Genome...athScan(3pm)
🌸 Genome...athScan(3pm) 🌸
okay so bestie 💖 welcome to the Genome...athScan(3pm) page — User Contributed Perl Documentation, and it is long, so it's rolling out in parts. This is part 1, and we are not skimming, we are reading every single line like the main characters we are. 👑
✨ OPTIONS ✨
--pathway-file— this is a tab-delimited file you put together from a pathway database (KEGG, iykyk). The columns go:[path_id, path_name, class, gene_line, diseases, drugs, description]. The last three columns are optional (but they're literally sitting there available on KEGG if you want them ✨). Thegene_linecontains the"entrez_id:gene_name"of all the genes involved in this pathway, each one separated by a"|"symbol.
For example, a line in the pathway-file would look like:
hsa00061 Fatty acid biosynthesis Lipid Metabolism 31:ACACA|32:ACACB|27349:MCAT|2194:FASN|54995:OXSM|55301:OLAHOkay so real talk 🫶 — make sure the gene names and entrez IDs you're using match the ones used in the MAF file. Entrez IDs are not mandatory (just drop a 0 if the Entrez ID is unknown). But here's the tea: if a gene name in the MAF does not match any gene name in this file, the entrez IDs get used to find a match (unless it's a 0, obviously).
--gene-covg-dir— this is usually thegene_covgssubdirectory that appears when you runmusic bmr calc-covg. It should contain files for each sample that report per-gene covered base counts. 🧬--bam-list— hand over a file with the sample names and the normal/tumor BAM locations for each one. Use the tab-delimited format[sample_name normal_bam tumor_bam]per line. This tool literally only needssample_name, so all the other columns can be skipped, no problem. Thesample_namemust be the same as the tumor sample names used in the MAF file (16th column, with the headerTumor_Sample_Barcode). 👀--bmr— the overall background mutation rate. You can calculate it withmusic bmr calc-bmr. 💅--genes-to-ignore— a comma-delimited list of genes to ignore from the MAF file. Super useful when there are recurrently mutated genes likeTP53that might mask the significance of other genes. not TP53 catching strays 😭
🎀 THE SOURCE 🎀
...the tail end of that options doc string 💅
EOS
); }_doc_authors
sub _doc_authors {
return <<EOS
Michael Wendl, Ph.D. EOS }_doc_credits
sub _doc_credits {
return <<EOS This module uses reformatted copies of data from the
Kyoto Encyclopedia of Genes and Genomes (KEGG) database:
* KEGG - http://www.genome.jp/kegg/
EOS
}execute
and now the big one, bestie — the whole execute method, served up verbatim, no cap. 🫶
sub execute {
my $self = shift;
my $covg_dir = $self->gene_covg_dir;
my $bam_list = $self->bam_list;
my $pathway_file = $self->pathway_file;
my $maf_file = $self->maf_file;
my $output_file = $self->output_file;
my $bgd_mut_rate = $self->bmr;
my $genes_to_ignore = $self->genes_to_ignore;
my $min_mut_genes_per_path = $self->min_mut_genes_per_path;
my $skip_non_coding = $self->skip_non_coding;
my $skip_silent = $self->skip_silent;
# Check on all the input data before starting work
print STDERR "MAF file not found or is empty: $maf_file\n" unless( -s $maf_file );
print STDERR "Directory with gene coverages not found: $covg_dir\n" unless( -e $covg_dir );
print STDERR "List of samples not found or is empty: $bam_list\n" unless( -s $bam_list );
print STDERR "Pathway info file not found or is empty: $pathway_file\n" unless( -s $pathway_file );
return undef unless( -s $maf_file && -e $covg_dir && -s $bam_list && -s $pathway_file );
# Build a hash to quickly lookup the genes whose mutations should be ignored
my %ignored_genes = ();
if( defined $genes_to_ignore )
{
%ignored_genes = map { $_ => 1 } split( /,/, $genes_to_ignore );
}
# PathScan uses a helluva lot of hashes - all your RAM are belong to it
my %sample_gene_hash; # sample => array of genes (based on maf)
my %gene_path_hash; # gene => array of pathways (based on path_file)
my %path_hash; # pathway => all the information about the pathways in the database
my %sample_path_hash; # sample => pathways (based on %sample_gene_hash and %gene_path_hash)
my %path_sample_hits_hash; # path => sample => hits,mutated_genes
my %gene_sample_cov_hash; # gene => sample => coverage
my @all_sample_names; # names of all the samples, no matter if it's mutated or not
my %id_gene_hash; # entrez id => gene (based on first two columns in MAF)
# Parse out the names of the samples which should match the names in the MAF file
my $sampleFh = IO::File->new( $bam_list ) or die "Couldn't open $bam_list. $!\n";
while( my $line = $sampleFh->getline )
{
next if ( $line =~ m/^#/ );
chomp( $line );
my ( $sample ) = split( /\t/, $line );
push( @all_sample_names, $sample );
}
$sampleFh->close;
# Read coverage data calculated by the Music::Bmr::CalcCovg
$covg_dir =~ s/(\/)+$//; # Remove trailing forward slashes if any
read_CoverageFiles( $covg_dir, \@all_sample_names, \%gene_sample_cov_hash );
#build gene => average_coverage hash for population test
my %gene_cov_hash;
foreach my $gene ( keys %gene_sample_cov_hash )
{
my $total_cov = 0;
my $sample_num = scalar( @all_sample_names );
$total_cov += $gene_sample_cov_hash{$gene}{$_} foreach( @all_sample_names );
$gene_cov_hash{$gene} = int( $total_cov / $sample_num );
}
#build %sample_gene_hash based on maf
my $maf_fh = IO::File->new( $maf_file );
while( my $line = $maf_fh->getline )
{
next if( $line =~ m/^(#|Hugo_Symbol)/ );
chomp( $line );
my @cols = split( /\t/, $line );
my ( $gene, $entrez_id, $mutation_class, $tumor_sample ) = ( $cols[0], $cols[1], $cols[8], $cols[15] );
# If the mutation classification is odd, quit with error
if( $mutation_class !~ m/^(Missense_Mutation|Nonsense_Mutation|Nonstop_Mutation|Splice_Site|Translation_Start_Site|Frame_Shift_Del|Frame_Shift_Ins|In_Frame_Del|Silent|In_Frame_Ins|Intron|RNA|3'Flank|3'UTR|5'Flank|5'UTR|IGR|Targeted_Region|De_novo_Start_InFrame|De_novo_Start_OutOfFrame)$/ )
{
print STDERR "Unrecognized Variant_Classification $mutation_class in MAF file.\n";
print STDERR "Please use TCGA MAF Specification v2.3.\n";
return undef;
}
# If user wants, skip Silent mutations, or those in Introns, RNA, UTRs, Flanks, IGRs, or the ubiquitous Targeted_Region
if(( $skip_non_coding && $mutation_class =~ m/^(Intron|RNA|3'Flank|3'UTR|5'Flank|5'UTR|IGR|Targeted_Region)$/ ) ||
( $skip_silent && $mutation_class =~ m/^Silent$/ ))
{
print STDERR "Skipping $mutation_class mutation in gene $gene.\n";
next;
}
# Check that the user followed instructions and named each sample correctly
unless( grep( /^$tumor_sample$/, @all_sample_names ))
{
print STDERR "Sample $tumor_sample in MAF file does not match any in $bam_list\n";
return undef;
}
next if( defined $ignored_genes{$gene} ); # Ignore variants in genes that user wants ignored
$id_gene_hash{$entrez_id} = $gene unless( $entrez_id eq '' or $entrez_id == 0 or $entrez_id !~ m/^\d+$/ );
push( @{$sample_gene_hash{$tumor_sample}}, $gene ) unless( grep /^$gene$/, @{$sample_gene_hash{$tumor_sample}} );
}
$maf_fh->close;
my $path_fh = IO::File->new( $pathway_file );
while( my $line = $path_fh->getline )
{
chomp( $line );
next if( $line =~ /^(#|ID)/ ); #Skip headers
my ( $path_id, $name, $class, $gene_line, $diseases, $drugs, $description ) = split( /\t/, $line );
my @genes = split( /\|/, $gene_line ); #Each gene is in the format "EntrezID:GeneSymbol"
$diseases =~ s/\|/, /g; #Change the separators to commas
$drugs =~ s/\|/, /g; #Change the separators to commas
$path_hash{$path_id}{name} = $name unless( $name eq '' );
$path_hash{$path_id}{class} = $class unless( $class eq '' );
$path_hash{$path_id}{diseases} = $diseases unless( $diseases eq '' );
$path_hash{$path_id}{drugs} = $drugs unless( $drugs eq '' );
$path_hash{$path_id}{description} = $description unless( $description eq '' );
@{$path_hash{$path_id}{gene}} = ();
foreach my $gene ( @genes )
{
my ( $entrez_id, $gene_symbol ) = split( /:/, $gene );
unless( $entrez_id eq '' or $entrez_id == 0 or $entrez_id !~ m/^\d+$/ )
{
# Use the gene name from the MAF file if the entrez ID matches
$gene_symbol = $id_gene_hash{$entrez_id} if( defined $id_gene_hash{$entrez_id} );
}
push( @{$gene_path_hash{$gene_symbol}}, $path_id ) unless( grep /^$path_id$/, @{$gene_path_hash{$gene_symbol}} );
unless( grep /^$gene_symbol$/, @{$path_hash{$path_id}{gene}} )
{
push( @{$path_hash{$path_id}{gene}}, $gene_symbol );
}
}
}
$path_fh->close;
#build a sample => pathway hash
foreach my $sample ( keys %sample_gene_hash )
{
foreach my $gene ( @{$sample_gene_hash{$sample}} )
{
if( defined $gene_path_hash{$gene} )
{
foreach my $pathway ( @{$gene_path_hash{$gene}} )
{
push( @{$sample_path_hash{$sample}}, $pathway ) unless( grep /^$pathway$/, @{$sample_path_hash{$sample}} );
}
}
}
}
#build path_sample_hits_hash, for population test
foreach my $sample ( keys %sample_path_hash )
{
foreach my $path ( @{$sample_path_hash{$sample}} )
{
my $hits = 0;
my @mutated_genes = (); #Mutated genes in this sample belonging to this pathway
my @mutated_genes_in_sample = @{$sample_gene_hash{$sample}};
foreach my $gene ( @{$path_hash{$path}{gene}} )
{
if( grep /^$gene$/, @mutated_genes_in_sample ) #if this gene is mutated in this sample (in maf)
{
$hits++;
push( @mutated_genes, $gene );
}
}
if( $hits > 0 )
{
$path_sample_hits_hash{$path}{$sample}{hits} = $hits;
$path_sample_hits_hash{$path}{$sample}{mutated_genes} = \@mutated_genes;
}
}
}and that's literally just where part 1 stops — there is so much more coming in part 2, don't go anywhere 🌈
okay bestie we're SO back and we're deep in the lab now 🧪✨ this is where the actual number crunching happens — p-values, FDRs, and two whole output files. strap in 💅
First up: the p-value calc. Watch her build @gene_sizes per pathway, but ONLY for genes that actually have coverage defined AND an average coverage greater than 3. No coverage? Pathway gets skipped, bye 🙈 No mutated genes in any sample? Also skipped, periodt.
#Calculation of p value
my %data; #For printing
my @pvals;
foreach my $path ( sort keys %path_hash )
{
my @pathway_genes = @{$path_hash{$path}{gene}};
my @gene_sizes = ();
foreach my $gene ( @pathway_genes )
{
if( defined $gene_cov_hash{$gene} )
{
my $avg_cov = int( $gene_cov_hash{$gene} );
push( @gene_sizes, $avg_cov ) if( $avg_cov > 3 );
}
}
#If this pathway doesn't have any gene coverage, skip it
next unless( scalar( @gene_sizes ) > 0 );
my @num_hits_per_sample; #store hits info for each patient
my @mutated_samples = sort keys %{$path_sample_hits_hash{$path}};
foreach my $sample ( @all_sample_names )
{
my $hits = 0;
#if this sample has mutation
if( grep /^$sample$/, @mutated_samples )
{
$hits = $path_sample_hits_hash{$path}{$sample}{hits};
}
push( @num_hits_per_sample, $hits );
}
#If this pathway doesn't have any mutated genes in any samples, skip it
next unless( scalar( @num_hits_per_sample ) > 0 );
my $hits_ref = \@num_hits_per_sample;
########### MCW ADDED
# FIND MAX NUMBER OF HITS IN A SAMPLE
my $max_hits = 0;
foreach my $hits_in_sample ( @num_hits_per_sample )
{
$max_hits = $hits_in_sample if( $hits_in_sample > $max_hits );
}
########### MCW ADDEDokay so notice the ########### MCW ADDED markers?? those are iconic little archaeological layers of the codebase, bestie, we do not touch them 🫶
Now the main character move: she builds a PopulationPathScan object, and how many "assign" slots she gives it depends on how many gene sizes she's working with — >= 3 goes down one branch, == 2 gets 2, everything else gets 1. And inside that first branch there's an if( $max_hits > 15 ) that bumps the assign all the way to 5, otherwise 3. Note the old line is still sitting there commented out: #$pop_obj->assign(3); — a fossil, a mood, a vibe 💀
Then preprocess (with the #mwendl's new fix comment, respect 🫡), then population_pval_approx gives us the p-value, and everything gets stashed into %data and pushed onto @pvals.
my $pop_obj = Genome::Model::Tools::Music::PathScan::PopulationPathScan->new( \@gene_sizes );
if( scalar( @gene_sizes ) >= 3 )
{
########### MCW ADDED
if( $max_hits > 15 )
{
$pop_obj->assign( 5 );
}
else
{
$pop_obj->assign( 3 );
}
########### MCW ADDED
#$pop_obj->assign(3);
}
elsif( @gene_sizes == 2 )
{
$pop_obj->assign( 2 );
}
else
{
$pop_obj->assign( 1 );
}
$pop_obj->preprocess( $bgd_mut_rate, $hits_ref ); #mwendl's new fix
my $pval = $pop_obj->population_pval_approx($hits_ref);
$data{$pval}{$path}{samples} = \@mutated_samples;
$data{$pval}{$path}{hits} = $hits_ref;
push( @pvals, $pval ); # For calculation of FDR
}
# Calculate False Discovery Rates (Benjamini-Hochberg FDR) for the p-values
my $pval_cnt = scalar( @pvals );
my %fdr_hash;
for( my $i = 0; $i < $pval_cnt; $i++ )
{
my $fdr = $pvals[$i] * $pval_cnt / ( $pval_cnt - $i );
$fdr = 1 if $fdr > 1;
$fdr_hash{$pvals[$i]} = $fdr;
}and YES she does the Benjamini-Hochberg FDR herself, no cap. $fdr = $pvals[$i] * $pval_cnt / ( $pval_cnt - $i ); and then $fdr = 1 if $fdr > 1; because we are NOT letting an FDR go above 1, that would be giving unhinged 🌸
the output era 💖
two files. one main, one _detailed. the main one gets a header row with tabs, and the detailed one gets the whole diary entry. also she skips any pathway whose mutated gene count is less than $min_mut_genes_per_path — user's choice, user's rules, slay 👑
# Print two output files, one more detailed than the other
my $out_fh = IO::File->new( $output_file, ">" );
my $out_detailed_fh = IO::File->new( "$output_file\_detailed", ">" );
$out_fh->print( "Pathway\tName\tClass\tSamples_Affected\tTotal_Variations\tp-value\tFDR\n" );
foreach my $pval ( sort { $a <=> $b } keys %data )
{
foreach my $path ( sort keys %{$data{$pval}} )
{
# Skip this pathway if it has fewer affected genes than the user wants
my %mutated_gene_hash;
my @samples = @{$data{$pval}{$path}{samples}};
foreach my $sample ( @samples )
{
foreach my $gene ( @{$path_sample_hits_hash{$path}{$sample}{mutated_genes}} )
{
$mutated_gene_hash{$gene}++;
}
}
next unless ( scalar( keys %mutated_gene_hash ) >= $min_mut_genes_per_path );the detailed file prints Pathway:, and then Name:, Class:, Diseases:, Drugs: — each one guarded with if( defined ... ) because we do NOT print undef in this house 🚫 — then P-value:, FDR:, and Description:.
then for each sample: $sample: followed by the mutated genes joined with ",". then the ✨iconic✨ Samples with mutations (#hits): line, which walks @all_sample_names and prints $all_sample_names[$i]($hits[$i]) for every hit over 0, counting up $mutSampleCnt and $totalMutGenes as she goes. ends with a double newline because spacing is self-care 🎀
# Print detailed output to a separate output file
$out_detailed_fh->print( "Pathway: $path\n" );
$out_detailed_fh->print( "Name: ", $path_hash{$path}{name}, "\n" ) if( defined $path_hash{$path}{name} );
$out_detailed_fh->print( "Class: ", $path_hash{$path}{class}, "\n" ) if( defined $path_hash{$path}{class} );
$out_detailed_fh->print( "Diseases: ", $path_hash{$path}{diseases}, "\n" ) if( defined $path_hash{$path}{diseases} );
$out_detailed_fh->print( "Drugs: ", $path_hash{$path}{drugs}, "\n" ) if( defined $path_hash{$path}{drugs} );
$out_detailed_fh->print( "P-value: $pval\n", "FDR: ", $fdr_hash{$pval}, "\n" );
$out_detailed_fh->print( "Description: ", $path_hash{$path}{description}, "\n" );
my @hits = @{$data{$pval}{$path}{hits}};
foreach my $sample ( @samples )
{
my @mutated_genes = @{$path_sample_hits_hash{$path}{$sample}{mutated_genes}};
$out_detailed_fh->print( "$sample:" );
$out_detailed_fh->print( join ",", @mutated_genes );
$out_detailed_fh->print( "\n" );
}
my ( $mutSampleCnt, $totalMutGenes ) = ( 0, 0 );
$out_detailed_fh->print( "Samples with mutations (#hits): " );
for( my $i = 0; $i < scalar( @all_sample_names ); ++$i )
{
if( $hits[$i] > 0 )
{
$out_detailed_fh->print( "$all_sample_names[$i]($hits[$i]) " );
$mutSampleCnt++;
$totalMutGenes += $hits[$i];
}
}
$out_detailed_fh->print( "\n\n" );and for the main file: $path_name and $path_class default to "-" and only get overwritten if they're actually defined. then one tab-separated line of $path, $path_name, $path_class, $mutSampleCnt, $totalMutGenes, $pval, and the FDR. both filehandles closed, return 1;, done. she ATE 💅✨
# Print tabulated output to the main output file
my ( $path_name, $path_class ) = ( "-", "-" );
$path_name = $path_hash{$path}{name} if( defined $path_hash{$path}{name} );
$path_class = $path_hash{$path}{class} if( defined $path_hash{$path}{class} );
$out_fh->print( "$path\t$path_name\t$path_class\t$mutSampleCnt\t$totalMutGenes\t",
"$pval\t", $fdr_hash{$pval}, "\n" );
}
}
$out_detailed_fh->close;
$out_fh->close;
return 1;
}read_CoverageFiles 🦋
this little subroutine takes three things: $covg_dir, $all_samples_ref, and $gene_sample_cov_hash_ref. for every sample she looks for $covg_dir/$sample.covg.
and if that file is missing or empty?? -s says nope, and she prints to STDERR:
Couldn't find $sample.covg in $covg_dir. (music bmr calc-covg possibly incomplete)
then exit 1; — no file, no party, go run your Music::Bmr::CalcCovg step, bestie 😭
otherwise she opens it, skips any line starting with #, splits on tabs into $gene, undef, $covd_bases, and stashes $covd_bases into $gene_sample_cov_hash_ref->{$gene}{$sample}. closes up, moves on. neat. tidy. iconic. 🌸
# Reads files for each sample which are formatted as tab-separated lines
each showing the number of # bases with sufficient coverage in a gene.
sub read_CoverageFiles {
my ( $covg_dir, $all_samples_ref, $gene_sample_cov_hash_ref ) = (
$_[0], $_[1], $_[2] );
# Read per-gene covered base counts for each sample
foreach my $sample ( @{$all_samples_ref} )
{
# If the file doesn't exist, quit with error. The Music::Bmr::CalcCovg step is incomplete
unless( -s "$covg_dir/$sample.covg" )
{
print STDERR "Couldn't find $sample.covg in $covg_dir. (music bmr calc-covg possibly incomplete)\n";
exit 1;
}
my $covgFh = IO::File->new( "$covg_dir/$sample.covg" );
while( my $line = $covgFh->getline )
{
next if( $line =~ m/^#/ );
my ( $gene, undef, $covd_bases ) = split( /\t/, $line );
$gene_sample_cov_hash_ref->{$gene}{$sample} = $covd_bases;
}
$covgFh->close;
}
}
1;and that's a wrap on the module, bestie 🫶 the classic 1; at the end because a Perl module that returns truth is a Perl module that returns vibes 💜
this page came out ofperl v5.30.3, dated2020-11-06, and it's part of the User Contributed Perl Documentation. shoutout to whoever wrote it, shoutout to whoever maintained it, shoutout to YOU for reading the whole thing. mwah 😘✨
📦 where this page comes from
- debian bookworm: libgenome-model-tools-music-perl 0.04-5 · LGPL-3.0-only
- debian trixie: libgenome-model-tools-music-perl 0.04-5 · LGPL-3.0-only
- ubuntu jammy: libgenome-model-tools-music-perl 0.04-5 · LGPL-3.0-only
- ubuntu noble: libgenome-model-tools-music-perl 0.04-5 · LGPL-3.0-only
- ubuntu resolute: libgenome-model-tools-music-perl 0.04-5 · LGPL-3.0-only
- ubuntu stonking: libgenome-model-tools-music-perl 0.04-5 · LGPL-3.0-only
- 💖 girlified by deepseek-ai/DeepSeek-V4.1-Flash on : a language model's rewrite of the original, under its terms