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plot-vcfstats
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#!/usr/bin/env perl
#
# Author: petr.danecek@sanger
#
# Dependencies:
# - matplotlib
# http://matplotlib.sourceforge.net
# - LaTex/xcolor.sty
# Download .sty.gz LaTeX class style from http://www.ukern.de/tex/xcolor.html,
# unpack and install system-wide or place elsewhere and make available by
# setting the TEXINPUTS environment variable (note the colon)
# export TEXINPUTS=some/dir:
# The list of the recognised path can be obtained from `kpsepath tex`
#
#
use strict;
use warnings;
use Carp;
use Storable qw(dclone);
my $opts = parse_params();
parse_vcfstats($opts);
merge_vcfstats($opts) if @{$$opts{vcfstats}} > 1;
if ( $$opts{make_plots} )
{
init_plots($opts);
plot_venn_bars($opts);
plot_counts_by_AF($opts);
plot_overlap_by_AF($opts);
plot_concordance_by_AF($opts);
plot_concordance_by_sample($opts);
for my $id (file_ids($opts))
{
plot_irc_by_AF($opts,$id);
plot_irc_by_rlen($opts,$id);
plot_tstv_by_AF($opts,$id);
plot_tstv_by_QUAL($opts,$id);
plot_indel_distribution($opts,$id);
plot_substitutions($opts,$id);
plot_per_sample_stats($opts,$id);
plot_DP($opts,$id);
plot_hwe($opts,$id);
}
plot($opts);
}
create_pdf($opts) unless !$$opts{make_pdf};
exit;
#--------------------------------
sub error
{
my (@msg) = @_;
if ( scalar @msg ) { confess @msg; }
die
"Usage: plot-vcfstats [OPTIONS] file.chk ...\n",
" plot-vcfstats -p outdir/ file.chk ...\n",
"Options:\n",
" -m, --merge Merge vcfstats files to STDOUT, skip plotting.\n",
" -p, --prefix <path> The output files prefix, add a slash to create new directory.\n",
" -P, --no-PDF Skip the PDF creation step.\n",
" -r, --rasterize Rasterize PDF images for fast rendering.\n",
" -s, --sample-names Use sample names for xticks rather than numeric IDs.\n",
" -t, --title <string> Identify files by these titles in plots. Can be given multiple times.\n",
" -T, --main-title <string> Main title for the PDF.\n",
" -h, -?, --help This help message.\n",
"\n";
}
sub parse_params
{
$0 =~ s{^.+/}{};
my $opts =
{
pdf_plots => 1,
use_sample_names => 0,
verbose => 1,
make_pdf => 1,
make_plots => 1,
merge => 0,
args => join(' ',$0,@ARGV),
img_width => 11/2.54,
img_height => 10/2.54,
id2col => [ 'orange', 'red', 'darkgreen' ],
tex =>
{
slide3v => { height1 => '7cm', height2 => '7cm', height3 => '4.5cm' },
slide3h => { width1 => '15cm', width2 => '10cm', width3 => '8cm' },
},
# for file version sanity check
sections =>
[
{
id=>'ID',
header=>'Definition of sets',
exp=>"# ID\t[2]id\t[3]tab-separated file names"
},
{
id=>'SN',
header=>'SN, Summary numbers',
exp=>"# SN [2]id [3]key [4]value"
},
{
id=>'TSTV',
header=>'# TSTV, transition/transversions:',
exp=>"# TSTV\t[2]id\t[3]ts\t[4]tv\t[5]ts/tv\t[6]ts (1st ALT)\t[7]tv (1st ALT)\t[8]ts/tv (1st ALT)"
},
{
id=>'SiS',
header=>'Sis, Singleton stats',
exp=>"# SiS\t[2]id\t[3]allele count\t[4]number of SNPs\t[5]number of transitions\t[6]number of transversions\t[7]number of indels\t[8]repeat-consistent\t[9]repeat-inconsistent\t[10]not applicable"
},
{
id=>'AF',
header=>'AF, Stats by non-reference allele frequency',
exp=>"# AF\t[2]id\t[3]allele frequency\t[4]number of SNPs\t[5]number of transitions\t[6]number of transversions\t[7]number of indels\t[8]repeat-consistent\t[9]repeat-inconsistent\t[10]not applicable"
},
{
id=>'IDD',
header=>'IDD, InDel distribution',
exp=>"# IDD\t[2]id\t[3]length (deletions negative)\t[4]count"
},
{
id=>'ST',
header=>'ST, Substitution types',
exp=>"# ST\t[2]id\t[3]type\t[4]count"
},
{
id=>'GCsAF',
header=>'GCsAF, Genotype concordance by non-reference allele frequency (SNPs)',
exp=>"# GCsAF\t[2]id\t[3]allele frequency\t[4]RR Hom matches\t[5]RA Het matches\t[6]AA Hom matches\t[7]RR Hom mismatches\t[8]RA Het mismatches\t[9]AA Hom mismatches\t[10]dosage r-squared\t[11]number of sites"
},
{
id=>'GCiAF',
header=>'GCiAF, Genotype concordance by non-reference allele frequency (indels)',
exp=>"# GCiAF\t[2]id\t[3]allele frequency\t[4]RR Hom matches\t[5]RA Het matches\t[6]AA Hom matches\t[7]RR Hom mismatches\t[8]RA Het mismatches\t[9]AA Hom mismatches\t[10]dosage r-squared\t[11]number of sites"
},
{
id=>'NRDs',
header=>'Non-Reference Discordance (NRD), SNPs',
exp=>"# NRDs\t[2]id\t[3]NRD\t[4]Ref/Ref discordance\t[5]Ref/Alt discordance\t[6]Alt/Alt discordance"
},
{
id=>'NRDi',
header=>'Non-Reference Discordance (NRD), indels',
exp=>"# NRDi\t[2]id\t[3]NRD\t[4]Ref/Ref discordance\t[5]Ref/Alt discordance\t[6]Alt/Alt discordance"
},
{
id=>'GCsS',
header=>'GCcS, Genotype concordance by sample (SNPs)',
exp=>"# GCsS\t[2]id\t[3]sample\t[4]non-reference discordance rate\t[5]RR Hom matches\t[6]RA Het matches\t[7]AA Hom matches\t[8]RR Hom mismatches\t[9]RA Het mismatches\t[10]AA Hom mismatches"
},
{
id=>'GCiS',
header=>'GCiS, Genotype concordance by sample (indels)',
exp=>"# GCiS\t[2]id\t[3]sample\t[4]non-reference discordance rate\t[5]RR Hom matches\t[6]RA Het matches\t[7]AA Hom matches\t[8]RR Hom mismatches\t[9]RA Het mismatches\t[10]AA Hom mismatches"
},
{
id=>'PSC',
header=>'PSC, Per-sample counts',
exp=>"# PSC\t[2]id\t[3]sample\t[4]nRefHom\t[5]nNonRefHom\t[6]nHets\t[7]nTransitions\t[8]nTransversions\t[9]nIndels\t[10]average depth\t[11]nSingletons"
},
{
id=>'DP',
header=>'DP, Depth distribution',
exp=>"# DP\t[2]id\t[3]bin\t[4]number of genotypes\t[5]fraction of genotypes (%)"
},
{
id=>'FS',
header=>'FS, Indel frameshifts',
exp=>"# FS\t[2]id\t[3]in-frame\t[4]out-frame\t[5]not applicable\t[6]out/(in+out) ratio\t[7]in-frame (1st ALT)\t[8]out-frame (1st ALT)\t[9]not applicable (1st ALT)\t[10]out/(in+out) ratio (1st ALT)"
},
{
id=>'ICS',
header=>'ICS, Indel context summary',
exp=>"# ICS\t[2]id\t[3]repeat-consistent\t[4]repeat-inconsistent\t[5]not applicable\t[6]c/(c+i) ratio"
},
{
id=>'ICL',
header=>'ICL, Indel context by length',
exp=>"# ICL\t[2]id\t[3]length of repeat element\t[4]repeat-consistent deletions)\t[5]repeat-inconsistent deletions\t[6]consistent insertions\t[7]inconsistent insertions\t[8]c/(c+i) ratio"
},
{
id=>'QUAL',
header=>'QUAL, Stats by quality',
exp=>"# QUAL\t[2]id\t[3]Quality\t[4]number of SNPs\t[5]number of transitions (1st ALT)\t[6]number of transversions (1st ALT)\t[7]number of indels"
},
{
id=>'HWE',
header=>'HWE',
exp=>"# HWE\t[2]id\t[3]1st ALT allele frequency\t[4]Number of observations\t[5]25th percentile\t[6]median\t[7]75th percentile",
},
],
};
for my $sec (@{$$opts{sections}}) { $$opts{exp}{$$sec{id}} = $$sec{exp}; $$opts{id2sec}{$$sec{id}} = $sec; }
while (defined(my $arg=shift(@ARGV)))
{
if ( $arg eq '--no-plots' ) { $$opts{make_plots}=0; next; }
if ( $arg eq '-P' || $arg eq '--no-PDF' ) { $$opts{make_pdf}=0; next; }
if ( $arg eq '-r' || $arg eq '--rasterize' ) { $$opts{rasterize}=1; $$opts{pdf_plots} = 0; next; }
if ( $arg eq '-m' || $arg eq '--merge' ) { $$opts{make_plots}=0; $$opts{make_pdf}=0; $$opts{merge}=1; next; }
if ( $arg eq '-s' || $arg eq '--sample-names' ) { $$opts{use_sample_names}=1; next; }
if ( $arg eq '-t' || $arg eq '--titles' ) { push @{$$opts{titles}},shift(@ARGV); next; }
if ( $arg eq '-T' || $arg eq '--main-title' ) { $$opts{main_title} = shift(@ARGV); next; }
if ( $arg eq '-p' || $arg eq '--prefix' ) { $$opts{prefix}=shift(@ARGV); next; }
if ( $arg eq '-?' || $arg eq '-h' || $arg eq '--help' ) { error(); }
if ( -e $arg ) { push @{$$opts{vcfstats}},$arg; next; }
error("Unknown parameter or non-existent file \"$arg\". Run -h for help.\n");
}
if ( !exists($$opts{vcfstats}) ) { error(); }
if ( !exists($$opts{prefix}) )
{
if ( !$$opts{merge} ) { error("Expected -p parameter.\n") }
$$opts{prefix} = './';
}
elsif ( $$opts{merge} ) { error("Only one of -p or -m should be given.\n"); }
if ( $$opts{merge} && @{$$opts{vcfstats}} < 2 ) { error("Nothing to merge\n") }
$$opts{dir} = $$opts{prefix};
$$opts{dir} =~ s{/[^/]+$}{/};
if ( !($$opts{dir}=~m{/$}) ) { $$opts{dir} = './'; }
if ( !($$opts{prefix}=~m{/$}) && !($$opts{prefix}=~/-$/) ) { $$opts{prefix} .= '-'; }
$$opts{lprefix} = $$opts{prefix};
$$opts{lprefix} =~ s{^.+/}{};
$$opts{logfile} = "$$opts{lprefix}plot-vcfstats.log";
if ( !-d $$opts{dir} ) { `mkdir -p $$opts{dir}`; }
`> $$opts{dir}$$opts{logfile}` unless $$opts{merge};
return $opts;
}
sub plot
{
my ($opts) = @_;
if ( !exists($$opts{plt_fh}) ) { return; }
close($$opts{plt_fh}) or error("close $$opts{plt_fh}");
my $cmd = "python $$opts{plt_file}";
print STDERR "Plotting graphs: $cmd\n" unless !$$opts{verbose};
system($cmd);
if ( $? ) { error("The command exited with non-zero status $?:\n\t$cmd\n\n"); }
}
sub parse_vcfstats
{
my ($opts) = @_;
for (my $i=0; $i<@{$$opts{vcfstats}}; $i++) { parse_vcfstats1($opts,$i); }
# Check sanity
if ( !exists($$opts{dat}{ID}{0}) )
{
error("Sanity check failed: no stats found by vcfstats??\n");
}
# Set titles
my %file2title;
my %title2file;
if ( exists($$opts{titles}) )
{
for (my $i=0; $i<@{$$opts{titles}}; $i++)
{
if ( !exists($$opts{dat}{ID}{$i}) ) { next; }
$file2title{$$opts{dat}{ID}{$i}[0][0]} = $$opts{titles}[$i];
$title2file{$$opts{titles}[$i]} = $$opts{dat}{ID}{$i}[0][0];
}
}
for my $id (file_ids($opts))
{
if ( @{$$opts{dat}{ID}{$id}[0]}>1 ) { next; } # shared stats of two files
my $file = $$opts{dat}{ID}{$id}[0][0];
if ( !exists($file2title{$file}) ) # create short title
{
my $bname = $file;
$bname =~ s{^.*/}{};
$bname =~ s{\.vcf\.gz$}{}i;
if ( length($bname) > 5 ) { $bname = substr($bname,0,5); }
my $i = 0;
my $title = $bname;
while ( exists($title2file{$title}) ) { $title = $bname.chr(66+$i); $i++; }
$file2title{$file} = $title;
$title2file{$title} = $file;
}
}
for my $id (file_ids($opts))
{
my @titles;
for my $file (@{$$opts{dat}{ID}{$id}[0]}) { push @titles, $file2title{$file} if $file2title{$file}; }
$$opts{title}{$id} = join(' + ',@titles);
}
# mapping from file names to list of IDs
for my $id (file_ids($opts))
{
my @files;
for my $file (@{$$opts{dat}{ID}{$id}[0]})
{
push @{$$opts{file2ids}{$file}}, $id;
}
}
# check sanity of the file merge: were the correct files merged?
if ( exists($$opts{coalesced_files}) && $$opts{verbose} )
{
print STDERR "The vcfstats outputs have been merged as follows:\n";
my %printed;
for my $id (keys %{$$opts{coalesced_files}})
{
for (my $i=0; $i<@{$$opts{coalesced_files}{$id}}; $i++)
{
for (my $j=0; $j<@{$$opts{coalesced_files}{$id}[$i]}; $j++)
{
if ( exists($printed{$$opts{dat}{ID}{$id}[$i][$j]}) ) { next; }
print STDERR "\t$$opts{dat}{ID}{$id}[$i][$j]\n";
for my $file (keys %{$$opts{coalesced_files}{$id}[$i][$j]})
{
my $n = $$opts{coalesced_files}{$id}[$i][$j]{$file};
print STDERR "\t\t$file", ($n>1 ? "\t..\t${n}x" : ''),"\n";
}
$printed{$$opts{dat}{ID}{$id}[$i][$j]} = 1;
}
}
}
}
}
sub add_to_values
{
my ($dst,$src,$cmp) = @_;
my $id = 0;
my $is = 0;
while ($is<@$src)
{
while ( $id<@$dst && &$cmp($$src[$is][0],$$dst[$id][0])>0 ) { $id++; }
if ( $id<@$dst && !&$cmp($$src[$is][0],$$dst[$id][0]) )
{
for (my $j=1; $j<@{$$src[$is]}; $j++) { $$dst[$id][$j] += $$src[$is][$j]; }
}
else { splice(@$dst,$id,0,$$src[$is]); }
$is++;
}
}
sub add_to_sample_values
{
my ($dst,$src) = @_;
my %id2i;
for (my $i=0; $i<@$dst; $i++)
{
$id2i{$$dst[$i][0]} = $i;
}
for (my $i=0; $i<@$src; $i++)
{
if ( !exists($id2i{$$src[$i][0]}) ) { error("Whoops, no such dst sample: $$src[$i][0]\n"); }
my $di = $id2i{$$src[$i][0]};
for (my $j=1; $j<@{$$src[$i]}; $j++)
{
$$dst[$di][$j] += $$src[$i][$j];
}
}
}
sub merge_PSC
{
my ($a,$b,$n) = @_;
for (my $i=0; $i<@$a; $i++) { $$a[$i][7] *= $n; } # average DP
add_to_sample_values($a,$b);
for (my $i=0; $i<@$a; $i++) { $$a[$i][7] /= $n+1; }
}
sub rglob
{
my ($a,$b) = @_;
if ( $a eq $b ) { return $a; }
$a =~ s/\*//;
my $la = length($a);
my $lb = length($b);
my $i = 0;
while ( $i<$la && $i<$lb && substr($a,$i,1) eq substr($b,$i,1) ) { $i++; }
$la--; $lb--;
while ( $la>$i && $lb>$i && substr($a,$la,1) eq substr($b,$lb,1) ) { $la--; $lb--; }
$la = $la==$i && $lb==$i ? 1 : $la-$i;
substr($a,$i,$la,'*');
return $a;
}
sub merge_id
{
# merge id filenames
my ($opts,$dst,$src,$id) = @_;
for (my $i=0; $i<@{$$src{$id}}; $i++)
{
for (my $j=0; $j<@{$$src{$id}[$i]}; $j++)
{
my $gname = rglob($$dst{$id}[$i][$j], $$src{$id}[$i][$j]);
$$dst{$id}[$i][$j] = $gname;
$$opts{coalesced_files}{$id}[$i][$j]{$$src{$id}[$i][$j]}++;
}
}
}
sub add_to_avg
{
my ($dst,$src,$n) = @_;
for (my $i=0; $i<@$src; $i++)
{
if ( ref($$dst[$i]) eq 'ARRAY' )
{
for (my $j=0; $j<@{$$dst[$i]}; $j++)
{
$$dst[$i][$j] = ($n*$$dst[$i][$j]+$$src[$i][$j])/($n+1);
}
}
else
{
$$dst[$i] = ($n*$$dst[$i]+$$src[$i])/($n+1);
}
}
}
sub cmp_str($$) { my ($a,$b) = @_; return $a cmp $b; }
sub cmp_num($$) { my ($a,$b) = @_; return $a <=> $b; }
sub cmp_num_op($$)
{
# numeric compare with operators
# Cases like <3, >500 make it complicated
my ($a,$b) = @_;
my $xa = '=';
my $xb = '=';
if ( $a=~/^(\D+)/ ) { $xa = $1; $a = $'; }
if ( $b=~/^(\D+)/ ) { $xb = $1; $b = $'; }
if ( $a==$b ) { return $xa cmp $xb; }
$a <=> $b;
}
sub merge_dp
{
my ($a,$b) = @_;
add_to_values($a,$b,\&cmp_num_op);
# recalculate fraction of GTs, cannot be simply summed
my $sum = 0;
for (my $i=0; $i<@$a; $i++) { $sum += $$a[$i][1]; }
for (my $i=0; $i<@$a; $i++) { $$a[$i][2] = $$a[$i][1]*100./$sum; }
}
sub merge_GCsS
{
my ($a,$b,$n) = @_;
# average the non-ref discordance rate
for (my $i=0; $i<@$a; $i++) { $$a[$i][1] *= $n; }
add_to_sample_values($a,$b);
for (my $i=0; $i<@$a; $i++) { $$a[$i][1] /= $n+1; }
}
sub merge_FS
{
my ($a,$b) = @_;
for (my $i=0; $i<@$a; $i++)
{
for (my $j=0; $j<3; $j++) { $$a[$i][$j] += $$b[$i][$j]; }
$$a[$i][3] = sprintf "%.2f", ($$a[$i][0] + $$a[$i][1]) ? $$a[$i][1]/($$a[$i][0] + $$a[$i][1]) : 0;
for (my $j=4; $j<7; $j++) { $$a[$i][$j] += $$b[$i][$j]; }
$$a[$i][7] = sprintf "%.2f", ($$a[$i][4] + $$a[$i][5]) ? $$a[$i][5]/($$a[$i][4] + $$a[$i][5]) : 0;
}
}
sub merge_ICS
{
my ($a,$b) = @_;
for (my $i=0; $i<@$a; $i++)
{
for (my $j=0; $j<3; $j++) { $$a[$i][$j] += $$b[$i][$j]; }
$$a[$i][3] = sprintf "%.4f", ($$a[$i][0] + $$a[$i][1]) ? $$a[$i][0]/($$a[$i][0] + $$a[$i][1]) : 0;
}
}
sub merge_ICL
{
my ($a,$b) = @_;
for (my $i=0; $i<@$a; $i++)
{
for (my $j=1; $j<5; $j++) { $$a[$i][$j] += $$b[$i][$j]; }
$$a[$i][5] = sprintf "%.4f", ($$a[$i][2] + $$a[$i][4]) ? ($$a[$i][1] + $$a[$i][3])/($$a[$i][1] + $$a[$i][2] + $$a[$i][3] + $$a[$i][4]) : 0;
}
}
sub merge_TSTV
{
my ($a,$b) = @_;
for (my $i=0; $i<@$a; $i++)
{
for (my $j=0; $j<2; $j++) { $$a[$i][$j] += $$b[$i][$j]; }
$$a[$i][2] = sprintf "%.2f", $$a[$i][1] ? $$a[$i][0]/$$a[$i][1] : 0;
for (my $j=3; $j<5; $j++) { $$a[$i][$j] += $$b[$i][$j]; }
$$a[$i][5] = sprintf "%.2f", $$a[$i][4] ? $$a[$i][3]/$$a[$i][4] : 0;
}
}
sub merge_GCsAF
{
my ($a,$b) = @_;
# recalculate r2
for (my $i=0; $i<@$a; $i++) { $$a[$i][7] *= $$a[$i][8]; }
for (my $i=0; $i<@$b; $i++) { $$b[$i][7] *= $$b[$i][8]; }
add_to_values($a,$b,\&cmp_num_op);
for (my $i=0; $i<@$a; $i++) { $$a[$i][7] /= $$a[$i][8]; }
}
sub parse_vcfstats1
{
my ($opts,$i) = @_;
my $file = $$opts{vcfstats}[$i];
print STDERR "Parsing vcfstats output: $file\n" unless !$$opts{verbose};
open(my $fh,'<',$file) or error("$file: $!");
my $line = <$fh>;
if ( !$line or !($line=~/^# This file was produced by \S*vcfstats/) ) { error("Sanity check failed: was this file generated by vcfstats?"); }
my %dat;
while ($line=<$fh>)
{
$line =~ s/\s*$//;
if ( $line=~/^#\s+(\S+)\t/ )
{
$$opts{def_line}{$1} = $line;
next;
}
if ( $line=~/^#/ ) { next; }
my @items = split(/\t/,$line);
if ( $items[0] eq 'SN' )
{
$dat{$items[1]}{$items[2]} = splice(@items,3);
next;
}
push @{$dat{$items[0]}{$items[1]}}, [splice(@items,2)];
}
close($fh);
for my $a (keys %dat)
{
if ( !exists($$opts{dat}{$a}) ) { $$opts{dat}{$a} = $dat{$a}; next; } # first vcfstats file
for my $b (keys %{$dat{$a}})
{
# Merging multiple vcfstats files. Honestly, this is quite hacky.
if ( !exists($$opts{dat}{$a}{$b}) ) { $$opts{dat}{$a}{$b} = $dat{$a}{$b}; next; } # copy all, first occurance
if ( $a eq 'ID' ) { merge_id($opts,$$opts{dat}{$a},$dat{$a},$b); }
elsif ( ref($dat{$a}{$b}) ne 'ARRAY' ) {$$opts{dat}{$a}{$b} += $dat{$a}{$b} unless $b eq 'number of samples:'; } # SN, Summary numbers, do not sum sample counts
elsif ( $a eq 'NRDs' ) { add_to_avg($$opts{dat}{$a}{$b},$dat{$a}{$b},$i); }
elsif ( $a eq 'NRDi' ) { add_to_avg($$opts{dat}{$a}{$b},$dat{$a}{$b},$i); }
elsif ( $a eq 'DP' ) { merge_dp($$opts{dat}{$a}{$b},$dat{$a}{$b}); }
elsif ( $a eq 'GCsS' ) { merge_GCsS($$opts{dat}{$a}{$b},$dat{$a}{$b},$i); }
elsif ( $a eq 'GCiS' ) { merge_GCsS($$opts{dat}{$a}{$b},$dat{$a}{$b},$i); }
elsif ( $a eq 'GCsAF' ) { merge_GCsAF($$opts{dat}{$a}{$b},$dat{$a}{$b},$i); }
elsif ( $a eq 'GCiAF' ) { merge_GCsAF($$opts{dat}{$a}{$b},$dat{$a}{$b},$i); }
elsif ( $a eq 'ST' ) { add_to_values($$opts{dat}{$a}{$b},$dat{$a}{$b},\&cmp_str); }
elsif ( $a eq 'PSC') { merge_PSC($$opts{dat}{$a}{$b},$dat{$a}{$b},$i); }
elsif ( $a eq 'IDD') { add_to_values($$opts{dat}{$a}{$b},$dat{$a}{$b},\&cmp_num); }
elsif ( $a eq 'FS') { merge_FS($$opts{dat}{$a}{$b},$dat{$a}{$b}); }
elsif ( $a eq 'ICS') { merge_ICS($$opts{dat}{$a}{$b},$dat{$a}{$b}); }
elsif ( $a eq 'ICL') { merge_ICL($$opts{dat}{$a}{$b},$dat{$a}{$b}); }
elsif ( $a eq 'TSTV') { merge_TSTV($$opts{dat}{$a}{$b},$dat{$a}{$b},$i); }
elsif ( $a eq 'DBG' ) { next; }
else { add_to_values($$opts{dat}{$a}{$b},$dat{$a}{$b},\&cmp_num_op); } # SiS AF IDD
}
}
}
sub file_ids
{
my ($opts) = @_;
my $id = 0;
my @out;
while ( exists($$opts{dat}{ID}) && exists($$opts{dat}{ID}{$id}) ) { push @out, $id++; }
return @out;
}
sub tprint
{
my ($fh,@txt) = @_;
for my $txt (@txt)
{
$txt =~ s/\n[ \t]+/\n/g; # eat leading tabs
while ( ($txt =~ /\n\t*\\t/) )
{
$txt =~ s/(\n\t*)\\t/$1\t/g; # replace escaped tabs (\\t) with tabs
}
print $fh $txt;
}
}
sub init_plots
{
my ($opts) = @_;
$$opts{plt_file} = "$$opts{prefix}plot.py";
my $titles = "# Title abbreviations:\n";
for my $id (file_ids($opts))
{
$titles .= "# \t $id .. $$opts{title}{$id} .. $$opts{dat}{ID}{$id}[0][0]\n";
}
$titles .= "#";
open(my $fh,'>',$$opts{plt_file}) or error("$$opts{plt_file}: $!");
tprint $fh, qq[
# This file was produced by plot-vcfstats, the command line was:
# $$opts{args}
#
# Edit as necessary and recreate the plots by running
# python $$opts{plt_file}
#
$titles
# Set to 1 to plot in PDF instead of PNG
pdf_plots = $$opts{pdf_plots}
# Set to 1 to use sample names for xticks instead of numeric sequential IDs
# and adjust margins and font properties if necessary
sample_names = $$opts{use_sample_names}
sample_margins = {'right':0.98, 'left':0.07, 'bottom':0.2}
sample_font = {'rotation':45, 'ha':'right', 'fontsize':8}
if sample_names==0: sample_margins=(); sample_font=();
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
import csv
csv.register_dialect('tab', delimiter='\\t', quoting=csv.QUOTE_NONE)
import numpy
def smooth(x,window_len=11,window='hanning'):
\\tif x.ndim != 1: raise ValueError, "smooth only accepts 1 dimension arrays."
\\tif x.size < window_len: return x
\\tif window_len<3: return x
\\tif not window in ['flat', 'hanning', 'hamming', 'bartlett', 'blackman']: raise ValueError, "Window is on of 'flat', 'hanning', 'hamming', 'bartlett', 'blackman'"
\\ts = numpy.r_[x[window_len-1:0:-1],x,x[-1:-window_len:-1]]
\\tif window == 'flat': # moving average
\\t\\tw = numpy.ones(window_len,'d')
\\telse:
\\t\\tw = eval('numpy.'+window+'(window_len)')
\\ty = numpy.convolve(w/w.sum(),s,mode='valid')
\\treturn y[(window_len/2-1):-(window_len/2)]
];
$$opts{plt_fh} = $fh;
}
sub percentile
{
my ($p,@vals) = @_;
my $N = 0;
for my $val (@vals) { $N += $val; }
my $n = $p*($N+1)/100.;
my $k = int($n);
my $d = $n-$k;
if ( $k<=0 ) { return 0; }
if ( $k>=$N ) { return scalar @vals-1; }
my $cnt;
for (my $i=0; $i<@vals; $i++)
{
$cnt += $vals[$i];
if ( $cnt>=$k ) { return $i; }
}
error("FIXME: this should not happen [percentile]\n");
}
sub get_values
{
my ($opts,$id,$key,$i,$j) = @_;
if ( !exists($$opts{dat}{$key}) ) { return (); }
if ( !exists($$opts{dat}{$key}{$id}) ) { return (); }
my $fields_ok = 1;
if ( !exists($$opts{exp}{$key}) ) { error("todo: sanity check for $key\n"); }
if ( exists($$opts{def_line}{$key}) && $$opts{def_line}{$key} ne $$opts{exp}{$key} && !$$opts{def_line_warned}{$key} )
{
warn("Warning: Possible version mismatch, the definition line differs\n\texpected: $$opts{exp}{$key}\n\tfound: $$opts{def_line}{$key}\n");
$$opts{def_line_warned}{$key} = 1;
}
if ( defined $i )
{
if ( defined $j ) { return $$opts{dat}{$key}{$id}[$i][$j]; }
return (@{$$opts{dat}{$key}{$id}[$i]});
}
return (@{$$opts{dat}{$key}{$id}});
}
sub get_value
{
my ($opts,$id,$key) = @_;
if ( !exists($$opts{dat}{$id}) ) { return undef; }
if ( !exists($$opts{dat}{$id}{$key}) ) { return undef}
return $$opts{dat}{$id}{$key};
}
sub plot_venn_bars
{
my ($opts) = @_;
my @ids = file_ids($opts);
if ( @ids != 3 ) { return; }
my (@snps,@indels,@tstv,@snp_titles,@indel_titles);
for my $id (0..2)
{
push @snps, get_value($opts,$id,'number of SNPs:');
push @indels, get_value($opts,$id,'number of indels:');
push @tstv, sprintf("%.2f",get_values($opts,$id,'TSTV',0,5));
push @snp_titles, "$$opts{title}{$id}\\nts/tv $tstv[$id]\\n" .bignum($snps[$id]);
my @fs = get_values($opts,$id,'FS');
my $fs = @fs ? "frm $fs[0][3]\\n" : '';
push @indel_titles, "$$opts{title}{$id}\\n$fs" .bignum($indels[$id]);
}
my $fh = $$opts{plt_fh};
tprint $fh, qq[
fig = plt.figure(figsize=($$opts{img_width},$$opts{img_height}))
ax1 = fig.add_subplot(111)
ax1.bar([1,2,3],[$snps[0],$snps[2],$snps[1]],align='center',color='$$opts{id2col}[0]',width=0.3)
ax1.ticklabel_format(style='sci', scilimits=(0,0), axis='y')
ax1.set_xlim(0.5,3.5)
plt.xticks([1,2,3],('$snp_titles[0]','$snp_titles[2]','$snp_titles[1]'))
plt.title('Number of SNPs')
plt.subplots_adjust(right=0.95,bottom=0.15)
plt.savefig('$$opts{prefix}venn_bars.snps.png')
if pdf_plots: plt.savefig('$$opts{prefix}venn_bars.snps.pdf')
plt.close()
fig = plt.figure(figsize=($$opts{img_width},$$opts{img_height}))
ax1 = fig.add_subplot(111)
ax1.bar([1,2,3],[$indels[0],$indels[2],$indels[1]],align='center',color='$$opts{id2col}[1]',width=0.3)
ax1.ticklabel_format(style='sci', scilimits=(0,0), axis='y')
ax1.set_xlim(0.5,3.5)
plt.xticks([1,2,3],('$indel_titles[0]','$indel_titles[2]','$indel_titles[1]'))
plt.title('Number of indels')
plt.subplots_adjust(right=0.95,bottom=0.15)
plt.savefig('$$opts{prefix}venn_bars.indels.png')
if pdf_plots: plt.savefig('$$opts{prefix}venn_bars.indels.pdf')
plt.close()
];
}
sub plot_per_sample_stats
{
my ($opts,$id) = @_;
my @vals = get_values($opts,$id,'PSC');
if ( !@vals ) { return; }
my $fh = $$opts{plt_fh};
my $img = "$$opts{prefix}tstv_by_sample.$id";
my $img2 = "$$opts{prefix}hets_by_sample.$id";
my $img3 = "$$opts{prefix}snps_by_sample.$id";
my $img4 = "$$opts{prefix}indels_by_sample.$id";
my $img5 = "$$opts{prefix}singletons_by_sample.$id";
my $img6 = "$$opts{prefix}dp_by_sample.$id";
tprint $fh, "
dat = [
";
for (my $i=0; $i<@vals; $i++)
{
my $tstv = $vals[$i][5] ? $vals[$i][4]/$vals[$i][5] : 0;
my $hethom = $vals[$i][2] ? $vals[$i][3]/$vals[$i][2] : 0;
tprint $fh, sprintf("\t[ %d, %f, %f, %d, %d, %f, %d, r'%s' ],\n", $i, $tstv, $hethom, $vals[$i][4]+$vals[$i][5], $vals[$i][6], $vals[$i][7], $vals[$i][8], $vals[$i][0]);
}
tprint $fh, "]
fig = plt.figure(figsize=(2*$$opts{img_width},$$opts{img_height}*0.7))
ax1 = fig.add_subplot(111)
ax1.plot([row[0] for row in dat], [row[1] for row in dat], 'o', color='$$opts{id2col}[$id]',mec='$$opts{id2col}[$id]')
ax1.set_ylabel('Ts/Tv')
ax1.set_ylim(min(row[1] for row in dat)-0.1,max(row[1] for row in dat)+0.1)
if sample_names:
\\t plt.xticks([row[0] for row in dat],[row[7] for row in dat],**sample_font)
\\t plt.subplots_adjust(**sample_margins)
else:
\\t plt.subplots_adjust(right=0.98,left=0.07,bottom=0.17)
\\t ax1.set_xlabel('Sample ID')
plt.title('$$opts{title}{$id}')
plt.savefig('$img.png')
if pdf_plots: plt.savefig('$img.pdf')
plt.close()
fig = plt.figure(figsize=(2*$$opts{img_width},$$opts{img_height}*0.7))
ax1 = fig.add_subplot(111)
ax1.plot([row[0] for row in dat], [row[2] for row in dat], 'o', color='$$opts{id2col}[$id]',mec='$$opts{id2col}[$id]')
ax1.set_ylabel('nHet(RA) / nHom(AA)')
ax1.ticklabel_format(style='sci', scilimits=(0,0), axis='y')
if sample_names:
\\t plt.xticks([row[0] for row in dat],[row[7] for row in dat],**sample_font)
\\t plt.subplots_adjust(**sample_margins)
else:
\\t plt.subplots_adjust(right=0.98,left=0.07,bottom=0.17)
\\t ax1.set_xlabel('Sample ID')
plt.title('$$opts{title}{$id}')
plt.savefig('$img2.png')
if pdf_plots: plt.savefig('$img2.pdf')
plt.close()
fig = plt.figure(figsize=(2*$$opts{img_width},$$opts{img_height}*0.7))
ax1 = fig.add_subplot(111)
ax1.plot([row[0] for row in dat], [row[3] for row in dat], 'o', color='$$opts{id2col}[$id]',mec='$$opts{id2col}[$id]')
ax1.set_ylabel('Number of SNPs')
ax1.ticklabel_format(style='sci', scilimits=(0,0), axis='y')
if sample_names:
\\t plt.xticks([row[0] for row in dat],[row[7] for row in dat],**sample_font)
\\t plt.subplots_adjust(**sample_margins)
else:
\\t plt.subplots_adjust(right=0.98,left=0.07,bottom=0.17)
\\t ax1.set_xlabel('Sample ID')
plt.title('$$opts{title}{$id}')
plt.savefig('$img3.png')
if pdf_plots: plt.savefig('$img3.pdf')
plt.close()
fig = plt.figure(figsize=(2*$$opts{img_width},$$opts{img_height}*0.7))
ax1 = fig.add_subplot(111)
ax1.plot([row[0] for row in dat], [row[4] for row in dat], 'o', color='$$opts{id2col}[$id]',mec='$$opts{id2col}[$id]')
ax1.set_ylabel('Number of indels')
ax1.ticklabel_format(style='sci', scilimits=(0,0), axis='y')
if sample_names:
\\t plt.xticks([row[0] for row in dat],[row[7] for row in dat],**sample_font)
\\t plt.subplots_adjust(**sample_margins)
else:
\\t plt.subplots_adjust(right=0.98,left=0.07,bottom=0.17)
\\t ax1.set_xlabel('Sample ID')
plt.title('$$opts{title}{$id}')
plt.savefig('$img4.png')
if pdf_plots: plt.savefig('$img4.pdf')
plt.close()
fig = plt.figure(figsize=(2*$$opts{img_width},$$opts{img_height}*0.7))
ax1 = fig.add_subplot(111)
ax1.plot([row[0] for row in dat], [row[6] for row in dat], 'o', color='$$opts{id2col}[$id]',mec='$$opts{id2col}[$id]')
ax1.set_ylabel('Number of singletons')
ax1.ticklabel_format(style='sci', scilimits=(0,0), axis='y')
if sample_names:
\\t plt.xticks([row[0] for row in dat],[row[7] for row in dat],**sample_font)
\\t plt.subplots_adjust(**sample_margins)
else:
\\t plt.subplots_adjust(right=0.98,left=0.07,bottom=0.17)
\\t ax1.set_xlabel('Sample ID')
plt.title('$$opts{title}{$id}')
plt.savefig('$img5.png')
if pdf_plots: plt.savefig('$img5.pdf')
plt.close()
fig = plt.figure(figsize=(2*$$opts{img_width},$$opts{img_height}*0.7))
ax1 = fig.add_subplot(111)
ax1.plot([row[0] for row in dat], [row[5] for row in dat], 'o', color='$$opts{id2col}[$id]',mec='$$opts{id2col}[$id]')
ax1.set_ylabel('Average depth')
ax1.ticklabel_format(style='sci', scilimits=(0,0), axis='y')
if sample_names:
\\t plt.xticks([row[0] for row in dat],[row[7] for row in dat],**sample_font)
\\t plt.subplots_adjust(**sample_margins)
else:
\\t plt.subplots_adjust(right=0.98,left=0.07,bottom=0.17)
\\t ax1.set_xlabel('Sample ID')
plt.title('$$opts{title}{$id}')
plt.savefig('$img6.png')
if pdf_plots: plt.savefig('$img6.pdf')
plt.close()
";
}
sub plot_DP
{
my ($opts,$id) = @_;
my @vals = get_values($opts,$id,'DP');
if ( !@vals ) { return; }
my $fh = $$opts{plt_fh};
my $img = "$$opts{prefix}depth.$id";
tprint $fh, "
dat = [
";
my $sum = 0;
for (my $i=0; $i<@vals; $i++)
{
if ( $sum>99. ) { last; }
if ( !($vals[$i][0]=~/^\d+$/) ) { next; } # DP ">500" case
$sum += $vals[$i][2];
tprint $fh, sprintf("\t[ %d, %f, %f ],\n", $vals[$i][0], $sum, $vals[$i][2]);
}
tprint $fh, "]
fig = plt.figure(figsize=($$opts{img_width},$$opts{img_height}))
ax1 = fig.add_subplot(111)
ax1.plot([row[0] for row in dat], [row[2] for row in dat], '-^', color='k')
ax1.set_ylabel('Number of genotypes [%]',color='k')
ax1.set_xlabel('Depth')
ax2 = ax1.twinx()
ax2.plot([row[0] for row in dat], [row[1] for row in dat], '-o', color='$$opts{id2col}[$id]')
ax2.set_ylabel('Cumulative number of genotypes [%]',color='$$opts{id2col}[$id]')
for tl in ax2.get_yticklabels(): tl.set_color('$$opts{id2col}[$id]')
plt.subplots_adjust(left=0.15,bottom=0.15,right=0.87)
plt.title('$$opts{title}{$id}')
plt.savefig('$img.png')
if pdf_plots: plt.savefig('$img.pdf')
plt.close()
";
}
sub plot_hwe
{
my ($opts,$id) = @_;
my @vals = get_values($opts,$id,'HWE');
if ( !@vals ) { return; }
my $fh = $$opts{plt_fh};
my $img = "$$opts{prefix}hwe.$id";
tprint $fh, "
dat = [
";
my $sum = 0;
for (my $i=0; $i<@vals; $i++)
{
if ( !$vals[$i][1] ) { next; }
tprint $fh, "\t[", join(',', @{$vals[$i]}), "],\n";
}
tprint $fh, "]
x = [row[0] for row in dat]
y1 = smooth(numpy.array([row[2] for row in dat]),40,'hanning')
y2 = smooth(numpy.array([row[3] for row in dat]),40,'hanning')
y3 = smooth(numpy.array([row[4] for row in dat]),40,'hanning')
dp = smooth(numpy.array([row[1] for row in dat]),40,'hanning')
hwe = []
for af in x: hwe.append(2*af/100.*(1-af/100.))
fig = plt.figure(figsize=($$opts{img_width},$$opts{img_height}))
ax1 = fig.add_subplot(111)
plots = ax1.plot(x,hwe,'--',color='#ff9900',label='HWE')
plots += ax1.plot(x,y2,color='#ff9900',label='Median')
plots += ax1.plot(x,y3,color='#ffe0b2',label='25-75th percentile')
ax1.fill_between(x,y1,y3, facecolor='#ffeacc',edgecolor='#ffe0b2')
ax1.set_ylabel('Fraction of hets',color='#ff9900')
ax1.set_xlabel('Allele frequency [%]')
for tl in ax1.get_yticklabels(): tl.set_color('#ff9900')
ax2 = ax1.twinx()
plots += ax2.plot(x,dp, 'k', label='Number of sites')
ax2.set_ylabel('Number of sites')
ax2.set_yscale('log')
labels = [l.get_label() for l in plots]
plt.legend(plots,labels,numpoints=1,markerscale=2,loc='center',prop={'size':9},frameon=False)
plt.subplots_adjust(left=0.15,bottom=0.15,right=0.86)
plt.title('$$opts{title}{$id}')
plt.savefig('$img.png')
if pdf_plots: plt.savefig('$img.pdf')
plt.close()
";
}
sub plot_irc_by_rlen
{
my ($opts,$id) = @_;
my @vals = get_values($opts,$id,'ICL');
if ( !@vals ) { return; }
my $fh = $$opts{plt_fh};
my $img = "$$opts{prefix}irc_by_rlen.$id";
my $has_vals = 0;
tprint $fh, "
dat = [
";
for (my $i=0; $i<@vals; $i++)
{
tprint $fh, sprintf("\t[ %d, %d, %f, %f ],\n",
$vals[$i][0], # repeat type
$vals[$i][1]+$vals[$i][2]+$vals[$i][3]+$vals[$i][4], # total count
$vals[$i][2] ? $vals[$i][1]/($vals[$i][1]+$vals[$i][2]) : 0, # IRC of deletions
$vals[$i][4] ? $vals[$i][3]/($vals[$i][3]+$vals[$i][4]) : 0 # IRC of insertions
);
}
tprint $fh, "]
fig = plt.figure(figsize=($$opts{img_width},$$opts{img_height}))
ax1 = fig.add_subplot(111)
ax2 = ax1.twinx()
plots = ax1.plot([row[0] for row in dat], [row[2] for row in dat], 'o-', ms=3, color='r', mec='r', label='Deletions');
plots += ax1.plot([row[0] for row in dat], [row[3] for row in dat], 'o-', ms=3, color='g', mec='g', label='Insertions');
plots += ax2.plot([row[0] for row in dat], [row[1] for row in dat], '^--', ms=3, color='k', mec='k', label='Number of sites');
ax2.ticklabel_format(style='sci',scilimits=(-3,4))
ax1.set_xlabel('Repeat type');
ax1.set_ylabel('Repeat Consistency');
ax2.set_ylabel('Number of sites');
labels = [l.get_label() for l in plots]
ax1.legend(plots,labels,numpoints=1,markerscale=1,loc='best',prop={'size':9},frameon=False)
plt.subplots_adjust(right=0.88,left=0.15,bottom=0.11)
plt.title('$$opts{title}{$id}')
plt.savefig('$img.png')