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plot_pancore_matrix.pl
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plot_pancore_matrix.pl
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#!/usr/bin/env perl
# 2014-21 Bruno Contreras-Moreira (1) and Pablo Vinuesa (2):
# 1: http://www.eead.csic.es/compbio (Estacion Experimental Aula Dei/CSIC/Fundacion ARAID, Spain)
# 2: http://www.ccg.unam.mx/~vinuesa (Center for Genomic Sciences, UNAM, Mexico)
# This script can be used to plot pan/core charts from .tab files generated by get_homologues.pl -c
# Produces PDF, SVG and PNG plots and a text report, and requires R (http://www.r-project.org)
$|=1;
use strict;
use warnings;
use File::Basename;
use Getopt::Std;
use File::Path qw(remove_tree);
use FindBin '$Bin';
use lib "$Bin/lib";
use lib "$Bin/lib/bioperl-1.5.2_102/";
use phyTools;
my $VERBOSE = 0; # set to 1 to see R messages, helping explain why fitting fails
my @FEATURES2CHECK = ('EXE_R');
my ($INP_tabfile,$INP_fittype,$INP_anim_dir,$INP_y,$INP_x) = ('','core_Tettelin','','','');
my ($Rparams,$FontScale,%opts) = ('',0.8);
my ($pancore_output_png,$pancore_output_pdf,$pancore_output_svg,$pancore_output_txt);
#my ($yfirst,$ylast) = ('','');
getopts('hi:f:F:a:y:x:', \%opts);
if(($opts{'h'})||(scalar(keys(%opts))==0))
{
print "\n[options]: \n";
print "-h \t this message\n";
print "-i \t input .tab data file (required, generated by get_homologues.pl)\n";
print "-f \t type of fit [pan|core_Tettelin|core_Willenbrock|core_both]\n".
" \t (default: core_Tettelin, PubMed:16172379,18088402)\n";
print "-F \t font scale for fitted formulas (optional, default=$FontScale)\n";
print "-a \t save snapshots for animations in dir (optional, example: -a animation)\n";
#print "-y \r ylim for R plot (optional, example: -y 1:10000)\n";
#print "-x \r xlim for R plot (optional, example: -x 1:20)\n";
exit(-1);
}
if(defined($opts{'f'}))
{
$INP_fittype = $opts{'f'};
if("pan|core_Tettelin|core_Willenbrock|core_both" !~ /$INP_fittype/)
{
die "# $0 : valid -f choices are: [pan|core_Tettelin|core_Willenbrock|core_both]\n";
}
}
if(defined($opts{'i'}))
{
$INP_tabfile = $opts{'i'};
$pancore_output_png = $INP_tabfile . '_'.$INP_fittype.'.png';
$pancore_output_pdf = $INP_tabfile . '_'.$INP_fittype.'.pdf';
$pancore_output_svg = $INP_tabfile . '_'.$INP_fittype.'.svg';
$pancore_output_txt = $INP_tabfile . '_'.$INP_fittype.'.log';
}
else{ die "\n# $0 : need -i parameter, exit\n"; }
if(defined($opts{'F'}))
{
if($opts{'F'}>0){ $FontScale = $opts{'F'} }
}
if(defined($opts{'a'}))
{
$INP_anim_dir = $opts{'a'};
if(-e $INP_anim_dir)
{
print "# $0 : existing directory '$INP_anim_dir' will be removed\n";
remove_tree($INP_anim_dir);
}
print "# $0 : creating directory $INP_anim_dir\n";
mkdir($INP_anim_dir);
}
check_installed_features(@FEATURES2CHECK);
if(!feature_is_installed('R'))
{
die "# $0 : this script requires the software R to be installed; please install it (http://www.r-project.org)\n";
} # check X server is ok?
if(!$VERBOSE){ $Rparams = '-q 2>&1 > /dev/null' }
printf("\n# %s -i %s -f %s -F %1.2f -a %s\n",
$0,$INP_tabfile,$INP_fittype,$FontScale,$INP_anim_dir);
#################################### MAIN PROGRAM ################################################
if($INP_fittype =~ /pan/)
{
plot_pan_genome($INP_tabfile,$pancore_output_txt,$pancore_output_png,
$pancore_output_pdf,$pancore_output_svg,$INP_anim_dir);
}
elsif($INP_fittype =~ /core_both/)
{
plot_core_genome($INP_tabfile,$pancore_output_txt,$pancore_output_png,
$pancore_output_pdf,$pancore_output_svg,'core_both',$INP_anim_dir);
}
elsif($INP_fittype =~ /core_Willenbrock/)
{
plot_core_genome($INP_tabfile,$pancore_output_txt,$pancore_output_png,
$pancore_output_pdf,$pancore_output_svg,'core_Willenbrock',$INP_anim_dir);
}
else
{
plot_core_genome($INP_tabfile,$pancore_output_txt,$pancore_output_png,
$pancore_output_pdf,$pancore_output_svg,'core_Tettelin',$INP_anim_dir);
}
print "# outfiles: $pancore_output_txt , $pancore_output_png , $pancore_output_pdf , $pancore_output_svg\n";
sub plot_core_genome
{
my ($data_file,$TXTfile,$PNGfile,$PDFfile,$SVGfile,$fittype,$anim_dir) = @_;
my (@genomes,@genes,$g,$expterm,$exptermeq,$expterm2,$exptermeq2,$max,$min,$n_of_genomes,$n_of_replicates);
my $deftauc = 2.8;
my $deftaucstep = 0.2;
if($fittype && $fittype eq 'core_both')
{
$expterm = '-genomes';
$exptermeq = '-g';
$expterm2 = '-sqrt(sqrt(genomes))';
$exptermeq2 = '-sqrt(sqrt(g))';
}
elsif($fittype && $fittype eq 'core_Willenbrock')
{
$expterm = '-sqrt(sqrt(genomes))';
$exptermeq = '-sqrt(sqrt(g))';
}
else
{
$fittype = 'core_Tettelin'; # default Tettelin et al PNAS 2005
$expterm = '-genomes';
$exptermeq = '-g';
}
unlink($PNGfile,$PDFfile,$SVGfile);
# 1) read input file in boxplot format
$n_of_replicates = 0;
open(DATA,$data_file) || die "# plot_core_genome : cannot read $data_file\n";
while(<DATA>)
{
$_ =~ s/\n|\r//g; # 11032014 MartinTay@ntu.edu.sg
my @data = split(/\t/,$_);
if(/^g\d/){ $n_of_genomes = scalar(@data); next }
for($g=0;$g<scalar(@data);$g++)
{
next if($data[$g] eq '');
push(@genomes,$g+1);
push(@genes,$data[$g]);
}
$n_of_replicates++;
}
close(DATA);
# 2) write temporary input file in data frame format and get max,min gene numbers
my $tmpfile = '_tmp'.basename($data_file);
open(TMP,">$tmpfile");
print TMP "genomes\tgenes\n";
for($g=0;$g<scalar(@genes);$g++){ print TMP "$genomes[$g]\t$genes[$g]\n"; }
close(TMP);
@genes = sort{$a<=>$b}(@genes);
$min = $genes[0];
$max = $genes[$#genes];
# 3) call R and find best fit(s)
if($fittype eq 'core_both')
{
open(RSHELL,"|R --no-save $Rparams ") || die "# plot_core_genome : cannot call R: $!\n";
print RSHELL<<EOF;
core = read.table('$tmpfile',header=T,sep='\t');
txtreport = file('$TXTfile',"w");
# first try Tettelin fit
tauc_value = $deftauc + $deftaucstep;
converged = FALSE;
while(converged == FALSE && tauc_value > 0)
{
param_guess = list(omegac=$max,kc=$min,tauc=tauc_value);
try(
{
fit = nls('genes ~ omegac + kc * exp($expterm/tauc)',data=core,start=param_guess);
sumfit = summary(fit);
converged = sumfit\$convInfo[1]\$isConv;
} ,
silent=TRUE); # set to FALSE to see detailed nls fitting messages
tauc_value = tauc_value - $deftaucstep;
}
if(converged == TRUE)
{
SER = sumfit\$sigma;
coeffs = coef(fit);
ffit = function(genomes) coeffs['omegac'] + coeffs['kc'] * exp($expterm/coeffs['tauc']);
if(coeffs['kc'] > 1)
{
fiteq = substitute(
coregenes(g) == omegac + kc ~ exp(frac($exptermeq,tauc)) , \
list(
omegac=sprintf("%1.0f", coeffs['omegac']), \
kc = sprintf("%1.0f", coeffs['kc']), \
tauc = sprintf("%1.2f",coeffs['tauc'])
)
)
}
else
{
fiteq = substitute(
coregenes(g) == omegac - kc ~ exp(frac($exptermeq,tauc)) , \
list(
omegac=sprintf("%1.0f", coeffs['omegac']), \
kc = sprintf("%1.0f",-coeffs['kc']), \
tauc = sprintf("%1.2f",coeffs['tauc'])
)
)
}
writeLines("# core_Tettelin fit converged", txtreport);
writeLines(sprintf("# residual standard error = %1.2f",SER), txtreport);
writeLines( paste(fiteq) , txtreport, sep=" " );
writeLines( "" , txtreport);
fittedvalues = lapply( 1:$n_of_genomes, ffit)
writeLines( "# fitted values (genomes, genes) :" , txtreport );
for(i in 1:$n_of_genomes ) {
writeLines( sprintf("%d\t%1.1f",i,fittedvalues[i]) , txtreport );
}
} else {
writeLines("# core_Tettelin fit failed to converge", txtreport)
}
## now try Willenbrock fit
tauc_value2 = $deftauc + $deftaucstep;
converged2 = FALSE;
while(converged2 == FALSE && tauc_value2 > 0)
{
param_guess = list(omegac=$max,kc=$min,tauc=tauc_value2);
try(
{
fit2 = nls('genes ~ omegac + kc * exp($expterm2/tauc)',data=core,start=param_guess);
sumfit2 = summary(fit2);
converged2 = sumfit2\$convInfo[1]\$isConv;
} ,
silent=TRUE);
tauc_value2 = tauc_value2 - $deftaucstep;
}
if(converged2 == TRUE)
{
SER2 = sumfit2\$sigma;
coeffs2 = coef(fit2);
ffit2 = function(genomes) coeffs2['omegac'] + coeffs2['kc'] * exp($expterm2/coeffs2['tauc']);
if(coeffs2['kc'] > 1)
{
fiteq2 = substitute(
coregenes(g) == omegac + kc ~ exp(frac($exptermeq2,tauc)) , \
list(
omegac=sprintf("%1.0f",coeffs2['omegac']), \
kc = sprintf("%1.0f",coeffs2['kc']), \
tauc = sprintf("%1.2f",coeffs2['tauc'])
)
)
}
else
{
fiteq2 = substitute(
coregenes(g) == omegac - kc ~ exp(frac($exptermeq2,tauc)) , \
list(
omegac=sprintf("%1.0f",coeffs2['omegac']), \
kc = sprintf("%1.0f",-coeffs2['kc']), \
tauc = sprintf("%1.2f",coeffs2['tauc'])
)
)
}
writeLines("# core_Willenbrock fit converged", txtreport);
writeLines(sprintf("# residual standard error = %1.2f",SER2), txtreport);
writeLines( paste(fiteq2) , txtreport, sep=" " );
writeLines( "" , txtreport);
fittedvalues = lapply( 1:$n_of_genomes, ffit2)
writeLines( "# fitted values (genomes, genes) :" , txtreport );
for(i in 1:$n_of_genomes ) {
writeLines( sprintf("%d\t%1.1f",i,fittedvalues[i]) , txtreport );
}
} else {
writeLines("# core_Willenbrock fit failed to converge", txtreport)
}
close(txtreport);
# actually make charts
pdf(file="$PDFfile");
plot(core\$genomes,core\$genes,xaxt='n',xlab='genomes (g)',ylab='core genome size (genes)',pch=20);
xaxis_labels = 1:$n_of_genomes;
axis(side=1,at=xaxis_labels);
if(converged == TRUE)
{
curve( ffit , from=1, to=max(core\$genomes), add=T, col="red" );
mtext(fiteq,side=3,cex=$FontScale,line=0.5, col="red");
#mtext(sprintf("residual standard error = %1.2f",SER),side=4,cex=0.8,line=0.5)
}
if(converged2 == TRUE)
{
curve( ffit2 , from=1, to=max(core\$genomes), add=T, col="blue" );
mtext(fiteq2,side=3,cex=$FontScale,line=-2.5, col="blue");
#mtext(sprintf("residual standard error = %1.2f",SER),side=4,cex=0.8,line=0.5)
}
dev.off()
png(file="$PNGfile");
plot(core\$genomes,core\$genes,xaxt='n',xlab='genomes (g)',ylab='core genome size (genes)',pch=20);
axis(side=1,at=xaxis_labels);
if(converged == TRUE)
{
curve( ffit , from=1, to=max(core\$genomes), add=T, col="red" );
mtext(fiteq,side=3,cex=$FontScale,line=0.5, col="red");
#mtext(sprintf("residual standard error = %1.2f",SER),side=4,cex=0.8,line=0.5)
}
if(converged2 == TRUE)
{
curve( ffit2 , from=1, to=max(core\$genomes), add=T, col="blue" );
mtext(fiteq2,side=3,cex=$FontScale,line=-2.5, col="blue");
#mtext(sprintf("residual standard error = %1.2f",SER),side=4,cex=0.8,line=0.5)
}
dev.off()
svg(file="$SVGfile");
plot(core\$genomes,core\$genes,xaxt='n',xlab='genomes (g)',ylab='core genome size (genes)',pch=20);
axis(side=1,at=xaxis_labels);
if(converged == TRUE)
{
curve( ffit , from=1, to=max(core\$genomes), add=T, col="red" );
mtext(fiteq,side=3,cex=$FontScale,line=0.5, col="red");
#mtext(sprintf("residual standard error = %1.2f",SER),side=4,cex=0.8,line=0.5)
}
if(converged2 == TRUE)
{
curve( ffit2 , from=1, to=max(core\$genomes), add=T, col="blue" );
mtext(fiteq2,side=3,cex=$FontScale,line=-2.5, col="blue");
#mtext(sprintf("residual standard error = %1.2f",SER),side=4,cex=0.8,line=0.5)
}
dev.off()
# make animation pics if required
# based on http://www.r-bloggers.com/animated-plots-with-r/
anim_dir = "$anim_dir"
if(file.exists(anim_dir))
{
i = 0
picname = ''
# add first sampling replicate
genomes = core\$genomes[1:$n_of_genomes]
genes = core\$genes[1:$n_of_genomes]
for(i in 1:$n_of_genomes){
if (i < 10) { picname = paste(anim_dir,'/000',i,'plot.png',sep='')}
if (i < 100 && i >= 10) { picname = paste(anim_dir,'/00',i,'plot.png', sep='')}
if (i >= 100) { picname = paste(anim_dir,'/0', i,'plot.png', sep='')}
colors = c( rep("green",i) , rep("white",$n_of_genomes-i) )
png(picname);
plot(genomes,genes,xaxt='n',xlab='genomes (g)',ylab='core genome size (genes)',
pch=20, col=colors, main=paste("Genomes/transcriptomes added=",i," replicates=",1));
axis(side=1,at=xaxis_labels);
dev.off()
}
# remaining replicates
for(r in 2:$n_of_replicates){
last = r*$n_of_genomes
genomes = core\$genomes[1:last]
genes = core\$genes[1:last]
i=last
colors = c( rep("black",(r-1)*$n_of_genomes) , rep("green",$n_of_genomes) )
if (i < 10) { picname = paste(anim_dir,'/000',i,'plot.png',sep='')}
if (i < 100 && i >= 10) { picname = paste(anim_dir,'/00',i,'plot.png', sep='')}
if (i >= 100) { picname = paste(anim_dir,'/0', i,'plot.png', sep='')}
png(picname);
plot(genomes,genes,xaxt='n',xlab='genomes (g)',ylab='core genome size (genes)',
pch=20, col=colors, main=paste("Genomes/transcriptomes added=",last," replicates=",r));
axis(side=1,at=xaxis_labels);
dev.off()
}
# final plot
png(picname);
plot(genomes,genes,xaxt='n',xlab='genomes (g)',ylab='core genome size (genes)',pch=20);
axis(side=1,at=xaxis_labels);
if(converged == TRUE)
{
curve( ffit , from=1, to=max(core\$genomes), add=T, col="red" );
mtext(fiteq,side=3,cex=$FontScale,line=0.5, col="red");
}
if(converged2 == TRUE)
{
curve( ffit2 , from=1, to=max(core\$genomes), add=T, col="blue" );
mtext(fiteq2,side=3,cex=$FontScale,line=-2.5, col="blue");
}
dev.off()
}
q()
EOF
close RSHELL;
}
else
{
open(RSHELL,"|R --no-save $Rparams ") || die "# plot_core_genome : cannot call R: $!\n";
print RSHELL<<EOF;
core = read.table('$tmpfile',header=T,sep='\t');
txtreport = file('$TXTfile',"w");
tauc_value = $deftauc + $deftaucstep;
converged = FALSE;
while(converged == FALSE && tauc_value > 0)
{
param_guess = list(omegac=$max,kc=$min,tauc=tauc_value);
try(
{
fit = nls('genes ~ omegac + kc * exp($expterm/tauc)', data=core,start=param_guess);
sumfit = summary(fit);
converged = sumfit\$convInfo[1]\$isConv;
} ,
silent=TRUE); # set to FALSE to see detailed nls fitting messages
tauc_value = tauc_value - $deftaucstep;
}
if(converged == TRUE)
{
SER = sumfit\$sigma;
coeffs = coef(fit);
ffit = function(genomes) coeffs['omegac'] + coeffs['kc'] * exp($expterm/coeffs['tauc']);
if(coeffs['kc'] > 1)
{
fiteq = substitute(
coregenes(g) == omegac + kc ~ exp(frac($exptermeq,tauc)) , \
list(
omegac=sprintf("%1.0f",coeffs['omegac']), \
kc = sprintf("%1.0f",coeffs['kc']), \
tauc = sprintf("%1.2f",coeffs['tauc'])
)
)
}
else
{
fiteq = substitute(
coregenes(g) == omegac - kc ~ exp(frac($exptermeq,tauc)) , \
list(
omegac=sprintf("%1.0f",coeffs['omegac']), \
kc = sprintf("%1.0f",-coeffs['kc']), \
tauc = sprintf("%1.2f",coeffs['tauc'])
)
)
}
writeLines( "# $fittype fit converged" , txtreport );
writeLines(sprintf("# residual standard error = %1.2f",SER), txtreport);
writeLines( paste(fiteq) , txtreport, sep=" " );
writeLines( "" , txtreport);
fittedvalues = lapply( 1:$n_of_genomes, ffit)
writeLines( "# fitted values (genomes, genes) :" , txtreport );
for(i in 1:$n_of_genomes ) {
writeLines( sprintf("%d\t%1.1f",i,fittedvalues[i]) , txtreport );
}
} else {
writeLines( "# $fittype failed to converge", txtreport )
}
close(txtreport);
# actually make charts
pdf(file="$PDFfile");
plot(core\$genomes,core\$genes,xaxt='n',xlab='genomes (g)',ylab='core genome size (genes)',pch=20);
xaxis_labels = 1:$n_of_genomes;
axis(side=1,at=xaxis_labels);
if(converged == TRUE)
{
curve( ffit , from=1, to=max(core\$genomes), add=T, col="red" );
mtext(fiteq,side=3,cex=$FontScale,line=0.5);
mtext(sprintf("residual standard error = %1.2f",SER),side=4,cex=$FontScale,line=0.5)
}
dev.off()
png(file="$PNGfile");
plot(core\$genomes,core\$genes,xaxt='n',xlab='genomes (g)',ylab='core genome size (genes)',pch=20);
axis(side=1,at=xaxis_labels);
if(converged == TRUE)
{
curve( ffit , from=1, to=max(core\$genomes), add=T, col="red" );
mtext(fiteq,side=3,cex=$FontScale,line=0.5);
mtext(sprintf("residual standard error = %1.2f",SER),side=4,cex=$FontScale,line=0.5)
}
dev.off()
svg(file="$SVGfile");
plot(core\$genomes,core\$genes,xaxt='n',xlab='genomes (g)',ylab='core genome size (genes)',pch=20);
axis(side=1,at=xaxis_labels);
if(converged == TRUE)
{
curve( ffit , from=1, to=max(core\$genomes), add=T, col="red" );
mtext(fiteq,side=3,cex=$FontScale,line=0.5);
mtext(sprintf("residual standard error = %1.2f",SER),side=4,cex=$FontScale,line=0.5)
}
dev.off()
# make animation pics if required
anim_dir = "$anim_dir"
if(file.exists(anim_dir))
{
i = 0
picname = ''
# add first sampling replicate
genomes = core\$genomes[1:$n_of_genomes]
genes = core\$genes[1:$n_of_genomes]
for(i in 1:$n_of_genomes){
if (i < 10) { picname = paste(anim_dir,'/000',i,'plot.png',sep='')}
if (i < 100 && i >= 10) { picname = paste(anim_dir,'/00',i,'plot.png', sep='')}
if (i >= 100) { picname = paste(anim_dir,'/0', i,'plot.png', sep='')}
colors = c( rep("green",i) , rep("white",$n_of_genomes-i) )
png(picname);
plot(genomes,genes,xaxt='n',xlab='genomes (g)',ylab='core genome size (genes)',
pch=20, col=colors, main=paste("Genomes/transcriptomes added=",i," replicates=",1));
axis(side=1,at=xaxis_labels);
dev.off()
}
# remaining replicates
for(r in 2:$n_of_replicates){
last = r*$n_of_genomes
genomes = core\$genomes[1:last]
genes = core\$genes[1:last]
i=last
colors = c( rep("black",(r-1)*$n_of_genomes) , rep("green",$n_of_genomes) )
if (i < 10) { picname = paste(anim_dir,'/000',i,'plot.png',sep='')}
if (i < 100 && i >= 10) { picname = paste(anim_dir,'/00',i,'plot.png', sep='')}
if (i >= 100) { picname = paste(anim_dir,'/0', i,'plot.png', sep='')}
png(picname);
plot(genomes,genes,xaxt='n',xlab='genomes (g)',ylab='core genome size (genes)',
pch=20, col=colors, main=paste("Genomes/transcriptomes added=",last," replicates=",r));
axis(side=1,at=xaxis_labels);
dev.off()
}
# final plot
png(picname);
plot(genomes,genes,xaxt='n',xlab='genomes (g)',ylab='core genome size (genes)',pch=20);
axis(side=1,at=xaxis_labels);
if(converged == TRUE)
{
curve( ffit , from=1, to=max(core\$genomes), add=T, col="red" );
mtext(fiteq,side=3,cex=$FontScale,line=0.5);
mtext(sprintf("residual standard error = %1.2f",SER),side=4,cex=$FontScale,line=0.5)
}
dev.off()
}
q()
EOF
close RSHELL;
}
# print summary of animation folder
if(-s $anim_dir)
{
opendir(ANIMDIR,$anim_dir) || die "# $0 : cannot list $anim_dir\n";
my @snapshots = grep{/\.png/} readdir(ANIMDIR);
closedir(ANIMDIR);
if(@snapshots)
{
printf("\n# %d animation pics available in folder '%s'\n\n",scalar(@snapshots),$anim_dir);
}
}
# 4) clean
unlink($tmpfile);
# 5) check outcome
if(!-s $PDFfile && !-s $PNGfile)
{
die "# plot_core_genome : ERROR, cannot plot data\n";
}
}
sub plot_pan_genome
{
my ($data_file,$TXTfile,$PNGfile,$PDFfile,$SVGfile,$anim_dir) = @_;
my (@genomes,@genes,$g,$min,$n_of_genomes,$n_of_replicates);
my $deftaup = 2.5; #Tettelin et al PNAS 2005
my $defthetap = 33;
my $defkp = 476;
my $deftaupstep = 0.2;
unlink($PNGfile,$PDFfile);
# 1) read input file in boxplot format
$n_of_replicates = 0;
open(DATA,$data_file) || die "# plot_pan_genome : cannot read $data_file\n";
while(<DATA>)
{
chomp($_);
my @data = split(/\t/,$_);
if(/^g\d/){ $n_of_genomes = scalar(@data); next }
for($g=0;$g<scalar(@data);$g++)
{
next if($data[$g] eq '');
push(@genomes,$g+1);
push(@genes,$data[$g]);
}
$n_of_replicates++;
}
close(DATA);
# 2) write temporary input file in data frame format and get max,min gene numbers
my $tmpfile = '_tmp'.basename($data_file);
open(TMP,">$tmpfile");
print TMP "genomes\tgenes\n";
for($g=0;$g<scalar(@genes);$g++){ print TMP "$genomes[$g]\t$genes[$g]\n"; }
close(TMP);
@genes = sort{$a<=>$b}(@genes);
$min = $genes[0];
# 3) call R and find best fit
open(RSHELL,"|R --no-save $Rparams") || die "# plot_pan_genome : cannot call R: $!\n";
print RSHELL<<EOF;
pan = read.table('$tmpfile',header=T,sep='\t');
txtreport = file('$TXTfile',"w");
taup_value = $deftaup + $deftaupstep;
function_string = 'genes ~ omegap + thetap*(genomes-1) + kp * \
exp(-2/taup) * ((1-exp(-(genomes-1)/taup))/(1-exp(-1/taup)))'
converged = FALSE;
while(converged == FALSE && taup_value > 0)
{
param_guess = list(omegap=$min,thetap=$defthetap,kp=$defkp,taup=taup_value);
try(
{
fit = nls(function_string,data=pan,start=param_guess);
sumfit = summary(fit);
converged = sumfit\$convInfo[1]\$isConv;
} ,
silent=TRUE); # set to FALSE to see detailed nls fitting messages
taup_value = taup_value - $deftaupstep;
}
if(converged == TRUE)
{
SER = sumfit\$sigma;
coeffs = coef(fit);
ffit = function(genomes) coeffs[1] + coeffs[2]*(genomes-1) + \
coeffs[3] * exp(-2/coeffs[4]) * ((1-exp(-(genomes-1)/coeffs[4]))/(1-exp(-1/coeffs[4])))
if(coeffs['thetap'] > 1 && coeffs['kp'] > 1)
{
fiteq = substitute(
pangenes(g) == omegap + thetap * (g-1) + kp ~ exp(frac(-2,taup)) ~ frac(1-exp(frac(-(g-1),taup)),1- exp(frac(-1,taup))), \
list(
omegap=sprintf("%1.0f",coeffs['omegap']), \
thetap=sprintf("%1.1f",coeffs['thetap']), \
kp = sprintf("%1.0f",coeffs['kp']), \
taup = sprintf("%1.2f",coeffs['taup'])
)
)
}
else if(coeffs['thetap'] < 1 && coeffs['kp'] > 1)
{
fiteq = substitute(
pangenes(g) == omegap - thetap * (g-1) + kp ~ exp(frac(-2,taup)) ~ frac(1-exp(frac(-(g-1),taup)),1-exp(frac(-1,taup))), \
list(
omegap=sprintf("%1.0f",coeffs['omegap']), \
thetap=sprintf("%1.1f",-coeffs['thetap']), \
kp = sprintf("%1.0f",coeffs['kp']), \
taup = sprintf("%1.2f",coeffs['taup'])
)
)
}
else if(coeffs['thetap'] > 1 && coeffs['kp'] < 1)
{
fiteq = substitute(
pangenes(g) == omegap + thetap * (g-1) - kp ~ exp(frac(-2,taup)) ~ frac(1-exp(frac(-(g-1),taup)),1- exp(frac(-1,taup))), \
list(
omegap=sprintf("%1.0f",coeffs['omegap']), \
thetap=sprintf("%1.1f",coeffs['thetap']), \
kp = sprintf("%1.0f",-coeffs['kp']), \
taup = sprintf("%1.2f",coeffs['taup'])
)
)
}
else
{
fiteq = substitute(
pangenes(g) == omegap - thetap * (g-1) - kp ~ exp(frac(-2,taup)) ~ frac(1-exp(frac(-(g-1),taup)),1-exp(frac(-1,taup))), \
list(
omegap=sprintf("%1.0f",coeffs['omegap']), \
thetap=sprintf("%1.1f",-coeffs['thetap']), \
kp = sprintf("%1.0f",-coeffs['kp']), \
taup = sprintf("%1.2f",coeffs['taup'])
)
)
}
writeLines("# pan fit converged", txtreport);
writeLines(sprintf("# residual standard error = %1.2f",SER), txtreport);
writeLines( paste(fiteq) , txtreport, sep=" " );
writeLines( "" , txtreport);
fittedvalues = lapply( 1:$n_of_genomes, ffit)
writeLines( "# fitted values (genomes, genes) :" , txtreport );
for(i in 1:$n_of_genomes ) {
writeLines( sprintf("%d\t%1.1f",i,fittedvalues[i]) , txtreport );
}
} else {
writeLines("# pan fit failed to converge", txtreport)
}
close(txtreport);
# actually make charts
pdf(file="$PDFfile");
plot(pan\$genomes,pan\$genes,xaxt='n',xlab='genomes (g)',ylab='pan genome size (genes)',pch=20);
xaxis_labels = 1:$n_of_genomes;
axis(side=1,at=xaxis_labels);
if(converged == TRUE)
{
curve( ffit , from=1, to=max(pan\$genomes), add=T, col="red" );
mtext(fiteq,side=3,cex=$FontScale,line=0.5);
mtext(sprintf("residual standard error = %1.2f",SER),side=4,cex=$FontScale,line=0.5)
}
dev.off()
png(file="$PNGfile");
plot(pan\$genomes,pan\$genes,xaxt='n',xlab='genomes (g)',ylab='pan genome size (genes)',pch=20); #,ylim=c(25000,35000));
axis(side=1,at=xaxis_labels);
if(converged == TRUE)
{
curve( ffit , from=1, to=max(pan\$genomes), add=T, col="red" );
mtext(fiteq,side=3,cex=$FontScale,line=0.5);
mtext(sprintf("residual standard error = %1.2f",SER),side=4,cex=$FontScale,line=0.5)
}
dev.off()
svg(file="$SVGfile");
plot(pan\$genomes,pan\$genes,xaxt='n',xlab='genomes (g)',ylab='pan genome size (genes)',pch=20); #,ylim=c(25000,35000));
axis(side=1,at=xaxis_labels);
if(converged == TRUE)
{
curve( ffit , from=1, to=max(pan\$genomes), add=T, col="red" );
mtext(fiteq,side=3,cex=$FontScale,line=0.5);
mtext(sprintf("residual standard error = %1.2f",SER),side=4,cex=$FontScale,line=0.5)
}
dev.off()
# make animation pics if required
anim_dir = "$anim_dir"
if(file.exists(anim_dir))
{
i = 0
picname = ''
# add first sampling replicate
genomes = pan\$genomes[1:$n_of_genomes]
genes = pan\$genes[1:$n_of_genomes]
for(i in 1:$n_of_genomes){
if (i < 10) { picname = paste(anim_dir,'/000',i,'plot.png',sep='')}
if (i < 100 && i >= 10) { picname = paste(anim_dir,'/00',i,'plot.png', sep='')}
if (i >= 100) { picname = paste(anim_dir,'/0', i,'plot.png', sep='')}
colors = c( rep("green",i) , rep("white",$n_of_genomes-i) )
png(picname);
plot(genomes,genes,xaxt='n',xlab='genomes (g)',ylab='pan genome size (genes)',
pch=20, col=colors, main=paste("Genomes/transcriptomes added=",i," replicates=",1));
axis(side=1,at=xaxis_labels);
dev.off()
}
# remaining replicates
for(r in 2:$n_of_replicates)
{
last = r*$n_of_genomes
genomes = pan\$genomes[1:last]
genes = pan\$genes[1:last]
i=last
colors = c( rep("black",(r-1)*$n_of_genomes) , rep("green",$n_of_genomes) )
if (i < 10) { picname = paste(anim_dir,'/000',i,'plot.png',sep='')}
if (i < 100 && i >= 10) { picname = paste(anim_dir,'/00',i,'plot.png', sep='')}
if (i >= 100) { picname = paste(anim_dir,'/0', i,'plot.png', sep='')}
png(picname);
plot(genomes,genes,xaxt='n',xlab='genomes (g)',ylab='pan genome size (genes)',
pch=20, col=colors, main=paste("Genomes/transcriptomes added=",last," replicates=",r));
axis(side=1,at=xaxis_labels);
dev.off()
}
# final plot
png(picname);
plot(genomes,genes,xaxt='n',xlab='genomes (g)',ylab='pan genome size (genes)',pch=20);
axis(side=1,at=xaxis_labels);
if(converged == TRUE)
{
curve( ffit , from=1, to=max(pan\$genomes), add=T, col="red" );
mtext(fiteq,side=3,cex=$FontScale,line=0.5);
mtext(sprintf("residual standard error = %1.2f",SER),side=4,cex=$FontScale,line=0.5)
}
dev.off()
}
q()
EOF
close RSHELL;
# print summary of animation folder
if(-s $anim_dir)
{
opendir(ANIMDIR,$anim_dir) || die "# $0 : cannot list $anim_dir\n";
my @snapshots = grep{/\.png/} readdir(ANIMDIR);
closedir(ANIMDIR);
if(@snapshots)
{
printf("\n# %d animation pics available in folder '%s'\n\n",scalar(@snapshots),$anim_dir);
}
}
# 4) clean
unlink($tmpfile);
# 5) check outcome
if(!-s $PDFfile && !-s $PNGfile)
{
die "# plot_pan_genome : ERROR, cannot plot data\n";
}
}