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NRsplit.py
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NRsplit.py
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import re
import argparse
from collections import defaultdict
__author__ = 'gdq'
class ParseNCBITaxonomy(object):
"""
parse taxonomy file from ncbi
input files are from ftp://ftp.ncbi.nih.gov/pub/taxonomy/
"""
def __init__(self, node_file, name_file, merged_file):
self.version = 0.1
self.node_file = node_file
self.name_file = name_file
self.merged_file = merged_file
def parse_nodes(self, node_file=None):
"""
< nodes.dmp > This file represents taxonomy nodes.
The description for each node includes the following fields:
tax_id -- node id in GenBank taxonomy database
parent tax_id -- parent node id in GenBank taxonomy database
rank -- rank of this node (superkingdom, kingdom, ...)
embl code -- locus-name prefix; not unique
division id -- see division.dmp file
inherited div flag (1 or 0) -- 1 if node inherits division from parent
genetic code id -- see gencode.dmp file
inherited GC flag (1 or 0) -- 1 if node inherits genetic code from parent
mitochondrial genetic code id -- see gencode.dmp file
inherited MGC flag (1 or 0) -- 1 if node inherits mitochondrial gencode from parent
GenBank hidden flag (1 or 0) -- 1 if name is suppressed in GenBank entry lineage
hidden subtree root flag (1 or 0) -- 1 if this subtree has no sequence data yet
comments -- free-text comments and citations
:rtype:dict
:param node_file: nodes.dmp
:return: dict, tax_id: {'parent_tax_id':123, 'rank':123,...}
"""
fileds = ['tax_id', 'parent_tax_id', 'rank', 'embl_code', 'division_id',
'inherited_div_flag', 'genetic_code_id', 'inherited_GC_flag',
'mitochondrial_genetic_code_id', 'inherited_MGC_flag',
'GenBank_hidden_flag', 'hidden_subtree_root', 'comments']
node_dict = dict()
if not node_file:
node_file = self.node_file
with open(node_file) as f:
for line in f:
if not line.strip():
continue
tmp_list = line.strip().replace('\t', '').split('|')[:-1]
# tmp_dict = dict(zip(fileds, tmp_list))
tmp_dict = dict(zip(fileds[0:3], tmp_list))
tax_id = tmp_dict.pop('tax_id')
node_dict[tax_id] = tmp_dict
return node_dict
def parse_names(self, name_file=None, target='scientific name'):
"""
< names.dmp > Taxonomy names file has these fields:
tax_id -- the id of node associated with this name
name_txt -- name itself
unique name -- the unique variant of this name if name not unique
name class -- (synonym, common name, ...)
:param name_file: names.dmp
:param target: str, target name to be extracted
:return: dict, tax_id: {'name_txt': xxx, 'name_class': xxx}
"""
fileds = ['tax_id', 'name_txt', 'unique_name', 'name_class']
name_dict = dict()
if not name_file:
name_file = self.name_file
with open(name_file) as f:
for line in f:
if not line.strip():
continue
tmp_list = line.strip().replace('\t', '').split('|')[:-1]
if tmp_list[-1] == target:
tmp_dict = dict(zip(fileds, tmp_list))
tax_id = tmp_dict.pop('tax_id')
name_dict[tax_id] = tmp_dict
return name_dict
def parse_merged(self, merged_file=None):
"""
parse merged.dmp file into dict
:param merged_file:
Merged nodes file (merged.dmp):
old_tax_id -- id of nodes which has been merged
new_tax_id -- id of nodes which is result of merging
----------------------------------------------
12 | 74109 |
30 | 29 |
36 | 184914 |
37 | 42 |
----------------------------------------------
:return: {old_tax_id: new_tax_id}
"""
if not merged_file:
merged_file = self.merged_file
old2new = dict()
with open(merged_file) as f:
for line in f:
if not line.strip():
continue
tmp_list = line.strip('\n').replace('\t', '').split('|')[:-1]
old2new[tmp_list[0]] = tmp_list[1]
return old2new
def get_children_nodes(self, parent_nodes, node_file=None, node_dict=None):
"""
Obtain all child node for a specific parent node
:param node_file: nodes.dmp
:param parent_nodes: str or list, example ['32199',]
:param node_dict: result from self.parse_nodes.
:return: set, {child_tax_id1, child_tax_id2,...}
"""
if not node_dict:
if not node_file:
node_file = self.node_file
node_dict = self.parse_nodes(node_file)
if isinstance(parent_nodes, str):
parent_nodes = [parent_nodes]
children_set = set(parent_nodes)
children_set_update = children_set.update
while True:
children = set()
for n in node_dict:
if node_dict[n]['parent_tax_id'] in parent_nodes:
children.add(n)
if children:
children_set_update(children)
parent_nodes = set(children)
else:
break
return children_set
def children_set_calculator(self, reg, node_dict=None):
"""
Only + and - are allowed for set calculation.
:param reg: such as '2759-4751-33090' or simply '2759'
:param node_dict: node dict
:return: set
"""
operations = re.findall(r'\d+([-+])', reg)
node_list = re.split('[-+]', reg)
if not operations:
return self.get_children_nodes(node_list, node_dict=node_dict)
else:
children_set = self.get_children_nodes(node_list[0], node_dict=node_dict)
for oper, node in zip(operations, node_list[1:]):
if oper == '+' or oper == "&":
children_set = children_set & self.get_children_nodes(node, node_dict=node_dict)
elif oper == '-':
children_set = children_set - self.get_children_nodes(node, node_dict=node_dict)
return children_set
def get_tax_id_of_taxon(self, node_file=None, taxon='all'):
"""
query tax_id of a taxon
:param taxon: could be anyone of: class cohort family forma genus infraclass infraorder kingdom order
parvorder phylum species 'species group' 'species subgroup' subclass subfamily subgenus subkingdom
suborder subphylum subspecies subtribe superclass superfamily superkingdom superorder
superphylum tribe varietas
:param node_file: nodes.dmp
:return: dict
"""
if not node_file:
node_file = self.node_file
node_dict = self.parse_nodes(node_file)
taxon_tax_id_dict = defaultdict(set)
for n in node_dict:
one_taxon = node_dict[n]['rank']
taxon_tax_id_dict[one_taxon].add(n)
if taxon == 'all':
return taxon_tax_id_dict
else:
if taxon in taxon_tax_id_dict:
return taxon_tax_id_dict[taxon]
else:
print(taxon + ' not found')
@staticmethod
def prot_accession2tax_id(prot2tax_file):
"""
parse prot.accession2taxid.gz into dict.
---------------------------------------------------
prot2tax_file:
accession accession.version taxid gi
APZ74649 APZ74649.1 36984 1137646701
AQT41667 AQT41667.1 1686310 1150388099
WP_080502060 WP_080502060.1 95486 1169627919
......
---------------------------------------------------
:param prot2tax_file:
:return: dict, {prot_id: tax_id, ...}, Protein with tax_id=0 will be filtered.
"""
with open(prot2tax_file) as f:
_ = f.readline()
prot2tax_dict = dict()
for line in f:
if not line.strip():
continue
tmp_list = line.strip('\n').split('\t')
if not tmp_list[2] == '0':
# protein are not classified.
prot2tax_dict[tmp_list[1]] = tmp_list[2]
return prot2tax_dict
@staticmethod
def fasta_parser(fasta):
"""
yield seq_name, sequence
:param fasta:
:return: seqname, sequence('\n' were kept)
"""
with open(fasta) as f:
match_pattern = re.compile(r'>([^\s]+)').match
seq_name, sequence, seq_num, desc = '', '', 0, ''
for line in f:
if (not line.strip()) or line.startswith('#'):
continue
if line.startswith('>'):
seq_num += 1
if seq_num >= 2:
yield seq_name, desc, sequence
sequence = ''
seq_name = match_pattern(line).group(1)
desc = line.lstrip('>'+seq_name).strip()
else:
sequence += line # "\n" still contained
else:
yield seq_name, desc, sequence
@staticmethod
def get_seq_names_from_fasta(fasta):
match_pattern = re.compile(r'>([^\s]+)').match
with open(fasta) as f:
seq_names = set()
for line in f:
if line.startswith('>'):
m = match_pattern(line)
if m:
name = m.group(1)
seq_names.add(name)
return seq_names
@staticmethod
def get_kingdom_taxid():
"""
List tax_id of kingdom and super-kingdom
:return: dict
"""
# three kingdom
kingdom_dict = dict(
fungi_tax_id='4751',
viridiplantae_tax_id='33090',
metazoa_tax_id='33208',
# five super-kingdom
bacteria_tax_id='2',
archaea_tax_id='2157',
eukaryota_tax_id='2759',
viruses_tax_id='10239',
viroids_tax_id='12884',
protist='2759-4751-33090-33208')
return kingdom_dict
def nr_split(self, name2taxid_dict, prot2tax_file, fasta_file, name_file=None,
node_file=None, merged_file=None):
"""
Split fasta file of NR.fa according to input name2taxid_dict. For each tax_id in the dict,
its children tax nodes will be find first, and proteins associated with these children tax
nodes will be found subsequently. finally, fasta for these proteins will be extracted.
:param name2taxid_dict: dict, such as {'scientific_name':tax_id, ...}
:param prot2tax_file: unzipped file of prot.accession2taxid.gz
:param fasta_file: NR fasta file from ncbi
:param name_file: names.dmp file from ncbi
:param node_file: nodes.dmp file from ncbi
:param merged_file: merged.dmp file from ncbi
:return: None, but fasta files will be generated.
"""
f = open('not_classified_protein.list', 'w')
f.write('not_classified_id\twhy_not_classified\n')
prot2tax_dict = self.prot_accession2tax_id(prot2tax_file)
name_dict = self.parse_names(name_file=name_file, target='scientific name')
old2new_dict = self.parse_merged(merged_file=merged_file)
# to reduce the size of dict, and replace the old id with new id
seq2tax = dict()
seq_set = self.get_seq_names_from_fasta(fasta_file)
for key in seq_set:
tmp_tax_id = prot2tax_dict.get(key)
if not tmp_tax_id:
f.write(key + '\tIt was not found in prot.accession2taxid\n')
continue
else:
# if tmp_tax_id is old, then new tax id will replace it
new_tax_id = old2new_dict.get(tmp_tax_id)
if new_tax_id:
tmp_tax_id = new_tax_id
tmp_tax_name = name_dict.get(tmp_tax_id)
if not tmp_tax_name:
sci_name = 'None'
print('tax_id {} of {} was not in names.dmp'.format(tmp_tax_id, key))
else:
sci_name = tmp_tax_name['name_txt']
seq2tax[key] = (tmp_tax_id, sci_name)
# get tax ids for each target and generate file objects
target_children_taxid_dict = dict()
file_obj_dict = dict()
node_dict = self.parse_nodes(node_file=node_file)
for tax_name in name2taxid_dict:
tmp_tax_name = tax_name.split('_tax_id')[0]
file_obj_dict[tax_name] = [open(tmp_tax_name+'.fa', 'w'), open(tmp_tax_name+'.prot_taxId_scientificName.txt', 'w')]
tmp_tax_id = name2taxid_dict[tax_name]
target_children_taxid_dict[tax_name] = self.children_set_calculator(tmp_tax_id, node_dict=node_dict)
# begin splitting
for seq_name, desc, sequence in self.fasta_parser(fasta_file):
if seq_name in seq2tax:
prot_tax_id, sci_name = seq2tax.pop(seq_name)
else:
continue
# write info
classified_num = 0
for tax_name in target_children_taxid_dict:
if prot_tax_id in target_children_taxid_dict[tax_name]:
# if scientific name and tax id are wanted, using the following line
# file_obj_dict[tax_name].write('>'+seq_name+' ['+prot_tax_id+':'+sci_name+'] '+desc+'\n '+sequence)
file_obj_dict[tax_name][0].write('>'+seq_name+' '+desc+'\n'+sequence)
file_obj_dict[tax_name][1].write('{}\t{}\t{}\n'.format(seq_name, prot_tax_id, sci_name))
classified_num += 1
if classified_num == 0:
f.write(seq_name + '\tits tax_id {} was not classified as any of target '
'taxonomies\n'.format(prot_tax_id))
f.close()
# close file objects
for obj_name in file_obj_dict:
file_obj_dict[obj_name][0].close()
file_obj_dict[obj_name][1].close()
if __name__ == "__main__":
import time
start_time = time.time()
parser = argparse.ArgumentParser(description="parse taxonomy from ftp://ftp.ncbi.nih.gov/pub/taxonomy/")
parser.add_argument('-node', type=str, required=True, help="nodes.dmp file from ncbi")
parser.add_argument('-name', type=str, required=True, help='names.dmp file from ncbi')
parser.add_argument('-merged', type=str, required=True, help='merged.dmp file from ncbi')
parser.add_argument('-pro2tax', type=str, required=True, help="unzipped file of prot.accession2taxid.gz")
parser.add_argument('-nr', metavar="NR.fa", type=str, required=True, help="NR fasta file from ncbi")
args = parser.parse_args()
worker = ParseNCBITaxonomy(args.node, args.name, args.merged)
target2taxid_dict = worker.get_kingdom_taxid()
worker.nr_split(target2taxid_dict, args.pro2tax, args.nr, name_file=args.name,
node_file=args.node, merged_file=args.merged)
end_time = time.time()
print("It takes {} seconds to do the work".format(end_time-start_time))