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ADEPT.pl
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#!/usr/bin/perl
###### Required ########################################################
# 1. Parallel::ForkManager module from CPAN #
# 2. String::Approx module from CPAN #
# 3. R for ploting #
###########################################################################
###### Inputs #########################################################
# 1. Fastq files either paired-end or unpaired reads or both #
# Can input multiple library fastq files but only output #
# concatenate trimmed fastq files #
# 2. Output directory #
# 3. Other options #
###########################################################################
###### Output #########################################################
# 1. Two Paired-ends files if input paired-end reads #
# 2. One unpaired reads file #
# 3. statistical text file #
# 4. quality report pdf file #
###########################################################################
use strict;
use File::Basename;
use Getopt::Long;
use Parallel::ForkManager;
use String::Approx;
my $version=1.1;
my $debug=0;
sub Usage {
print <<"END";
Usage: perl $0 [options] [-u unpaired.fastq] -p 'reads1.fastq reads2.fastq' -d out_directory
Version $version
Input File: (can use more than once)
-u Unpaired reads
-p Paired reads in two files and separate by space in quote
Trim:
-qE 5" and 3" ends triming # as quality level (default 5) for trimming
-qC threhold to call a base to be correct (default = 0.25, higher quality
than 25% the nucleotides at that position within the sampled run )
-qW threhold to identifying a nucleotide as an error if it falls below a defined
percentage of the quality scores for that position (default = 0)
-qMN ratio of the of the base quality to the qualities of upstream and downstream positions
By default, all qMN ratios must be at least 0.4 to be considered as a potential erroneous base
(i.e. all adjacent qualities must be at least 2.5 times higher than the quality of the position being investigated).
-qNS threhold to identify a nucleotide as an potential error if its neighbors' quality falls below a defined
percentage of the quality scores for that neighbors' position within the sampled run (default = 0.3)
-trimcenter whether performing center trimming by spliting the reads at center erroneous bases (yes or no, default is no)
Filters:
-min_L Trimmed sequence length will have at least minimum length (default:50)
Q_Format:
-ascii Encoding type: 33 or 64 or autoCheck (default)
Type of ASCII encoding: 33 (standard) or 64 (illumina 1.3+)
-out_ascii Output encoding. (default: 33)
Output:
-prefix Output file prefix. (default: QC)
-stats Statistical numbers output file (default: prefix.stats.txt)
-d Output directory.
Options:
-t # of CPUs to run the script (default:2 )
-split_size Split the input file into several sub files by sequence number (default: 1000000)
-out_non_trim_reads <bool> Output not trimmed reads to prefix.discard.fastq (default: 0, not output)
-debug keep intermediate files
END
exit;
}
# magic number of quality score
my $highest_illumina_score=41;
my $lowest_illumina_score=0;
# Options Variable initialization
my $thread=2;
my $opt_q=5;
my $opt_min_L=50;
my $minilength=$opt_min_L;
my $opt_avg_cutoff=0;
my $ascii;
my $out_offset=33;
my $subfile_size=1000000;
my $kmer=31;
my $prefix="QC";
my $plots_file;
my $stats_output;
my $trimmed_reads1_fastq_file;
my $trimmed_reads2_fastq_file;
my $trimmed_unpaired_fastq_file;
my $notrimmed_reads1_fastq_file;
my $notrimmed_reads2_fastq_file;
my @paired_files;
my @unpaired_files;
my $outDir;
my $output_discard;
my $qc_only;
my $nontrimed_output;
#ADEPT OPTIOPN
my $cutlimit=0.3;
my $lowperc=0;
my $upperc=0.25;
my $discperc=0.4;
my $cutlimit1= $cutlimit;
my $cutlimit2= $cutlimit;
my $trimcenter='no';
# Options
GetOptions("qE=i" => \$opt_q,
"qC=i" => \$upperc,
"qW=i" => \$lowperc,
"qMN=i" => \$discperc,
"qNS=i" => \$cutlimit,
"min_L=i" => \$opt_min_L,
"avg_q=f" => \$opt_avg_cutoff,
"p=s" => \@paired_files,
"u=s" => \@unpaired_files,
"ascii=i" => \$ascii,
"out_ascii=i" => \$out_offset,
"t|threads=i" => \$thread,
'split_size=i' => \$subfile_size,
'prefix=s' => \$prefix,
'd=s' => \$outDir,
'stats=s' => \$stats_output,
'trimcenter=s' => \$trimcenter,
'out_non_trim_reads' => \$nontrimed_output,
'debug' => \$debug,
"help|?" => sub{Usage()} );
die "Missing input files.\n", &Usage() unless @unpaired_files or @paired_files;
die "Missing output directory.\n",&Usage() unless $outDir;
###### Output file initialization #####
# temp files for plotting
my $quality_matrix="$outDir/$prefix.quality.matrix";
my $avg_quality_histogram="$outDir/$prefix.for_qual_histogram.txt";
my $base_matrix="$outDir/$prefix.base.matrix";
my $nuc_composition_file="$outDir/$prefix.base_content.txt";
my $length_histogram="$outDir/$prefix.length_count.txt";
# output files
$plots_file="$outDir/${prefix}_qc_report.pdf" if (!$plots_file);
$trimmed_unpaired_fastq_file="$outDir/$prefix.unpaired.trimmed.fastq" if (!$trimmed_unpaired_fastq_file);
$trimmed_reads1_fastq_file="$outDir/$prefix.1.trimmed.fastq" if (!$trimmed_reads1_fastq_file);
$trimmed_reads2_fastq_file="$outDir/$prefix.2.trimmed.fastq" if (!$trimmed_reads2_fastq_file);
$notrimmed_reads1_fastq_file="$outDir/$prefix.1.qc.fastq" if (!$trimmed_reads1_fastq_file);
$notrimmed_reads2_fastq_file="$outDir/$prefix.2.qc.fastq" if (!$trimmed_reads2_fastq_file);
$stats_output="$outDir/$prefix.stats.txt" if (!$stats_output);
#######################################
###### Output check ################
if (! -e $outDir)
{
mkdir $outDir;
}
if (-e $trimmed_reads1_fastq_file)
{
print "The output $trimmed_reads1_fastq_file file exists and will be overwritten.\n";
system ("rm $trimmed_reads1_fastq_file");
}
if (-e $trimmed_reads2_fastq_file)
{
print "The output $trimmed_reads2_fastq_file file exists and will be overwritten.\n";
system ("rm $trimmed_reads2_fastq_file");
}
if ($notrimmed_reads1_fastq_file)
{
if (-e $notrimmed_reads1_fastq_file)
{
print "The output $notrimmed_reads1_fastq_file file exists and will be overwritten.\n";
system ("rm $notrimmed_reads1_fastq_file");
}
}
if ( $notrimmed_reads2_fastq_file)
{
if (-e $notrimmed_reads2_fastq_file)
{
print "The output $notrimmed_reads2_fastq_file file exists and will be overwritten.\n";
system ("rm $notrimmed_reads2_fastq_file");
}
}
if (-e $trimmed_unpaired_fastq_file)
{
print "The output $trimmed_unpaired_fastq_file file exists and will be overwritten.\n";
system ("rm $trimmed_unpaired_fastq_file");
}
if (-e $plots_file)
{
print "The output $plots_file file exists and will be overwritten.\n";
system ("rm $plots_file");
}
#######################################
my ( $total_count,$total_count_1, $total_count_2, $total_num, $trimmed_num,$total_raw_seq_len, $total_trimmed_seq_len);
my ( $trim_seq_len_std, $trim_seq_len_avg, $max, $min, $median, $numOfReadsWithAdapter);
my ( $paired_seq_num, $total_paired_bases );
my ( @split_files, @split_files_2);
my (%error);
my %position;
my %AverageQ;
my %base_position;
my %base_content;
my %len_hash;
my ( $i_file_name, $i_path, $i_suffix );
foreach my $input (@unpaired_files,@paired_files){
print "Processing $input file\n";
my ($reads1_file,$reads2_file) = split /\s+/,$input;
# check file
if(&file_check($reads1_file)<0) { die "The file $reads1_file doesn't exist or empty.\n";}
if(&file_check($reads2_file)<0 and $reads2_file) { die "The file $reads2_file doesn't exist or empty.\n";}
# check quality offset
if (! $ascii){$ascii = &checkQualityFormat($reads1_file)}
#baseline quality
my $basequality=&build_initial_quality_matrix($reads1_file);
#split
($total_count_1,@split_files) = &split_fastq($reads1_file,$outDir,$subfile_size);
($total_count_2,@split_files_2) = &split_fastq($reads2_file,$outDir,$subfile_size) if ($reads2_file);
$total_count += $total_count_1 + $total_count_2;
my $pm = new Parallel::ForkManager($thread);
$pm -> run_on_finish ( # called BEFORE the first call to start()
sub {
my ($pid, $exit_code, $ident, $exit_signal, $core_dump, $nums_ref) = @_;
# retrieve data structure from child
if (defined($nums_ref)) { # children are not forced to send anything
my ($total_score, $avg_score);
$total_num += $nums_ref->{raw_seq_num};
$trimmed_num += $nums_ref->{trim_seq_num};
$total_raw_seq_len += $nums_ref->{total_raw_seq_len};
$total_trimmed_seq_len += $nums_ref->{total_trim_seq_len};
my $processed_num= $nums_ref->{raw_seq_num};
$trim_seq_len_std = $nums_ref->{trim_seq_len_std};
$trim_seq_len_avg = $nums_ref->{trim_seq_len_avg};
$max = $nums_ref->{max};
$min = $nums_ref->{min};
$median = $nums_ref->{median};
$paired_seq_num += $nums_ref->{paired_seq_num};
$total_paired_bases += $nums_ref->{total_paired_bases};
$numOfReadsWithAdapter += $nums_ref->{numOfReadsWithAdapter};
my %temp_avgQ = %{$nums_ref->{ReadAvgQ}};
map {$AverageQ{$_}->{bases} += $temp_avgQ{$_}->{basesNum};
$AverageQ{$_}->{reads} += $temp_avgQ{$_}->{readsNum};
} keys %temp_avgQ;
my %temp_position= %{$nums_ref->{qual}};
my %temp_base_position= %{$nums_ref->{base}};
foreach my $pos (1..($total_raw_seq_len/$total_num))
{
for my $score ($lowest_illumina_score..$highest_illumina_score)
{
$position{$pos}->{$score} += $temp_position{$pos}->{$score};
$total_score += $score * $temp_position{$pos}->{$score};
}
for my $nuc ("A","T","C","G","N")
{
$base_position{$pos}->{$nuc} += $temp_base_position{$pos}->{$nuc};
}
}
my %tmp_base_content = %{$nums_ref->{Base_content}};
for my $nuc ("A","T","C","G","N","GC")
{
while (my ($key, $value)= each %{$tmp_base_content{$nuc}})
{
$base_content{$nuc}->{$key} += $value;
}
}
while (my ($key, $value)= each %{$nums_ref->{ReadLen}} )
{
$len_hash{$key} += $value;
}
print "Processed $total_num/$total_count\n";
printf (" Post Trimming Length(Mean, Std, Median, Max, Min) of %d reads with Overall quality %.2f\n",$processed_num, $total_score/$nums_ref->{total_trim_seq_len});
printf (" (%.2f, %.2f, %.1f, %d, %d)\n",$trim_seq_len_avg,$trim_seq_len_std,$median,$max,$min);
} else { # problems occuring during storage or retrieval will throw a warning
print qq|No message received from child process $pid! on $ident\n|;
}
}
);
foreach my $i(0..$#split_files)
{
$pm->start($i) and next;
my $hash_ref = &qc_process($split_files[$i],$split_files_2[$i],$basequality);
$pm->finish(0, $hash_ref);
}
$pm->wait_all_children;
# clean up
foreach my $i(0..$#split_files)
{
unlink $split_files[$i];
unlink $split_files_2[$i] if ($split_files_2[$i]);
}
} #end foreach $input
# concatenate each thread's trimmed reads and files clean up.
if (! $qc_only)
{
if (@unpaired_files)
{
foreach my $input (@unpaired_files){
( $i_file_name, $i_path, $i_suffix ) = fileparse( "$input", qr/\.[^.]*/ );
( $i_file_name, $i_path, $i_suffix ) = fileparse( "$i_file_name", qr/\.[^.]*/ ) if ($i_suffix =~ /gz$/);
if (system("cat $outDir/${i_file_name}_?????_trim.fastq >> $trimmed_unpaired_fastq_file")) { die "cat failed: $!" }
`rm $outDir/${i_file_name}_?????_trim.fastq`;
}
}
if (@paired_files)
{
foreach my $input (@paired_files){
my ($reads1_file,$reads2_file) = split /\s+/,$input;
( $i_file_name, $i_path, $i_suffix ) = fileparse( "$reads1_file", qr/\.[^.]*/ );
( $i_file_name, $i_path, $i_suffix ) = fileparse( "$i_file_name", qr/\.[^.]*/ ) if ($i_suffix =~ /gz$/);
if (system("cat $outDir/${i_file_name}_?????_trim.fastq >> $trimmed_reads1_fastq_file")) { die "cat failed: $!" }
`rm $outDir/${i_file_name}_?????_trim.fastq`;
( $i_file_name, $i_path, $i_suffix ) = fileparse( "$reads2_file", qr/\.[^.]*/ );
( $i_file_name, $i_path, $i_suffix ) = fileparse( "$i_file_name", qr/\.[^.]*/ ) if ($i_suffix =~ /gz$/);
if (system("cat $outDir/${i_file_name}_?????_trim.fastq >> $trimmed_reads2_fastq_file")) { die "cat failed: $!" }
`rm $outDir/${i_file_name}_?????_trim.fastq`;
if (system("cat $outDir/${i_file_name}_?????_trim_unpaired.fastq >> $trimmed_unpaired_fastq_file")) { die "cat failed: $!" }
`rm $outDir/${i_file_name}_?????_trim_unpaired.fastq`;
}
}
if ($nontrimed_output)
{
if (@paired_files)
{
foreach my $input (@paired_files){
my ($reads1_file,$reads2_file) = split /\s+/,$input;
( $i_file_name, $i_path, $i_suffix ) = fileparse( "$reads1_file", qr/\.[^.]*/ );
( $i_file_name, $i_path, $i_suffix ) = fileparse( "$i_file_name", qr/\.[^.]*/ ) if ($i_suffix =~ /gz$/);
if (system("cat $outDir/${i_file_name}_?????_qc.fastq >> $notrimmed_reads1_fastq_file")) { die "cat failed: $!" }
`rm $outDir/${i_file_name}_?????_qc.fastq`;
( $i_file_name, $i_path, $i_suffix ) = fileparse( "$reads2_file", qr/\.[^.]*/ );
( $i_file_name, $i_path, $i_suffix ) = fileparse( "$i_file_name", qr/\.[^.]*/ ) if ($i_suffix =~ /gz$/);
if (system("cat $outDir/${i_file_name}_?????_qc.fastq >> $trimmed_reads2_fastq_file")) { die "cat failed: $!" }
`rm $outDir/${i_file_name}_?????_qc.fastq`;
}
}
}
}
&print_quality_report_files();
&print_final_stats();
&plot_by_R();
unless ($debug){
unlink $nuc_composition_file;
unlink $quality_matrix;
unlink $base_matrix;
unlink $avg_quality_histogram;
unlink $length_histogram;
}
exit(0);
sub build_initial_quality_matrix
{
print "start build_initial_quality_matrix\n";
my $fastqFile=shift;
open (my $fh, "$fastqFile") or die "$fastqFile $!";
my %basequal;
my $total_reads=0;
while(<$fh>)
{
last if ($total_reads>1000000);
my $name=$_;
my $seq=<$fh>;
$seq =~ s/\n//g;
while ($seq !~ /\+/)
{
$seq .= <$fh>;
$seq =~ s/\n//g;
}
my $q_id_pos=index($seq,"+");
$seq = substr($seq, 0, $q_id_pos);
my $seq_len = length $seq;
my $qual_seq=<$fh>;
$qual_seq =~ s/\n//g;
my $qual_seq_len = length $qual_seq;
while ( $qual_seq_len < $seq_len )
{
last if ( $qual_seq_len == $seq_len);
$qual_seq .= <$fh>;
$qual_seq =~ s/\n//g;
$qual_seq_len = length $qual_seq;
}
my @qual_seq=split //, $qual_seq;
if (rand() <=0.2) {
$total_reads++;
for my $pos(0..$#qual_seq)
{
push @{$basequal{$pos}}, ord($qual_seq[$pos])-$ascii;
}
}
}
close $fh;
@{$basequal{$_}}= sort {$a <=> $b} @{$basequal{$_}} foreach (keys %basequal);
print "done build_initial_quality_matrix\n";
return \%basequal;
}
sub print_final_stats{
open (my $fh, ">$stats_output") or die "$!\t$stats_output\n";
# stats output
print $fh "\nBefore Trimming\n";
print $fh "Reads #:\t$total_num\n";
print $fh "Total bases:\t$total_raw_seq_len\n";
printf $fh ("Reads Length:\t%.2f\n",$total_raw_seq_len/$total_num);
print $fh "\nAfter Trimming\n";
printf $fh ("Reads #:\t\%d (%.2f %%)\n",$trimmed_num, $trimmed_num/$total_num*100);
printf $fh ("Total bases:\t\%d (%.2f %%)\n",$total_trimmed_seq_len,$total_trimmed_seq_len/$total_raw_seq_len*100);
if ($trimmed_num)
{
printf $fh ("Mean Reads Length:\t%.2f\n",$total_trimmed_seq_len/$trimmed_num);
}
else
{
printf $fh "Mean Reads Length:\t0\n";
}
if (@paired_files){
printf $fh (" Paired Reads #:\t\%d (%.2f %%)\n",$paired_seq_num, $paired_seq_num/$trimmed_num*100);
printf $fh (" Paired total bases:\t\%d (%.2f %%)\n",$total_paired_bases,$total_paired_bases/$total_trimmed_seq_len*100);
printf $fh (" Unpaired Reads #:\t\%d (%.2f %%)\n", $trimmed_num - $paired_seq_num, ($trimmed_num - $paired_seq_num)/$trimmed_num*100);
printf $fh (" Unpaired total bases:\t\%d (%.2f %%)\n", $total_trimmed_seq_len - $total_paired_bases , ($total_trimmed_seq_len - $total_paired_bases)/$total_trimmed_seq_len*100);
}
printf $fh ("\nDiscarded reads #:\t\%d (%.2f %%)\n", $total_num - $trimmed_num , ($total_num - $trimmed_num)/$total_num*100);
printf $fh ("Trimmed bases:\t\%d (%.2f %%)\n", $total_raw_seq_len - $total_trimmed_seq_len, ($total_raw_seq_len - $total_trimmed_seq_len)/$total_raw_seq_len*100);
return (0);
}
sub plot_by_R
{
open (R,">$outDir/tmp$$.R");
print R <<RSCRIPT;
def.par <- par(no.readonly = TRUE) # get default parameters
pdf(file = \"$plots_file\",width = 10, height = 8)
#trimmed summary
txt<-c(
"Before Trimming",
paste("Reads #:", prettyNum(\"$total_num\",big.mark=",")),
paste("Total bases:", prettyNum(\"$total_raw_seq_len\",big.mark=",")),
paste("Reads Length:",sprintf("%.2f",$total_raw_seq_len/$total_num)),
" ",
"After Trimming",
paste("Reads #:", prettyNum(\"$trimmed_num\",big.mark=","),sprintf("(%.2f %%)", $trimmed_num/$total_num*100)),
paste("Total bases:",prettyNum(\"$total_trimmed_seq_len\",big.mark=","),sprintf("(%.2f %%)",$total_trimmed_seq_len/$total_raw_seq_len*100))
)
if($trimmed_num>0)
{
txt<-c(txt,
paste("Mean Reads Length:", sprintf("%.2f",$total_trimmed_seq_len/$trimmed_num))
)
}
if($paired_seq_num >0){
txt <- c(txt,
paste(" Paired Reads #: ", prettyNum(\"$paired_seq_num\",big.mark=","), sprintf("(%.2f %%)", $paired_seq_num/$trimmed_num*100)),
paste(" Paired total bases: ", prettyNum(\"$total_paired_bases\",big.mark=","),sprintf("(%.2f %%)",$total_paired_bases/$total_trimmed_seq_len*100)),
paste(" Unpaired Reads: ", prettyNum($trimmed_num - $paired_seq_num,big.mark=","),sprintf("(%.2f %%)", ($trimmed_num - $paired_seq_num)/$trimmed_num*100)),
paste(" Unpaired total bases: ",prettyNum($total_trimmed_seq_len - $total_paired_bases,big.mark=","),sprintf("(%.2f %%)" , ($total_trimmed_seq_len - $total_paired_bases)/$total_trimmed_seq_len*100))
)
}
txt<- c( txt, " ")
txt<- c( txt,
paste("Discarded reads #: ", prettyNum($total_num - $trimmed_num,big.mark=","), sprintf("(%.2f %%)", ($total_num - $trimmed_num)/$total_num*100)),
paste("Discarded bases: ",prettyNum($total_raw_seq_len - $total_trimmed_seq_len,big.mark=","),sprintf("(%.2f %%)", ($total_raw_seq_len - $total_trimmed_seq_len)/$total_raw_seq_len*100))
)
plot(1:80,xaxt=\'n\',yaxt=\'n\',type=\'n\',ylab=\'\',xlab=\'\')
#title(paste(\"$prefix\",\"QC report\"),sub = 'DOE Joint Genome Institute/Los Alamos National Laboratory', adj = 0.5, col.sub='darkblue',font.sub=2,cex.sub=0.8)
title("QC stats")
for (i in seq(along=txt))
{
text(1,(85-i*5),txt[i],adj=0,font=2)
}
#lenght histogram
lengthfile<-read.table(file=\"$length_histogram\")
lengthList<-as.numeric(lengthfile\$V1)
lengthCount<-as.numeric(lengthfile\$V2)
lenAvg<-sum(lengthList * lengthCount)/sum(lengthCount)
lenStd<-sqrt(sum(((lengthList - lenAvg)**2)*lengthCount)/sum(lengthCount))
lenMax<-max(lengthList[lengthCount>0])
lenMin<-min(lengthList[lengthCount>0])
barplot(lengthCount/1000000,names.arg=lengthList,xlab=\"Length\",ylab=\"Count (millions)\",main=\"Reads Length Histogram\",cex.names=0.8)
legend.txt<-c(paste(\"Mean\",sprintf (\"%.2f\",lenAvg),\"±\",sprintf (\"%.2f\",lenStd)),paste(\"Max\",lenMax),paste(\"Min\",lenMin))
legend('topleft',legend.txt,bty='n')
#readGC plot
baseP<-read.table(file=\"$nuc_composition_file\")
Apercent<-baseP\$V2[which(baseP\$V1==\"A\")]
ApercentCount<-baseP\$V3[which(baseP\$V1==\"A\")]
Tpercent<-baseP\$V2[which(baseP\$V1==\"T\")]
TpercentCount<-baseP\$V3[which(baseP\$V1==\"T\")]
Cpercent<-baseP\$V2[which(baseP\$V1==\"C\")]
CpercentCount<-baseP\$V3[which(baseP\$V1==\"C\")]
Gpercent<-baseP\$V2[which(baseP\$V1==\"G\")]
GpercentCount<-baseP\$V3[which(baseP\$V1==\"G\")]
#Npercent<-baseP\$V2[which(baseP\$V1==\"N\")]
#NpercentCount<-baseP\$V3[which(baseP\$V1==\"N\")]
GCpercent<-baseP\$V2[which(baseP\$V1==\"GC\")]
GCpercentCount<-baseP\$V3[which(baseP\$V1==\"GC\")]
aAvg<-sum(Apercent * ApercentCount)/sum(ApercentCount)
aStd<-sqrt(sum(((Apercent - aAvg)**2)*ApercentCount)/sum(ApercentCount))
tAvg<-sum(Tpercent * TpercentCount)/sum(TpercentCount)
tStd<-sqrt(sum(((Tpercent - tAvg)**2)*TpercentCount)/sum(TpercentCount))
cAvg<-sum(Cpercent * CpercentCount)/sum(CpercentCount)
cStd<-sqrt(sum(((Cpercent - cAvg)**2)*CpercentCount)/sum(CpercentCount))
gAvg<-sum(Gpercent * GpercentCount)/sum(GpercentCount)
gStd<-sqrt(sum(((Gpercent - gAvg)**2)*GpercentCount)/sum(GpercentCount))
#nAvg<-sum(Npercent * NpercentCount)/sum(NpercentCount)
#nStd<-sqrt(sum(((Npercent - nAvg)**2)*NpercentCount)/sum(NpercentCount))
gcAvg<-sum(GCpercent * GCpercentCount)/sum(GCpercentCount)
gcStd<-sqrt(sum(((GCpercent - gcAvg)**2)*GCpercentCount)/sum(GCpercentCount))
GCaggregate<-tapply(GCpercentCount,list(cut(GCpercent,breaks=c(seq(0,100,1)))),FUN=sum)
Aaggregate<-tapply(ApercentCount,list(cut(Apercent,breaks=c(seq(0,100,1)))),FUN=sum)
Taggregate<-tapply(TpercentCount,list(cut(Tpercent,breaks=c(seq(0,100,1)))),FUN=sum)
Caggregate<-tapply(CpercentCount,list(cut(Cpercent,breaks=c(seq(0,100,1)))),FUN=sum)
Gaggregate<-tapply(GpercentCount,list(cut(Gpercent,breaks=c(seq(0,100,1)))),FUN=sum)
par(fig=c(0,0.75,0,1),mar=c(5,4,4,2),xpd=FALSE,cex.main=1.2)
plot(GCaggregate/1000000,xlim=c(0,100),type=\"h\",lwd=4, main=\"Reads GC content\",xlab=\"GC (%)\",ylab=\"Number of reads (millions)\",lend=2)
legend.txt<-c(paste(\"GC\",sprintf (\"%.2f%%\",gcAvg),\"±\",sprintf (\"%.2f\",gcStd)))
legend('topright',legend.txt,bty='n')
par(fig=c(0.75,1,0.75,1), mar=c(3, 2, 2, 2),new=TRUE,cex.main=1)
legend.txt<-c(paste(\"A\",sprintf (\"%.2f%%\",aAvg),\"±\",sprintf (\"%.2f\",aStd)))
plot(Aaggregate/1000000,xlim=c(0,50),type=\"h\",lwd=2,main=legend.txt,xlab="",ylab="",)
par(fig=c(0.75,1,0.5,0.75),mar=c(3, 2, 2, 2),new=TRUE)
legend.txt<-c(paste(\"T\",sprintf (\"%.2f%%\",tAvg),\"±\",sprintf (\"%.2f\",tStd)))
plot(Taggregate/1000000,xlim=c(0,50),type=\"h\",lwd=2,main=legend.txt,xlab="",ylab="")
par(fig=c(0.75,1,0.25,0.5),mar=c(3, 2, 2, 2),new=TRUE)
legend.txt<-c(paste(\"C\",sprintf (\"%.2f%%\",cAvg),\"±\",sprintf (\"%.2f\",cStd)))
plot(Caggregate/1000000,xlim=c(0,50),type=\"h\",lwd=2,main=legend.txt,xlab="",ylab="")
par(fig=c(0.75,1,0,0.25),mar=c(3, 2, 2, 2),new=TRUE)
legend.txt<-c(paste(\"G\",sprintf (\"%.2f%%\",gAvg),\"±\",sprintf (\"%.2f\",gStd)))
plot(Gaggregate/1000000,xlim=c(0,50),type=\"h\",lwd=2,main=legend.txt,xlab="",ylab="")
par(def.par)#- reset to default
#ATCG composition per base ATCG plot
baseM<-read.table(file=\"$base_matrix\")
aBase<-baseM\$V1
tBase<-baseM\$V2
cBase<-baseM\$V3
gBase<-baseM\$V4
nBase<-baseM\$V5
aPer<-(aBase/rowSums(baseM))*100
tPer<-(tBase/rowSums(baseM))*100
cPer<-(cBase/rowSums(baseM))*100
gPer<-(gBase/rowSums(baseM))*100
xpos<-seq(1,length(aBase),1)
plot(xpos,aPer,col=\'green3\',type=\'l\',xaxt=\'n\',xlab=\'Base\',ylab=\'Base content (%)\',ylim=c(1,100))
lines(xpos,tPer,col=\'red\')
lines(xpos,cPer,col=\'blue\')
lines(xpos,gPer,col=\'black\')
axis(1,at=xpos,labels=xpos)
legend(\'topright\',c(\'A\',\'T\',\'C\',\'G\'),col=c(\'green3\',\'red\',\'blue\',\'black\'),box.col=0,lwd=1)
title(\"Nucleotide Content Per Cycle\")
# read avg quality count barplot
Qhist_file<-read.table(file=\"$avg_quality_histogram\",header=TRUE)
par(mar=c(5,4,4,4))
cumulate<-cumsum(Qhist_file\$readsNum)
plot(Qhist_file\$Score,Qhist_file\$readsNum/1000000,type=\'h\',xlim=c(max(Qhist_file\$Score),min(Qhist_file\$Score)),xlab=\"Avg Score\", ylab=\"Reads Number (millions)\",lwd=12,lend=2)
title('Reads Average Quality Histogram')
par(new=TRUE)
plot(Qhist_file\$Score,cumulate/sum(Qhist_file\$readsNum)*100,type='l',xlim=c(max(Qhist_file\$Score),min(Qhist_file\$Score)),yaxt='n',xaxt='n',ylab="",xlab="",col='blue',lwd=3)
axis(4,col='blue',col.ticks='blue',col.axis='blue')
mtext(side=4,'Cumulative Percentage',line=2,col='blue')
Qover20Reads<-sum(as.numeric(Qhist_file\$readsNum[Qhist_file\$Score>=20]))
Qover20ReadsPer<-sprintf(\"%.2f%%\",Qover20Reads/sum(Qhist_file\$readsNum)*100)
Qover20Bases<-sum(as.numeric(Qhist_file\$readsBases[Qhist_file\$Score>=20]))
Qover20AvgLen<-sprintf(\"%.2f\",Qover20Bases/Qover20Reads)
mtext(side=3,paste(\"Number of Q>=20 reads:\",prettyNum(Qover20Reads,big.mark=\",\"),\"(\",Qover20ReadsPer,\")\",\", mean Length:\",Qover20AvgLen),adj=0,cex=0.8,line=0.5)
par(def.par)#- reset to default
# read in matrix file for the following three plots
z<-as.matrix(read.table(file=\"$quality_matrix\"));
x<-1:nrow(z)
y<-1:ncol(z)
y<-y-1
#quality boxplot per base
is.wholenumber <- function(x, tol = .Machine\$double.eps^0.5) abs(x - round(x)) < tol
plot(1:length(x),x,type=\'n\',xlab=\"Position\",ylab=\"Quality score\", ylim=c(0,max(y)+1),xaxt=\'n\')
axis(1,at=x,labels=TRUE)
title(\"Quality Boxplot Per Cycle\")
for (i in 1:length(x)) {
total<-sum(z[i,])
qAvg<-sum(y*z[i,])/total
if (is.wholenumber(total/2))
{
med<-( min(y[cumsum((z[i,]))>=total/2]) + min(y[cumsum((z[i,]))>=total/2+1]) )/2
}
else
{
med<-min(y[cumsum((z[i,]))>=ceiling(total/2)])
}
if (is.wholenumber(total/4))
{
Q1<-( min(y[cumsum((z[i,]))>=total/4]) + min(y[cumsum((z[i,]))>=total/4+1]) )/2
}
else
{
Q1<-min(y[cumsum((z[i,]))>=round(total/4)])
}
if (is.wholenumber(total/4*3))
{
Q3<-( min(y[cumsum((z[i,]))>=total/4*3]) + min(y[cumsum((z[i,]))>=total/4*3+1]) )/2
}
else
{
Q3<-min(y[cumsum((z[i,]))>=round(total/4*3)])
}
maxi<-max(y[z[i,]>0])
mini<-min(y[z[i,]>0])
#if (Q1 == 'Inf') {Q1 = maxi}
if (Q3 == \'Inf\') {Q3 = maxi}
IntQ<-Q3-Q1
mini<-max(mini,Q1-1.5*IntQ)
maxi<-min(maxi,Q3+1.5*IntQ)
rect(i-0.4,Q1,i+0.4,Q3,col=\'bisque\')
lines(c(i,i),c(Q3,maxi),lty=2)
lines(c(i,i),c(mini,Q1),lty=2)
lines(c(i-0.4,i+0.4),c(mini,mini))
lines(c(i-0.4,i+0.4),c(maxi,maxi))
lines(c(i-0.4,i+0.4),c(med,med))
#points(i,qAvg,col=\'red\')
reads_num<-prettyNum($trimmed_num,big.mark=",")
reads_base<-prettyNum($total_trimmed_seq_len,big.mark=",")
abline(h=20, col = \"gray60\")
legend(\"bottomleft\",c(paste(\"# Reads: \",reads_num),paste(\"# Bases:\",reads_base)))
## for outliers
#points()
}
#quality 3D plot
persp(x,y,z/1000000,theta = 50, phi = 30, expand = 0.7, col = \"#0000ff22\",ntick=10,ticktype=\"detailed\",xlab=\'Position\',ylab=\'Score\',zlab=\"\",r=6,shade=0.75)
mtext(side=2, \"Frequency (millions)\",line=2)
title(\"Quality 3D plot. (Position vs. Score vs. Frequency)\")
#Quality count bar plot
col<-colSums(z)
less30columnNum<-length(col)-$highest_illumina_score+30-1
atleast30columnNum<-$highest_illumina_score-30+1
color<-c(rep(\'blue\',less30columnNum),rep(\'darkgreen\',atleast30columnNum))
over30per<-sprintf(\"%.2f%%\",sum(col[(less30columnNum+1):length(col)])/sum(col)*100)
countInM<-col/1000000
plot(seq($lowest_illumina_score,$highest_illumina_score,1),countInM,col=color,type='h',ylab=\"Total (million)\",xlab=\"Q score\",lwd=12,lend=2,bty='n')
abline(v=29.5,col='darkgreen')
text(30,(max(countInM)-min(countInM))*0.9,labels=\">=Q30\",cex=0.8,adj=0,col=\'darkgreen\')
text(30,(max(countInM)-min(countInM))*0.85,labels=over30per,cex=0.8,adj=0,col=\'darkgreen\')
title(\"Quality report\")
tmp<-dev.off()
quit()
RSCRIPT
close R;
system ("R --vanilla --silent --quiet < $outDir/tmp$$.R 1>/dev/null");
unless ($debug){system ("rm $outDir/tmp$$.*");}
system ("rm $outDir/Rplots.pdf") if (-e "$outDir/Rplots.pdf");
system ("rm Rplots.pdf") if (-e "Rplots.pdf");
}
sub print_quality_report_files{
open (OUT, ">$quality_matrix");
open (BASE, ">$base_matrix");
foreach my $pos2(sort {$a<=>$b} keys %position){
my $q_string;
my $n_string;
for ($lowest_illumina_score..$highest_illumina_score)
{
if ($position{$pos2}->{$_}){
$q_string .= $position{$pos2}->{$_}."\t";
}
else
{
$q_string .= "0\t";
}
}
for my $base ("A","T","C","G","N")
{
if ($base_position{$pos2}->{$base}){
$n_string .= $base_position{$pos2}->{$base}."\t";
}
else
{
$n_string .= "0\t";
}
}
$q_string =~ s/\t$/\n/;
$n_string =~ s/\t$/\n/;
print OUT $q_string;
print BASE $n_string;
}
close OUT;
close BASE;
open (OUT2, ">$avg_quality_histogram");
my $Key=$highest_illumina_score;
my $h_print_string;
while ($Key >= 0)
{
if(defined $AverageQ{$Key}->{reads}){
$h_print_string .= "$Key\t".
$AverageQ{$Key}->{reads}. "\t".$AverageQ{$Key}->{bases}."\n";
}else{
$h_print_string .= "$Key\t".
"0\t".
"0\n";
}
--$Key;
}
print OUT2 "Score\treadsNum\treadsBases\n";
print OUT2 $h_print_string;
close OUT2;
open (OUT3, ">$nuc_composition_file");
for my $nuc ("A","T","C","G","N","GC")
{
foreach my $key ( sort {$a<=>$b} keys %{$base_content{$nuc}})
{
print OUT3 "$nuc\t$key\t${$base_content{$nuc}}{$key}\n";
}
}
close OUT3;
open (OUT4,">$length_histogram");
my @len_list= sort {$a<=>$b} keys %len_hash;
for my $key (1..$len_list[-1])
{
if ($len_hash{$key})
{
print OUT4 "$key\t$len_hash{$key}\n";
}
else
{
print OUT4 "$key\t0\n";
}
}
close OUT4;
}
sub file_check
{
#check file exist and non zero size
my $file=shift;
my $exist=-1;
if (-e $file) {$exist=1};
if (-z $file) {$exist=-1};
return $exist;
}
sub qc_process {
my ($input, $input2, $basequality) = @_;
my ($h1,$s,$s_trimmed,$h2,$q, $q_trimmed); my $len=0; my $trim_len=0;
my ($r2_h1,$r2_s,$r2_s_trimmed,$r2_h2,$r2_q,$r2_q_trimmed); my $r2_len=0; my $r2_trim_len=0;
my ($q1_nontrim, $s1_nontrim,$q2_nontrim,$s2_nontrim);
my %stats;
my $seq_r;
my $avg_q;
my ($pos5,$pos3);
my $numOfReadsWithAdapter;
my ($raw_seq_num,$total_raw_seq_len);
my ($trim_seq_num_1,$trim_seq_num_2,$trim_seq_len, $total_trim_seq_len,@trim_seq_len);
my ($paired_seq_num,$total_paired_bases);
my (%tmp1,%tmp2);
my ($drop_1,$drop_2)=(1,1);
my ( $i_file_name, $i_path, $i_suffix ) = fileparse( "$input", qr/\.[^.]*/ );
my $trim_output_1="$outDir/${i_file_name}_trim.fastq";
my $qc_output_1="$outDir/${i_file_name}_qc.fastq";
my $qc_output_2;
my $trim_output_2;
my $trim_output_unpaired;
my $trim_output_discard="$outDir/${i_file_name}_trim_discard.fastq";
open(IN,"$input") or die "$input\t$!";
if ($nontrimed_output) { open(OUTQC,"> $qc_output_1"); }
if (! $qc_only)
{
open(OUT,"> $trim_output_1");
open(DISCARD,">$trim_output_discard") if ($output_discard);
}
if ($input2) # paired mate
{
open(IN2,"$input2") or die "$input2\t$!";
my ( $i_file_name, $i_path, $i_suffix ) = fileparse( "$input2", qr/\.[^.]*/ );
$trim_output_2="$outDir/${i_file_name}_trim.fastq";
my $qc_output_2="$outDir/${i_file_name}_qc.fastq";
$trim_output_unpaired="$outDir/${i_file_name}_trim_unpaired.fastq";
if ($nontrimed_output) { open(OUTQC2,"> $qc_output_2"); }
if (! $qc_only)
{
open(OUT2,"> $trim_output_2");
open(UNPAIR,"> $trim_output_unpaired");
}
}
while ($h1 = <IN>) { # read first header
$drop_1=0;
$raw_seq_num++;
$s = <IN>; # read sequence
chomp $s;
$s=uc($s);
$h2 = <IN>; # read second header
$q = <IN>; # read quality scores
chomp $q;
$len = length($q);
$total_raw_seq_len += $len;
$drop_1=1 if ($len < $opt_min_L);
if ($drop_1==0){
($s1_nontrim,$q1_nontrim,$s_trimmed,$q_trimmed,$pos5,$pos3)= &adept_trim($len,$s,$q, $basequality);
$trim_len=length($s_trimmed);
$drop_1=1 if ($trim_len < $opt_min_L);
}
if ($drop_1==0)
{
($seq_r,$drop_1)=&get_base_and_quality_info($s_trimmed,$q_trimmed,$trim_len,$pos5,$pos3,\%stats);
%stats=%{$seq_r};
}
if ($drop_1==0){ # pass all filters...
$q_trimmed=&quality_encoding_coversion($q_trimmed,$ascii,$out_offset) if ($ascii != $out_offset);
$trim_seq_num_1++;
push @trim_seq_len, $trim_len;
$total_trim_seq_len += $trim_len;
}
if ($input2) {
$drop_2=0;
$r2_h1 = <IN2>;
$raw_seq_num++;
$r2_s = <IN2>; # mate read sequence
chomp $r2_s;
$r2_h2 = <IN2>; # mate read second header
$r2_q = <IN2>; # mate read quality scores
chomp $r2_q;
$r2_len = length($r2_q);
$total_raw_seq_len += $r2_len;
$drop_2=1 if ($r2_len < $opt_min_L);
if ($drop_2==0){
($s2_nontrim,$q2_nontrim,$r2_s_trimmed, $r2_q_trimmed, $pos5, $pos3)=&adept_trim($r2_len,$r2_s,$r2_q,$basequality);
$r2_trim_len=length($r2_s_trimmed);
$drop_2=1 if ($r2_trim_len < $opt_min_L);
}
if ($drop_2==0)
{
($seq_r,$drop_2)=&get_base_and_quality_info($r2_s_trimmed,$r2_q_trimmed,$r2_trim_len,$pos5,$pos3,\%stats);
%stats=%{$seq_r};
}
if ($drop_2==0){ # pass all filters
$r2_q_trimmed=&quality_encoding_coversion($r2_q_trimmed,$ascii,$out_offset) if ($ascii != $out_offset);
$trim_seq_num_2++;
push @trim_seq_len, $r2_trim_len;
$total_trim_seq_len += $r2_trim_len;
}
}
if ($drop_1==0 and $drop_2==0)
{
$paired_seq_num +=2;
$total_paired_bases += $trim_len + $r2_trim_len;
}
# output trimmed files
if (! $qc_only)
{
if ($nontrimed_output)
{
print OUTQC $h1.$s1_nontrim."\n".$h2.$q1_nontrim."\n";
if ($input2) { print OUTQC2 $r2_h1.$s2_nontrim."\n".$r2_h2.$q2_nontrim."\n";}
}
if ($drop_1==0 and $drop_2==0)
{
print OUT $h1.$s_trimmed."\n".$h2.$q_trimmed."\n";
print OUT2 $r2_h1.$r2_s_trimmed."\n".$r2_h2.$r2_q_trimmed."\n";
}
elsif ($drop_1==1 and $drop_2==0)
{
print DISCARD $h1.$s."\n".$h2.$q."\n" if ($output_discard);
print UNPAIR $r2_h1.$r2_s_trimmed."\n".$r2_h2.$r2_q_trimmed."\n";
}
elsif ($drop_1==0 and $drop_2==1)
{
if ($input2)
{
print UNPAIR $h1.$s_trimmed."\n".$h2.$q_trimmed."\n";
print DISCARD $r2_h1.$r2_s."\n".$r2_h2.$r2_q."\n" if ($output_discard);
}
else
{
print OUT $h1.$s_trimmed."\n".$h2.$q_trimmed."\n";
}
}
elsif ($output_discard)
{
print DISCARD $h1.$s."\n".$h2.$q."\n";
if ($input2)
{
print DISCARD $r2_h1.$r2_s."\n".$r2_h2.$r2_q."\n";
}
}
}
} # end while
my ($trim_seq_len_std,$trim_seq_len_avg,$max,$min,$median)=&standard_deviation(@trim_seq_len);
close(IN);
close(OUT);
close IN2 if ($input2);
close OUT2 if ($input2);
close UNPAIR if ($input2);
close DISCARD;
$stats{raw_seq_num}=$raw_seq_num;
$stats{trim_seq_num}=$trim_seq_num_1+$trim_seq_num_2;
$stats{trim_seq_num_1}=$trim_seq_num_1;
$stats{trim_seq_num_2}=$trim_seq_num_2;
$stats{total_raw_seq_len}=$total_raw_seq_len;
$stats{total_trim_seq_len}=$total_trim_seq_len;
$stats{trim_seq_len_std}=$trim_seq_len_std;
$stats{trim_seq_len_avg}=$trim_seq_len_avg;
$stats{max}=$max;
$stats{min}=$min;
$stats{median}=$median;
$stats{paired_seq_num}=$paired_seq_num;
$stats{total_paired_bases}=$total_paired_bases;
$stats{trim_file_name_1}=$trim_output_1;
$stats{trim_file_name_2}=$trim_output_2;
$stats{numOfReadsWithAdapter}=$numOfReadsWithAdapter;
return \%stats;
}
sub adept_trim
{
# bwa trim implementation from both 5' and 3' end
# at least scan 5 bases from both end and 2 more bases after the negative area