on bottom row - ax.xaxis.tick_bottom() # ticks without labels on bottom - P.setp(ax.get_xticklabels(), fontsize=label_size, rotation=x_label_rotation, visible=False) - elif x_tick_bool: # x ticks on top row - ax.xaxis.tick_top() # # ticks without labels on top - P.setp(ax.get_xticklabels(), fontsize=label_size, rotation=x_label_rotation, visible=False) # inner diagrams without labelling - elif idx == jdx and representation != 0: - if not mirror_y_axis and representation == 1: # upper - ax.xaxis.tick_bottom() - elif mirror_y_axis and representation == 2: # lower - ax.xaxis.tick_top() - elif mirror_y_axis and representation == 1: # upper - ax.xaxis.tick_bottom() - elif not mirror_y_axis and representation == 2: # lower - ax.xaxis.tick_top() - P.setp(ax.get_xticklabels(), visible=False) # inner diagrams without labelling - else: # no x ticks on internal rows - ax.axes.get_xaxis().set_visible(False) - - # y axis labels dependent on plot position/number - if fig_pos % ncols == y_label_pos or (ncols == 1 and nrows == 1): # y title and labels in 1st column - P.ylabel(unicode_name(shorten_name(n2, max_len=title_length, title_clip_pos=title_clip_pos)), fontsize=label_size, rotation=y_label_rotation, verticalalignment=yvalign, horizontalalignment=yhalign, fontweight='bold', labelpad=label_dist) - P.setp(ax.get_yticklabels(), fontsize=label_size*.9) # axis naming - elif fig_pos % ncols == 0: # y ticks in last column - ax.yaxis.tick_right() - P.setp(ax.get_yticklabels(), visible=False) # inner diagrams without labelling - elif idx == jdx and representation != 0: - if not mirror_y_axis and representation == 1: # upper - ax.yaxis.tick_left() - elif mirror_y_axis and representation == 2: # lower - ax.yaxis.tick_left() - elif mirror_y_axis and representation == 1: # upper - ax.yaxis.tick_right() - elif not mirror_y_axis and representation == 2: # lower - ax.yaxis.tick_right() - P.setp(ax.get_yticklabels(), visible=False) # inner diagrams without labelling - else: - ax.axes.get_yaxis().set_visible(False) - - if not verbose: - print seq_counter, "done" - log_txt += str(seq_counter) + " done" - else: - print "\n%d done" % seq_counter - log_txt += "\n%d done" % seq_counter - logprint(log_txt, start=False, printing=False) - - if verbose: - try: - logprint(lcs_text, start=False, printing=True) - except: - pass - - # finalize layout - margins & spacing between plots - P.tick_params(axis='both', which='major', labelsize=label_size*.9) - try: - P.tight_layout(h_pad=.02, w_pad=.02) - except: - logprint("Attention - pylab.tight_layout failed! Please check sequence names and layout settings!") - # gs.tight_layout(fig, h_pad=.02, w_pad=.02) # less overlapping tick labels, but also disturbingly large spacing - if y_label_rotation == "horizontal": - if x_label_pos_top: - P.subplots_adjust(hspace=spacing, wspace=spacing, left=0.13, top=0.87) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=spacing, wspace=spacing, left=0.13, bottom=0.13) # space between rows - def 0.4 - else: - P.subplots_adjust(hspace=spacing, wspace=spacing) # space between rows - def 0.4 - - # save figure and close instance - fig_name = '%s%s_wordsize%i%s.%s' % (prefix, name_graph, wordsize, suffix, filetype) - P.savefig(fig_name) - P.close() - P.cla() - - - # create figure color legend - if lcs_shading: - if lcs_shading_ref == 1: # percentage of shorter sequence - legend_file_name = legend_figure(colors, lcs_shading_num, unit="%", filetype=filetype, prefix=prefix) - elif lcs_shading_ref == 2: # interval sizes - legend_file_name = legend_figure(colors, lcs_shading_num, unit=aa_bp_unit, filetype=filetype, prefix=prefix, bins=color_bins) - else: # relative of maximum lcs - legend_file_name = legend_figure(colors, lcs_shading_num, unit=aa_bp_unit, filetype=filetype, prefix=prefix, max_len=max_lcs) - - if custom_shading: - custom_prefix = "custom-matrix-" + prefix - legend_file_name_custom = legend_figure(colors_2, lcs_shading_num, unit="%", filetype=filetype, prefix=custom_prefix, max_len=custom_max, min_len=custom_min) - - if lcs_shading and custom_shading: - return [fig_name, legend_file_name, legend_file_name_custom] - elif lcs_shading: - return [fig_name, legend_file_name] - elif custom_shading: - return [fig_name, legend_file_name_custom] - else: - return [fig_name] - - -############################### -# Function Call # -############################### - -def main(seq_list, wordsize, modes=[0, 1, 2], prefix=None, plot_size=10, label_size=10, filetype="png", type_nuc=True, convert_wobbles=False, substitution_count=0, rc_option=True, alphabetic_sorting=False, only_vs_first_seq=False, gff=None, multi=True, ncols=1, nrows=1, lcs_shading=True, lcs_shading_num=5, lcs_shading_ref=0, lcs_shading_interval_len=100, lcs_shading_ori=0, gff_color_config_file="", input_user_matrix_file="", user_matrix_print=False, length_scaling=True, title_length=50, title_clip_pos="B", spacing=0.04, max_N_percentage=49, mirror_y_axis=False, verbose=False): - - global t1, line_col_rev - - # check input variables - if convert_wobbles and max_N_percentage > 49: - max_N_percentage = 49 - if type_nuc: - ambiq_res = "N" - else: - ambiq_res = "X" - text = "Provide valid max_N_percentage, kmers with >50%% %ss are ignored\n" % (ambiq_res) - logprint(text, start=False, printing=True) - - if filetype not in ["png", "pdf", "svg"]: - text = "Provide valid file type - png, pdf, or svg - given:%s\n" % filetype - logprint(text, start=False, printing=True) - filetype = "png" - - # read gff color config file if provided - if len(input_gff_files) != 0 and input_gff_files != None: - if gff_color_config_file not in ["", None]: - text = "\n%s\n\nReading GFF color configuration file\n%s\n\n=> %s\n" % (50*"=", 28*"-", gff_color_config_file) - logprint(text, start=False, printing=True) - gff_feat_colors = read_gff_color_config(gff_color_config_file) - else: - gff_feat_colors = {} - if gff_color_config_file not in ["", None]: - text = "Please provide GFF annotation files to use configuration file", gff_color_config_file - logprint(text, start=False, printing=True) - - # if color is set to white, reverse complementary matches are skipped - if not rc_option: - line_col_rev = "white" # reverse matches not calculated - elif not type_nuc: - logprint("Reverse complement deactivated for proteins!") - line_col_rev = "white" # reverse matches not calculated - - mode_text = [] - for item in modes: - mode_text.append(str(item)) - text = "%s\n\nRunning plotting modes %s" % (50*"=", ", ".join(mode_text)) - logprint(text, start=False, printing=True) - - - # create dotplots - ########################################## - - # self dotplots - t1 = time.time() - if 0 in modes: - list_of_png_names = selfdotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, title_clip_pos=title_clip_pos, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, multi=multi, ncols=ncols, nrows=nrows, gff_files=gff, gff_color_dict=gff_feat_colors, mirror_y_axis=mirror_y_axis, max_N_percentage=max_N_percentage, verbose=verbose) - t1 = time_track(t1) - if list_of_png_names != [] and list_of_png_names != None: - text = "-> Image file(s): %s\n" % ", ".join(list_of_png_names) - else: - text = "No image files were created!\n" - logprint(text, start=False, printing=True) - logprint(50*"=") - - # paired dotplots - if 1 in modes: - if multi: - list_of_png_names = pairdotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, title_clip_pos=title_clip_pos, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, only_vs_first_seq=only_vs_first_seq, multi=multi, ncols=ncols, nrows=nrows, length_scaling=length_scaling, mirror_y_axis=mirror_y_axis, max_N_percentage=max_N_percentage, verbose=verbose) - t1 = time_track(t1) - else: - if not length_scaling: - text = "\nPairwise dotplot with individual output files scaled by sequence length automatically!" - logprint(text, start=False, printing=True) - list_of_png_names = pairdotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, title_clip_pos=title_clip_pos, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, only_vs_first_seq=only_vs_first_seq, multi=multi, ncols=ncols, nrows=nrows, length_scaling=True, mirror_y_axis=mirror_y_axis, max_N_percentage=max_N_percentage, verbose=verbose) - t1 = time_track(t1) - if list_of_png_names != [] and list_of_png_names != None: - text = "-> Image file(s): %s\n" % ", ".join(list_of_png_names) - else: - text = "No image files were created!\n" - logprint(text, start=False, printing=True) - logprint(50*"=") - - # all-against-all dotplot - if 2 in modes: - list_of_png_names = polydotplot(seq_list, wordsize, prefix=prefix, label_size=label_size, title_length=title_length, title_clip_pos=title_clip_pos, plot_size=plot_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=convert_wobbles, substitution_count=substitution_count, alphabetic_sorting=alphabetic_sorting, lcs_shading=lcs_shading, lcs_shading_num=lcs_shading_num, lcs_shading_ref=lcs_shading_ref, lcs_shading_interval_len=lcs_shading_interval_len, lcs_shading_ori=lcs_shading_ori, input_user_matrix_file=input_user_matrix_file, user_matrix_print=user_matrix_print, spacing=spacing, gff_files=gff, gff_color_dict=gff_feat_colors, mirror_y_axis=mirror_y_axis, max_N_percentage=max_N_percentage, verbose=verbose) - t1 = time_track(t1) - if list_of_png_names != [] and list_of_png_names != None: - text = "-> Image file(s): %s\n" % ", ".join(list_of_png_names) - else: - text = "No image files were created!\n" - logprint(text, start=False, printing=True) - logprint(50*"=") - - text = "\n" + 50 * "#" + "\n" + 50 * "#" - text += "\n\nThank you for using FlexiDot!\n" - logprint(text, start=False, printing=True) - - -load_modules() - -# testing mode for debugging -trial_mode = True -trial_mode = False - -# parameters = check_input(sys.argv) -parameters = check_input(sys.argv, trial_mode=trial_mode) - -# read out parameters -commandline, auto_fas, input_fasta, output_file_prefix, collage_output, m_col, n_row, filetype, type_nuc, input_gff_files, gff_color_config_file, wordsize, plotting_modes, wobble_conversion, substitution_count, rc_option, alphabetic_sorting, only_vs_first_seq, lcs_shading, lcs_shading_num, lcs_shading_ref, lcs_shading_interval_len, lcs_shading_ori, input_user_matrix_file, user_matrix_print, plot_size, line_width, line_col_for, line_col_rev, x_label_pos_top, label_size, spacing, length_scaling, title_length, title_clip_pos, max_N_percentage, mirror_y_axis, representation, verbose = parameters - -# evtl. overwrite parameters for testing purposes in trial mode -if trial_mode: - input_fasta = ["Inversionen_IDs_v2_test2.fas"] - # input_fasta = ["Inversionen_IDs_v2_test3.fas"] - # input_fasta = ["test-sequences-8.fas"] - # input_gff_files = ["Seq2_annotations.gff3"] - # input_user_matrix_file = "matrix.txt" - # user_matrix_print = True - output_file_prefix = "#Test" - plot_size = 10 - plotting_modes = [0,1,2] - plotting_modes = [2] - plotting_modes = [0] - lcs_shading = False - lcs_shading = True - lcs_shading_ref = 2 - lcs_shading_num = 4 - lcs_shading_ori = 0 - lcs_shading_interval_len = 15 - wordsize = 10 - wordsize = 7 - x_label_pos_top = True - filetype = "pdf" - filetype = "png" - mirror_y_axis = False - mirror_y_axis = True - - output_file_prefix = "#R-upper" - representation = 0 # both - representation = 1 # upper - representation = 2 # lower - - wobble_conversion = False - wobble_conversion = True - - substitution_count = 0 - substitution_count = 1 - - rc_option = True - rc_option = False - label_size = 10 - - verbose = False - verbose = True - -if auto_fas: - path = os.path.dirname(os.path.abspath(__file__)) - files_long = glob.glob(path+"/*.fasta") - files_long.extend(glob.glob(path+"/*.fas")) - files_long.extend(glob.glob(path+"/*.fa")) - files_long.extend(glob.glob(path+"/*.fna")) - input_fasta = [] - for i in files_long: - if not "combined" in i: - filename = i[i.rfind('\\')+1:] - input_fasta.append(filename) - -if trial_mode: - # start logging file - logprint(commandline, start=True, printing=False, prefix=output_file_prefix) - - - -###################### -# FlexiDot Execution # -###################### - -main(input_fasta, wordsize, modes=plotting_modes, prefix=output_file_prefix, plot_size=plot_size, label_size=label_size, filetype=filetype, type_nuc=type_nuc, convert_wobbles=wobble_conversion, substitution_count=substitution_count, rc_option=rc_option, alphabetic_sorting=alphabetic_sorting, only_vs_first_seq=only_vs_first_seq, gff=input_gff_files, multi=collage_output, ncols=m_col, nrows=n_row, lcs_shading=lcs_shading, lcs_shading_num=lcs_shading_num, lcs_shading_ref=lcs_shading_ref, lcs_shading_interval_len=lcs_shading_interval_len, lcs_shading_ori=lcs_shading_ori, gff_color_config_file=gff_color_config_file, input_user_matrix_file=input_user_matrix_file, user_matrix_print=user_matrix_print, length_scaling=length_scaling, title_length=title_length, title_clip_pos=title_clip_pos, spacing=spacing, max_N_percentage=max_N_percentage, mirror_y_axis=mirror_y_axis, verbose=verbose) - - From c1a20186933d9d9e0cb9678370aac8d17626dbe0 Mon Sep 17 00:00:00 2001 From: Adam Taranto Date: Thu, 12 Dec 2024 17:26:40 +1100 Subject: [PATCH 02/73] create changelog --- CHANGELOG.md | 150 +++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 150 insertions(+) create mode 100644 CHANGELOG.md diff --git a/CHANGELOG.md b/CHANGELOG.md new file mode 100644 index 0000000..94489a1 --- /dev/null +++ b/CHANGELOG.md @@ -0,0 +1,150 @@ +# FlexiDot version changes + +![alt text](https://github.com/molbio-dresden/flexidot/blob/master/images/Selfdotplots_banner4.png "FlexiDot self dotplots") + +## Version 1.06 +*14.04.2019* + +* [new parameter cheat sheet v1.06](https://github.com/molbio-dresden/flexidot/blob/master/documentation/usage_v1.06.pdf) +* [new FlexiDot script v1.06](https://github.com/molbio-dresden/flexidot/blob/master/code/flexidot_v1.06.py) + + +**[Major bugfixes]:** + +We corrected a few bugs, including a bug introduced in version 1.05, affecting dotplots with substitutions allowed. We reverted (for now) to the pattern matching algorithm of version 1.04. + +
+ +## Version 1.05 +*14.12.2018* + +* [new parameter cheat sheet v1.05](https://github.com/molbio-dresden/flexidot/blob/master/documentation/usage_v1.05.pdf) +* [new FlexiDot script v1.05](https://github.com/molbio-dresden/flexidot/blob/master/code/flexidot_v1.05.py) + + +**[Faster run time]:** +We modified word match recognition, speeding up FlexiDot's runtime. + + +**[New feature] New option for pairwise dotplot collages:** +With the new `-O, --only_vs_first_seq` option, it is now possible to limit the output of the pairwise dotplots. Instead of printing all possible pairwise combinations from a multi-fasta-sequence, only the pairwise comparisons against the first sequence are generated, if switched on (`-O y`). We use this feature to compare a new/unknown sequence against a batch of references. + + +**[Changed default wordsize]:** +The default wordsize has been changed from 7 to 10 in order to prevent people from running FlexiDot with small word sizes on large datasets, as this presumably takes a very long time. + + +**[Bugfixes]:** + +We fixed a few bugs with the dotplot shading legends. + +
+ +## Version 1.04 +*29.06.2018* + +* [new parameter cheat sheet v1.04](https://github.com/molbio-dresden/flexidot/blob/master/documentation/usage_v1.04.pdf) +* [new FlexiDot script v1.04](https://github.com/molbio-dresden/flexidot/blob/master/code/flexidot_v1.04.py) + + +**[New feature] Graphic formatting options for all-against-all dotplots:** +On request we added two parameters: + +* With `-M/--mirror` it is now possible to mirror the middle diagonal. + + + +Basic commands: +``` +python flexidot.py -i test-seqs.fas -p 2 -M n +python flexidot.py -i test-seqs.fas -p 2 -M y +``` +Command plus aesthetics as shown here (as described in version update 1.03): +``` +python flexidot.py -i test-seqs.fas -p 2 -M n -g example2.gff3 -G gff_color.config -x y -k 10 -F 0.06 -A 1.5 +python flexidot.py -i test-seqs.fas -p 2 -M y -g example2.gff3 -G gff_color.config -x y -k 10 -F 0.06 -A 1.5 +``` +
+ +* The `-R/--representation` parameter allows partial dotplotting, either printing the complete `-R 0`, the top `-R 1`, or the bottom dotplot `-R 2`. + + + +Basic commands: +``` +python flexidot.py -i test-seqs.fas -p 2 -R 0 +python flexidot.py -i test-seqs.fas -p 2 -R 1 +python flexidot.py -i test-seqs.fas -p 2 -R 2 +``` +Command plus aesthetics as shown here (as described in version update 1.03): +``` +python flexidot.py -i test-seqs.fas -p 2 -R 0 -g example2.gff3 -G gff_color.config -x y -k 10 -F 0.06 -A 1.5 +python flexidot.py -i test-seqs.fas -p 2 -R 1 -g example2.gff3 -G gff_color.config -x y -k 10 -F 0.06 -A 1.5 +python flexidot.py -i test-seqs.fas -p 2 -R 2 -g example2.gff3 -G gff_color.config -x y -k 10 -F 0.06 -A 1.5 +``` +
+ +**[Bugfix]:** + +We also fixed a distortion issue in `-p/--plotting_mode 0` (self dotplots). + +
+ +## Version 1.03 +*17.06.2018* + +* [new parameter cheat sheet v1.03](https://github.com/molbio-dresden/flexidot/blob/master/documentation/usage_v1.03.pdf) +* [new FlexiDot script v1.03](https://github.com/molbio-dresden/flexidot/blob/master/code/flexidot_v1.03.py) + + +**[New feature] Annotation-based shading also available for all-against-all dotplots:** +Previously only available for self dotplots, we added annotation-based shading to all-against-all dotplots, allowing for many new visualizations. As before, annotation information is provided as general feature file (GFF3). These features are added to the middle diagonal (see our example below). + + + +Basic command: +``` +python flexidot.py -i test-seqs.fas -g example2.gff3 -G gff_color.config -p 2 +``` + +Command plus aesthetics as shown here (+ LCS shading, wordsize 10, change of subplot spacing and line width): +``` +python flexidot.py -i test-seqs.fas -g example2.gff3 -G gff_color.config -p 2 -x y -k 10 -F 0.06 -A 1.5 +``` + +The test files used here are provided: +* [test-seqs.fas](https://github.com/molbio-dresden/flexidot/blob/master/test-data/test-seqs.fas) +* [example2.gff3](https://github.com/molbio-dresden/flexidot/blob/master/test-data/example2.gff3) +* [gff_color.config](https://github.com/molbio-dresden/flexidot/blob/master/test-data/gff_color.config) + +
+ +## Version 1.02 +*09.05.2018* + +* [new parameter cheat sheet v1.02](https://github.com/molbio-dresden/flexidot/blob/master/documentation/usage_v1.02.pdf) +* [new FlexiDot script v1.02](https://github.com/molbio-dresden/flexidot/blob/master/code/flexidot_v1.02.py) + +Changed handling of `-T` parameter: The character count of the sequence titles has been limited to `20` by default. This limit can be changed with `-T`. If an `E` (end) is added to the limit, the last characters are chosen instead of the first. + +``` +-T 20 (the first 20 characters) +-T 20E (the last 20 characters) +``` +
+ +## Version 1.01 +*21.04.2018* + + +* [parameter cheat sheet v1.01](https://github.com/molbio-dresden/flexidot/blob/master/documentation/usage_v1.01.pdf) +* [FlexiDot script v1.01](https://github.com/molbio-dresden/flexidot/blob/master/code/flexidot_v1.01.py) + +minor bugfixing + +
+ +## Version 1.00 +*21.03.2018* + +first FlexiDot release From 2bc0e633b3bd8ec26878f9986646b598bc0c0687 Mon Sep 17 00:00:00 2001 From: Adam Taranto Date: Thu, 12 Dec 2024 17:27:26 +1100 Subject: [PATCH 03/73] rm old changelog --- code/README.md | 150 ------------------------------------------------- 1 file changed, 150 deletions(-) delete mode 100644 code/README.md diff --git a/code/README.md b/code/README.md deleted file mode 100644 index 94489a1..0000000 --- a/code/README.md +++ /dev/null @@ -1,150 +0,0 @@ -# FlexiDot version changes - -![alt text](https://github.com/molbio-dresden/flexidot/blob/master/images/Selfdotplots_banner4.png "FlexiDot self dotplots") - -## Version 1.06 -*14.04.2019* - -* [new parameter cheat sheet v1.06](https://github.com/molbio-dresden/flexidot/blob/master/documentation/usage_v1.06.pdf) -* [new FlexiDot script v1.06](https://github.com/molbio-dresden/flexidot/blob/master/code/flexidot_v1.06.py) - - -**[Major bugfixes]:** - -We corrected a few bugs, including a bug introduced in version 1.05, affecting dotplots with substitutions allowed. We reverted (for now) to the pattern matching algorithm of version 1.04. - -
- -## Version 1.05 -*14.12.2018* - -* [new parameter cheat sheet v1.05](https://github.com/molbio-dresden/flexidot/blob/master/documentation/usage_v1.05.pdf) -* [new FlexiDot script v1.05](https://github.com/molbio-dresden/flexidot/blob/master/code/flexidot_v1.05.py) - - -**[Faster run time]:** -We modified word match recognition, speeding up FlexiDot's runtime. - - -**[New feature] New option for pairwise dotplot collages:** -With the new `-O, --only_vs_first_seq` option, it is now possible to limit the output of the pairwise dotplots. Instead of printing all possible pairwise combinations from a multi-fasta-sequence, only the pairwise comparisons against the first sequence are generated, if switched on (`-O y`). We use this feature to compare a new/unknown sequence against a batch of references. - - -**[Changed default wordsize]:** -The default wordsize has been changed from 7 to 10 in order to prevent people from running FlexiDot with small word sizes on large datasets, as this presumably takes a very long time. - - -**[Bugfixes]:** - -We fixed a few bugs with the dotplot shading legends. - -
- -## Version 1.04 -*29.06.2018* - -* [new parameter cheat sheet v1.04](https://github.com/molbio-dresden/flexidot/blob/master/documentation/usage_v1.04.pdf) -* [new FlexiDot script v1.04](https://github.com/molbio-dresden/flexidot/blob/master/code/flexidot_v1.04.py) - - -**[New feature] Graphic formatting options for all-against-all dotplots:** -On request we added two parameters: - -* With `-M/--mirror` it is now possible to mirror the middle diagonal. - - - -Basic commands: -``` -python flexidot.py -i test-seqs.fas -p 2 -M n -python flexidot.py -i test-seqs.fas -p 2 -M y -``` -Command plus aesthetics as shown here (as described in version update 1.03): -``` -python flexidot.py -i test-seqs.fas -p 2 -M n -g example2.gff3 -G gff_color.config -x y -k 10 -F 0.06 -A 1.5 -python flexidot.py -i test-seqs.fas -p 2 -M y -g example2.gff3 -G gff_color.config -x y -k 10 -F 0.06 -A 1.5 -``` -
- -* The `-R/--representation` parameter allows partial dotplotting, either printing the complete `-R 0`, the top `-R 1`, or the bottom dotplot `-R 2`. - - - -Basic commands: -``` -python flexidot.py -i test-seqs.fas -p 2 -R 0 -python flexidot.py -i test-seqs.fas -p 2 -R 1 -python flexidot.py -i test-seqs.fas -p 2 -R 2 -``` -Command plus aesthetics as shown here (as described in version update 1.03): -``` -python flexidot.py -i test-seqs.fas -p 2 -R 0 -g example2.gff3 -G gff_color.config -x y -k 10 -F 0.06 -A 1.5 -python flexidot.py -i test-seqs.fas -p 2 -R 1 -g example2.gff3 -G gff_color.config -x y -k 10 -F 0.06 -A 1.5 -python flexidot.py -i test-seqs.fas -p 2 -R 2 -g example2.gff3 -G gff_color.config -x y -k 10 -F 0.06 -A 1.5 -``` -
- -**[Bugfix]:** - -We also fixed a distortion issue in `-p/--plotting_mode 0` (self dotplots). - -
- -## Version 1.03 -*17.06.2018* - -* [new parameter cheat sheet v1.03](https://github.com/molbio-dresden/flexidot/blob/master/documentation/usage_v1.03.pdf) -* [new FlexiDot script v1.03](https://github.com/molbio-dresden/flexidot/blob/master/code/flexidot_v1.03.py) - - -**[New feature] Annotation-based shading also available for all-against-all dotplots:** -Previously only available for self dotplots, we added annotation-based shading to all-against-all dotplots, allowing for many new visualizations. As before, annotation information is provided as general feature file (GFF3). These features are added to the middle diagonal (see our example below). - - - -Basic command: -``` -python flexidot.py -i test-seqs.fas -g example2.gff3 -G gff_color.config -p 2 -``` - -Command plus aesthetics as shown here (+ LCS shading, wordsize 10, change of subplot spacing and line width): -``` -python flexidot.py -i test-seqs.fas -g example2.gff3 -G gff_color.config -p 2 -x y -k 10 -F 0.06 -A 1.5 -``` - -The test files used here are provided: -* [test-seqs.fas](https://github.com/molbio-dresden/flexidot/blob/master/test-data/test-seqs.fas) -* [example2.gff3](https://github.com/molbio-dresden/flexidot/blob/master/test-data/example2.gff3) -* [gff_color.config](https://github.com/molbio-dresden/flexidot/blob/master/test-data/gff_color.config) - -
- -## Version 1.02 -*09.05.2018* - -* [new parameter cheat sheet v1.02](https://github.com/molbio-dresden/flexidot/blob/master/documentation/usage_v1.02.pdf) -* [new FlexiDot script v1.02](https://github.com/molbio-dresden/flexidot/blob/master/code/flexidot_v1.02.py) - -Changed handling of `-T` parameter: The character count of the sequence titles has been limited to `20` by default. This limit can be changed with `-T`. If an `E` (end) is added to the limit, the last characters are chosen instead of the first. - -``` --T 20 (the first 20 characters) --T 20E (the last 20 characters) -``` -
- -## Version 1.01 -*21.04.2018* - - -* [parameter cheat sheet v1.01](https://github.com/molbio-dresden/flexidot/blob/master/documentation/usage_v1.01.pdf) -* [FlexiDot script v1.01](https://github.com/molbio-dresden/flexidot/blob/master/code/flexidot_v1.01.py) - -minor bugfixing - -
- -## Version 1.00 -*21.03.2018* - -first FlexiDot release From 443c19d64c3ce125a8fe0e991fb2d023b97707a7 Mon Sep 17 00:00:00 2001 From: Adam Taranto Date: Thu, 12 Dec 2024 17:27:43 +1100 Subject: [PATCH 04/73] init env yaml --- environment.yml | 0 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 environment.yml diff --git a/environment.yml b/environment.yml new file mode 100644 index 0000000..e69de29 From d4950b409554740e7c067362965f02a29f0e572a Mon Sep 17 00:00:00 2001 From: Adam Taranto Date: Thu, 12 Dec 2024 17:28:02 +1100 Subject: [PATCH 05/73] init pyproject toml --- pyproject.toml | 0 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 pyproject.toml diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..e69de29 From 53d4595d9c31084366fc62b9386f0a804ebb9736 Mon Sep 17 00:00:00 2001 From: Adam Taranto Date: Thu, 12 Dec 2024 17:28:34 +1100 Subject: [PATCH 06/73] update image paths --- README.md | 20 ++++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/README.md b/README.md index 9c2b99f..106fabb 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ # FlexiDot: Highly customizable, ambiguity-aware dotplots for visual sequence analyses -![alt text](https://github.com/molbio-dresden/flexidot/blob/master/images/Selfdotplots_banner4.png "FlexiDot self dotplots") +![alt text](https://github.com/molbio-dresden/flexidot/blob/master/docs/images/Selfdotplots_banner4.png "FlexiDot self dotplots") FlexiDot is a cross-platform dotplot suite generating high quality self, pairwise and all-against-all visualizations. To improve dotplot suitability for comparison of consensus and error-prone sequences, FlexiDot harbors routines for strict and relaxed handling of mismatches and ambiguous residues. The custom shading modules facilitate dotplot interpretation and motif identification by adding information on sequence annotations and sequence similarities to the images. Combined with collage-like outputs, FlexiDot supports simultaneous visual screening of a large sequence sets, allowing dotplot use for routine screening. @@ -14,7 +14,7 @@ If you use FlexiDot in your research, please cite us: ## FlexiDot versions and updates - + *We are currently working on a new version, including the long requested Python3 support. Please stay tuned.* @@ -105,7 +105,7 @@ with `-p/--plotting_mode 0` In **self** dotplot mode, each sequence is compared with itself. The resulting dotplots can be combined to form a **collage** [default] or written to separate files. -![alt text](https://github.com/molbio-dresden/flexidot/blob/master/images/Selfdotplots_banner.png "FlexiDot self dotplots") +![alt text](https://github.com/molbio-dresden/flexidot/blob/master/docs/images/Selfdotplots_banner.png "FlexiDot self dotplots") ``` python flexidot.py -i test-seqs.fas -p 0 -D y -f 1 -k 10 -w y -r y -x n -m 6 -P 15 -g example.gff3 -G gff_color.config @@ -118,7 +118,7 @@ with `-p/--plotting_mode 1` For **pairwise** dotplots, the collage output is recommended for larger numbers of sequences. The collage output of the 15 pairwise dotplots for the test sequences is shown below. By default, dotplot images are in square format (panel A). This maximizes the visibility of matches, if the compared sequences differ drastically in length. To enable scaling according to the respective sequence lengths, the FlexiDot scaling feature is callable via option `-L/--length_scaling` (panel B). If scaling is enabled, a red line indicates the end of the shorter sequence in the collage output. - + ``` Panel A$ python flexidot.py -i test-seqs.fas -p 1 -D y -f 0 -k 10 -w y -r y -m 5 -c y -L n @@ -132,7 +132,7 @@ with `-p/--plotting_mode 2` In **all-against-all** mode, FlexiDot compares each pair from a set of input sequences. To enable the identification of long shared subsequences at a glance, FlexiDot offers similarity shading (switched on/off via option `-x/--lcs_shading`) based on the LCS length in all-against-all comparisons (see below). - + ``` python flexidot.py -i test-seqs.fas -p 2 -D y -f 0 -t y -k 10 -w y -r y -x y -y 0 @@ -151,7 +151,7 @@ Secondly, a defined number of **mismatches** within the window can be allowed wi Lastly, both mismatch and ambiguity handling can be combined for the analysis. - + ``` Panel tl$ python flexidot.py -i Seq4.fas,Seq1.fas -p 1 -D n -f 0 -c n -k 10 -w n -r y -x n @@ -171,7 +171,7 @@ In FlexiDot self dotplots, annotated sequence regions can be highlighted by **sh If you wish to find out more on the gff3 file format used here, Ensembl provides a [good overview](https://www.ensembl.org/info/website/upload/gff3.html). - + ``` python flexidot.py -i Seq2.fas -p 0 -D y -f 0 -k 10 -w y -r y -x n -m 12 -P 5 -g example.gff3 -G gff_color.config @@ -181,7 +181,7 @@ python flexidot.py -i Seq2.fas -p 0 -D y -f 0 -k 10 -w y -r y -x n -m 12 -P 5 -g Previously only available for self dotplots, we added annotation-based shading to all-against-all dotplots, allowing for many new visualizations. As before, annotation information is provided as general feature file (GFF3). These features are added to the middle diagonal (see our example below). - + Basic command: ``` @@ -210,7 +210,7 @@ FlexiDot similarity shading is highly customizable with the following parameters Shading examples based on sequence orientation (forward, panel A; reverse, panel B; both, panel C) are shown: -![alt text](https://github.com/molbio-dresden/flexidot/blob/master/images/all_against_all_shaded_orientation2.png "FlexiDot shaded dotplots") +![alt text](https://github.com/molbio-dresden/flexidot/blob/master/docs/images/all_against_all_shaded_orientation2.png "FlexiDot shaded dotplots") ``` Panel A$ python flexidot.py -i test-seqs.fas -p 2 -D y -f 0 -t y -k 10 -w n -r y -x y -y 0 -z 0 @@ -224,7 +224,7 @@ When comparing related sequences, multiple sequence alignments are frequently ap In the example, LCS and matrix shading are combined to visualize the relationships between different members of a repeat family. - + ``` python flexidot.py -i Beetle.fas -p 2 -x y -k 10 -S 1 -r n -u 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