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main.nf
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#!/usr/bin/env nextflow
/*
========================================================================================
nf-core/rnaseq
========================================================================================
nf-core/rnaseq Analysis Pipeline.
#### Homepage / Documentation
https://github.com/nf-core/rnaseq
----------------------------------------------------------------------------------------
*/
def helpMessage() {
log.info nfcoreHeader()
log.info """
Usage:
The typical command for running the pipeline is as follows:
nextflow run nf-core/rnaseq --reads '*_R{1,2}.fastq.gz' --genome GRCh37 -profile docker
Mandatory arguments:
--reads Path to input data (must be surrounded with quotes)
-profile Configuration profile to use. Can use multiple (comma separated)
Available: conda, docker, singularity, awsbatch, test and more.
Options:
--genome Name of iGenomes reference
--singleEnd Specifies that the input is single end reads
Strandedness:
--forward_stranded The library is forward stranded
--reverse_stranded The library is reverse stranded
--unstranded The default behaviour
References If not specified in the configuration file or you wish to overwrite any of the references.
--star_index Path to STAR index
--hisat2_index Path to HiSAT2 index
--fasta Path to Fasta reference
--gtf Path to GTF file
--gff Path to GFF3 file
--bed12 Path to bed12 file
--saveReference Save the generated reference files the the Results directory.
--saveTrimmed Save trimmed FastQ file intermediates
--saveAlignedIntermediates Save the BAM files from the Aligment step - not done by default
Trimming options
--clip_r1 [int] Instructs Trim Galore to remove bp from the 5' end of read 1 (or single-end reads)
--clip_r2 [int] Instructs Trim Galore to remove bp from the 5' end of read 2 (paired-end reads only)
--three_prime_clip_r1 [int] Instructs Trim Galore to remove bp from the 3' end of read 1 AFTER adapter/quality trimming has been performed
--three_prime_clip_r2 [int] Instructs Trim Galore to re move bp from the 3' end of read 2 AFTER adapter/quality trimming has been performed
Presets:
--pico Sets trimming and standedness settings for the SMARTer Stranded Total RNA-Seq Kit - Pico Input kit. Equivalent to: --forward_stranded --clip_r1 3 --three_prime_clip_r2 3
--fcExtraAttributes Define which extra parameters should also be included in featureCounts (default: gene_names)
--fcGroupFeatures Define the attribute type used to group features. (default: 'gene_name')
--fcGroupFeaturesType Define the type attribute used to group features based on the group attribute (default: 'gene_biotype')
Other options:
--outdir The output directory where the results will be saved
-w/--work-dir The temporary directory where intermediate data will be saved
--email Set this parameter to your e-mail address to get a summary e-mail with details of the run sent to you when the workflow exits
--sampleLevel Used to turn of the edgeR MDS and heatmap. Set automatically when running on fewer than 3 samples
--maxMultiqcEmailFileSize Theshold size for MultiQC report to be attached in notification email. If file generated by pipeline exceeds the threshold, it will not be attached (Default: 25MB)
-name Name for the pipeline run. If not specified, Nextflow will automatically generate a random mnemonic.
--seqCenter Add sequencing center in @RG line of output BAM header
QC options:
--skip_qc Skip all QC steps apart from MultiQC
--skip_fastqc Skip FastQC
--skip_rseqc Skip RSeQC
--skip_genebody_coverage Skip calculating genebody coverage
--skip_preseq Skip Preseq
--skip_dupradar Skip dupRadar (and Picard MarkDups)
--skip_edger Skip edgeR MDS plot and heatmap
--skip_multiqc Skip MultiQC
AWSBatch options:
--awsqueue The AWSBatch JobQueue that needs to be set when running on AWSBatch
--awsregion The AWS Region for your AWS Batch job to run on
""".stripIndent()
}
/*
* SET UP CONFIGURATION VARIABLES
*/
// Show help emssage
if (params.help){
helpMessage()
exit 0
}
// Check if genome exists in the config file
if (params.genomes && params.genome && !params.genomes.containsKey(params.genome)) {
exit 1, "The provided genome '${params.genome}' is not available in the iGenomes file. Currently the available genomes are ${params.genomes.keySet().join(", ")}"
}
// Reference index path configuration
// Define these here - after the profiles are loaded with the iGenomes paths
params.star_index = params.genome ? params.genomes[ params.genome ].star ?: false : false
params.fasta = params.genome ? params.genomes[ params.genome ].fasta ?: false : false
params.gtf = params.genome ? params.genomes[ params.genome ].gtf ?: false : false
params.gff = params.genome ? params.genomes[ params.genome ].gff ?: false : false
params.bed12 = params.genome ? params.genomes[ params.genome ].bed12 ?: false : false
params.hisat2_index = params.genome ? params.genomes[ params.genome ].hisat2 ?: false : false
ch_mdsplot_header = Channel.fromPath("$baseDir/assets/mdsplot_header.txt")
ch_heatmap_header = Channel.fromPath("$baseDir/assets/heatmap_header.txt")
ch_biotypes_header = Channel.fromPath("$baseDir/assets/biotypes_header.txt")
Channel.fromPath("$baseDir/assets/where_are_my_files.txt")
.into{ch_where_trim_galore; ch_where_star; ch_where_hisat2; ch_where_hisat2_sort}
// Define regular variables so that they can be overwritten
clip_r1 = params.clip_r1
clip_r2 = params.clip_r2
three_prime_clip_r1 = params.three_prime_clip_r1
three_prime_clip_r2 = params.three_prime_clip_r2
forward_stranded = params.forward_stranded
reverse_stranded = params.reverse_stranded
unstranded = params.unstranded
// Preset trimming options
if (params.pico){
clip_r1 = 3
clip_r2 = 0
three_prime_clip_r1 = 0
three_prime_clip_r2 = 3
forward_stranded = true
reverse_stranded = false
unstranded = false
}
// Validate inputs
if (params.aligner != 'star' && params.aligner != 'hisat2'){
exit 1, "Invalid aligner option: ${params.aligner}. Valid options: 'star', 'hisat2'"
}
if( params.star_index && params.aligner == 'star' ){
star_index = Channel
.fromPath(params.star_index)
.ifEmpty { exit 1, "STAR index not found: ${params.star_index}" }
}
else if ( params.hisat2_index && params.aligner == 'hisat2' ){
hs2_indices = Channel
.fromPath("${params.hisat2_index}*")
.ifEmpty { exit 1, "HISAT2 index not found: ${params.hisat2_index}" }
}
else if ( params.fasta ){
Channel.fromPath(params.fasta)
.ifEmpty { exit 1, "Fasta file not found: ${params.fasta}" }
.into { ch_fasta_for_star_index; ch_fasta_for_hisat_index}
}
else {
exit 1, "No reference genome specified!"
}
if( params.gtf ){
Channel
.fromPath(params.gtf)
.ifEmpty { exit 1, "GTF annotation file not found: ${params.gtf}" }
.into { gtf_makeSTARindex; gtf_makeHisatSplicesites; gtf_makeHISATindex; gtf_makeBED12;
gtf_star; gtf_dupradar; gtf_featureCounts; gtf_stringtieFPKM }
} else if( params.gff ){
gffFile = Channel.fromPath(params.gff)
.ifEmpty { exit 1, "GFF annotation file not found: ${params.gff}" }
} else {
exit 1, "No GTF or GFF3 annotation specified!"
}
if( params.bed12 ){
bed12 = Channel
.fromPath(params.bed12)
.ifEmpty { exit 1, "BED12 annotation file not found: ${params.bed12}" }
.into {bed_rseqc; bed_genebody_coverage}
}
if( params.aligner == 'hisat2' && params.splicesites ){
Channel
.fromPath(params.bed12)
.ifEmpty { exit 1, "HISAT2 splice sites file not found: $alignment_splicesites" }
.into { indexing_splicesites; alignment_splicesites }
}
if( workflow.profile == 'uppmax' || workflow.profile == 'uppmax-devel' ){
if ( !params.project ) exit 1, "No UPPMAX project ID found! Use --project"
}
// Has the run name been specified by the user?
// this has the bonus effect of catching both -name and --name
custom_runName = params.name
if( !(workflow.runName ==~ /[a-z]+_[a-z]+/) ){
custom_runName = workflow.runName
}
if( workflow.profile == 'awsbatch') {
// AWSBatch sanity checking
if (!params.awsqueue || !params.awsregion) exit 1, "Specify correct --awsqueue and --awsregion parameters on AWSBatch!"
if (!workflow.workDir.startsWith('s3') || !params.outdir.startsWith('s3')) exit 1, "Specify S3 URLs for workDir and outdir parameters on AWSBatch!"
// Check workDir/outdir paths to be S3 buckets if running on AWSBatch
// related: https://github.com/nextflow-io/nextflow/issues/813
if (!workflow.workDir.startsWith('s3:') || !params.outdir.startsWith('s3:')) exit 1, "Workdir or Outdir not on S3 - specify S3 Buckets for each to run on AWSBatch!"
}
// Stage config files
ch_multiqc_config = Channel.fromPath(params.multiqc_config)
ch_output_docs = Channel.fromPath("$baseDir/docs/output.md")
/*
* Create a channel for input read files
*/
if(params.readPaths){
if(params.singleEnd){
Channel
.from(params.readPaths)
.map { row -> [ row[0], [file(row[1][0])]] }
.ifEmpty { exit 1, "params.readPaths was empty - no input files supplied" }
.into { raw_reads_fastqc; raw_reads_trimgalore }
} else {
Channel
.from(params.readPaths)
.map { row -> [ row[0], [file(row[1][0]), file(row[1][1])]] }
.ifEmpty { exit 1, "params.readPaths was empty - no input files supplied" }
.into { raw_reads_fastqc; raw_reads_trimgalore }
}
} else {
Channel
.fromFilePairs( params.reads, size: params.singleEnd ? 1 : 2 )
.ifEmpty { exit 1, "Cannot find any reads matching: ${params.reads}\nNB: Path needs to be enclosed in quotes!\nNB: Path requires at least one * wildcard!\nIf this is single-end data, please specify --singleEnd on the command line." }
.into { raw_reads_fastqc; raw_reads_trimgalore }
}
// Header log info
log.info nfcoreHeader()
def summary = [:]
if(workflow.revision) summary['Pipeline Release'] = workflow.revision
summary['Run Name'] = custom_runName ?: workflow.runName
summary['Reads'] = params.reads
summary['Data Type'] = params.singleEnd ? 'Single-End' : 'Paired-End'
if(params.genome) summary['Genome'] = params.genome
if(params.pico) summary['Library Prep'] = "SMARTer Stranded Total RNA-Seq Kit - Pico Input"
summary['Strandedness'] = ( unstranded ? 'None' : forward_stranded ? 'Forward' : reverse_stranded ? 'Reverse' : 'None' )
summary['Trimming'] = "5'R1: $clip_r1 / 5'R2: $clip_r2 / 3'R1: $three_prime_clip_r1 / 3'R2: $three_prime_clip_r2"
if(params.aligner == 'star'){
summary['Aligner'] = "STAR"
if(params.star_index) summary['STAR Index'] = params.star_index
else if(params.fasta) summary['Fasta Ref'] = params.fasta
} else if(params.aligner == 'hisat2') {
summary['Aligner'] = "HISAT2"
if(params.hisat2_index) summary['HISAT2 Index'] = params.hisat2_index
else if(params.fasta) summary['Fasta Ref'] = params.fasta
if(params.splicesites) summary['Splice Sites'] = params.splicesites
}
if(params.gtf) summary['GTF Annotation'] = params.gtf
if(params.gff) summary['GFF3 Annotation'] = params.gff
if(params.bed12) summary['BED Annotation'] = params.bed12
summary['Save prefs'] = "Ref Genome: "+(params.saveReference ? 'Yes' : 'No')+" / Trimmed FastQ: "+(params.saveTrimmed ? 'Yes' : 'No')+" / Alignment intermediates: "+(params.saveAlignedIntermediates ? 'Yes' : 'No')
summary['Max Resources'] = "$params.max_memory memory, $params.max_cpus cpus, $params.max_time time per job"
if(workflow.containerEngine) summary['Container'] = "$workflow.containerEngine - $workflow.container"
summary['Output dir'] = params.outdir
summary['Launch dir'] = workflow.launchDir
summary['Working dir'] = workflow.workDir
summary['Script dir'] = workflow.projectDir
summary['User'] = workflow.userName
if(workflow.profile == 'awsbatch'){
summary['AWS Region'] = params.awsregion
summary['AWS Queue'] = params.awsqueue
}
summary['Config Profile'] = workflow.profile
if(params.config_profile_description) summary['Config Description'] = params.config_profile_description
if(params.config_profile_contact) summary['Config Contact'] = params.config_profile_contact
if(params.config_profile_url) summary['Config URL'] = params.config_profile_url
if(params.email) {
summary['E-mail Address'] = params.email
summary['MultiQC maxsize'] = params.maxMultiqcEmailFileSize
}
log.info summary.collect { k,v -> "${k.padRight(18)}: $v" }.join("\n")
log.info "\033[2m----------------------------------------------------\033[0m"
// Check the hostnames against configured profiles
checkHostname()
def create_workflow_summary(summary) {
def yaml_file = workDir.resolve('workflow_summary_mqc.yaml')
yaml_file.text = """
id: 'nf-core-rnaseq-summary'
description: " - this information is collected when the pipeline is started."
section_name: 'nf-core/rnaseq Workflow Summary'
section_href: 'https://github.com/nf-core/rnaseq'
plot_type: 'html'
data: |
<dl class=\"dl-horizontal\">
${summary.collect { k,v -> " <dt>$k</dt><dd><samp>${v ?: '<span style=\"color:#999999;\">N/A</a>'}</samp></dd>" }.join("\n")}
</dl>
""".stripIndent()
return yaml_file
}
/*
* Parse software version numbers
*/
process get_software_versions {
output:
file 'software_versions_mqc.yaml' into software_versions_yaml
script:
"""
echo $workflow.manifest.version &> v_ngi_rnaseq.txt
echo $workflow.nextflow.version &> v_nextflow.txt
fastqc --version &> v_fastqc.txt
cutadapt --version &> v_cutadapt.txt
trim_galore --version &> v_trim_galore.txt
STAR --version &> v_star.txt
hisat2 --version &> v_hisat2.txt
stringtie --version &> v_stringtie.txt
preseq &> v_preseq.txt
read_duplication.py --version &> v_rseqc.txt
echo \$(bamCoverage --version 2>&1) > v_deeptools.txt
featureCounts -v &> v_featurecounts.txt
picard MarkDuplicates --version &> v_markduplicates.txt || true
samtools --version &> v_samtools.txt
multiqc --version &> v_multiqc.txt
scrape_software_versions.py &> software_versions_mqc.yaml
"""
}
/*
* PREPROCESSING - Build STAR index
*/
if(params.aligner == 'star' && !params.star_index && params.fasta){
process makeSTARindex {
label 'high_memory'
tag "$fasta"
publishDir path: { params.saveReference ? "${params.outdir}/reference_genome" : params.outdir },
saveAs: { params.saveReference ? it : null }, mode: 'copy'
input:
file fasta from ch_fasta_for_star_index
file gtf from gtf_makeSTARindex
output:
file "star" into star_index
script:
def avail_mem = task.memory ? "--limitGenomeGenerateRAM ${task.memory.toBytes() - 100000000}" : ''
"""
mkdir star
STAR \\
--runMode genomeGenerate \\
--runThreadN ${task.cpus} \\
--sjdbGTFfile $gtf \\
--genomeDir star/ \\
--genomeFastaFiles $fasta \\
$avail_mem
"""
}
}
/*
* PREPROCESSING - Build HISAT2 splice sites file
*/
if(params.aligner == 'hisat2' && !params.splicesites){
process makeHisatSplicesites {
tag "$gtf"
publishDir path: { params.saveReference ? "${params.outdir}/reference_genome" : params.outdir },
saveAs: { params.saveReference ? it : null }, mode: 'copy'
input:
file gtf from gtf_makeHisatSplicesites
output:
file "${gtf.baseName}.hisat2_splice_sites.txt" into indexing_splicesites, alignment_splicesites
script:
"""
hisat2_extract_splice_sites.py $gtf > ${gtf.baseName}.hisat2_splice_sites.txt
"""
}
}
/*
* PREPROCESSING - Build HISAT2 index
*/
if(params.aligner == 'hisat2' && !params.hisat2_index && params.fasta){
process makeHISATindex {
tag "$fasta"
publishDir path: { params.saveReference ? "${params.outdir}/reference_genome" : params.outdir },
saveAs: { params.saveReference ? it : null }, mode: 'copy'
input:
file fasta from ch_fasta_for_hisat_index
file indexing_splicesites from indexing_splicesites
file gtf from gtf_makeHISATindex
output:
file "${fasta.baseName}.*.ht2*" into hs2_indices
script:
if( !task.memory ){
log.info "[HISAT2 index build] Available memory not known - defaulting to 0. Specify process memory requirements to change this."
avail_mem = 0
} else {
log.info "[HISAT2 index build] Available memory: ${task.memory}"
avail_mem = task.memory.toGiga()
}
if( avail_mem > params.hisatBuildMemory ){
log.info "[HISAT2 index build] Over ${params.hisatBuildMemory} GB available, so using splice sites and exons in HISAT2 index"
extract_exons = "hisat2_extract_exons.py $gtf > ${gtf.baseName}.hisat2_exons.txt"
ss = "--ss $indexing_splicesites"
exon = "--exon ${gtf.baseName}.hisat2_exons.txt"
} else {
log.info "[HISAT2 index build] Less than ${params.hisatBuildMemory} GB available, so NOT using splice sites and exons in HISAT2 index."
log.info "[HISAT2 index build] Use --hisatBuildMemory [small number] to skip this check."
extract_exons = ''
ss = ''
exon = ''
}
"""
$extract_exons
hisat2-build -p ${task.cpus} $ss $exon $fasta ${fasta.baseName}.hisat2_index
"""
}
}
/*
* PREPROCESSING - Convert GFF3 to GTF
*/
if(params.gff){
process convertGFFtoGTF {
tag "$gff"
input:
file gff from gffFile
output:
file "${gff.baseName}.gtf" into gtf_makeSTARindex, gtf_makeHisatSplicesites, gtf_makeHISATindex, gtf_makeBED12,
gtf_star, gtf_dupradar, gtf_featureCounts, gtf_stringtieFPKM
script:
"""
gffread $gff -T -o ${gff.baseName}.gtf
"""
}
}
/*
* PREPROCESSING - Build BED12 file
*/
if(!params.bed12){
process makeBED12 {
tag "$gtf"
publishDir path: { params.saveReference ? "${params.outdir}/reference_genome" : params.outdir },
saveAs: { params.saveReference ? it : null }, mode: 'copy'
input:
file gtf from gtf_makeBED12
output:
file "${gtf.baseName}.bed" into bed_rseqc, bed_genebody_coverage
script: // This script is bundled with the pipeline, in nfcore/rnaseq/bin/
"""
gtf2bed $gtf > ${gtf.baseName}.bed
"""
}
}
/*
* STEP 1 - FastQC
*/
process fastqc {
tag "$name"
publishDir "${params.outdir}/fastqc", mode: 'copy',
saveAs: {filename -> filename.indexOf(".zip") > 0 ? "zips/$filename" : "$filename"}
when:
!params.skip_qc && !params.skip_fastqc
input:
set val(name), file(reads) from raw_reads_fastqc
output:
file "*_fastqc.{zip,html}" into fastqc_results
script:
"""
fastqc -q $reads
"""
}
/*
* STEP 2 - Trim Galore!
*/
process trim_galore {
label 'low_memory'
tag "$name"
publishDir "${params.outdir}/trim_galore", mode: 'copy',
saveAs: {filename ->
if (filename.indexOf("_fastqc") > 0) "FastQC/$filename"
else if (filename.indexOf("trimming_report.txt") > 0) "logs/$filename"
else if (!params.saveTrimmed && filename == "where_are_my_files.txt") filename
else if (params.saveTrimmed && filename != "where_are_my_files.txt") filename
else null
}
input:
set val(name), file(reads) from raw_reads_trimgalore
file wherearemyfiles from ch_where_trim_galore.collect()
output:
file "*fq.gz" into trimmed_reads
file "*trimming_report.txt" into trimgalore_results
file "*_fastqc.{zip,html}" into trimgalore_fastqc_reports
file "where_are_my_files.txt"
script:
c_r1 = clip_r1 > 0 ? "--clip_r1 ${clip_r1}" : ''
c_r2 = clip_r2 > 0 ? "--clip_r2 ${clip_r2}" : ''
tpc_r1 = three_prime_clip_r1 > 0 ? "--three_prime_clip_r1 ${three_prime_clip_r1}" : ''
tpc_r2 = three_prime_clip_r2 > 0 ? "--three_prime_clip_r2 ${three_prime_clip_r2}" : ''
if (params.singleEnd) {
"""
trim_galore --fastqc --gzip $c_r1 $tpc_r1 $reads
"""
} else {
"""
trim_galore --paired --fastqc --gzip $c_r1 $c_r2 $tpc_r1 $tpc_r2 $reads
"""
}
}
/*
* STEP 3 - align with STAR
*/
// Function that checks the alignment rate of the STAR output
// and returns true if the alignment passed and otherwise false
skipped_poor_alignment = []
def check_log(logs) {
def percent_aligned = 0;
logs.eachLine { line ->
if ((matcher = line =~ /Uniquely mapped reads %\s*\|\s*([\d\.]+)%/)) {
percent_aligned = matcher[0][1]
}
}
logname = logs.getBaseName() - 'Log.final'
if(percent_aligned.toFloat() <= '5'.toFloat() ){
log.info "#################### VERY POOR ALIGNMENT RATE! IGNORING FOR FURTHER DOWNSTREAM ANALYSIS! ($logname) >> ${percent_aligned}% <<"
skipped_poor_alignment << logname
return false
} else {
log.info " Passed alignment > star ($logname) >> ${percent_aligned}% <<"
return true
}
}
if(params.aligner == 'star'){
hisat_stdout = Channel.from(false)
process star {
label 'high_memory'
tag "$prefix"
publishDir "${params.outdir}/STAR", mode: 'copy',
saveAs: {filename ->
if (filename.indexOf(".bam") == -1) "logs/$filename"
else if (!params.saveAlignedIntermediates && filename == "where_are_my_files.txt") filename
else if (params.saveAlignedIntermediates && filename != "where_are_my_files.txt") filename
else null
}
input:
file reads from trimmed_reads
file index from star_index.collect()
file gtf from gtf_star.collect()
file wherearemyfiles from ch_where_star.collect()
output:
set file("*Log.final.out"), file ('*.bam') into star_aligned
file "*.out" into alignment_logs
file "*SJ.out.tab"
file "*Log.out" into star_log
file "where_are_my_files.txt"
file "${prefix}Aligned.sortedByCoord.out.bam.bai" into bam_index_rseqc, bam_index_genebody
script:
prefix = reads[0].toString() - ~/(_R1)?(_trimmed)?(_val_1)?(\.fq)?(\.fastq)?(\.gz)?$/
def star_mem = task.memory ?: params.star_memory ?: false
def avail_mem = star_mem ? "--limitBAMsortRAM ${star_mem.toBytes() - 100000000}" : ''
seqCenter = params.seqCenter ? "--outSAMattrRGline ID:$prefix 'CN:$params.seqCenter'" : ''
"""
STAR --genomeDir $index \\
--sjdbGTFfile $gtf \\
--readFilesIn $reads \\
--runThreadN ${task.cpus} \\
--twopassMode Basic \\
--outWigType bedGraph \\
--outSAMtype BAM SortedByCoordinate $avail_mem \\
--readFilesCommand zcat \\
--runDirPerm All_RWX \\
--outFileNamePrefix $prefix $seqCenter
samtools index ${prefix}Aligned.sortedByCoord.out.bam
"""
}
// Filter removes all 'aligned' channels that fail the check
star_aligned
.filter { logs, bams -> check_log(logs) }
.flatMap { logs, bams -> bams }
.into { bam_count; bam_rseqc; bam_preseq; bam_markduplicates; bam_featurecounts; bam_stringtieFPKM; bam_forSubsamp; bam_skipSubsamp }
}
/*
* STEP 3 - align with HISAT2
*/
if(params.aligner == 'hisat2'){
star_log = Channel.from(false)
process hisat2Align {
label 'high_memory'
tag "$prefix"
publishDir "${params.outdir}/HISAT2", mode: 'copy',
saveAs: {filename ->
if (filename.indexOf(".hisat2_summary.txt") > 0) "logs/$filename"
else if (!params.saveAlignedIntermediates && filename == "where_are_my_files.txt") filename
else if (params.saveAlignedIntermediates && filename != "where_are_my_files.txt") filename
else null
}
input:
file reads from trimmed_reads
file hs2_indices from hs2_indices.collect()
file alignment_splicesites from alignment_splicesites.collect()
file wherearemyfiles from ch_where_hisat2.collect()
output:
file "${prefix}.bam" into hisat2_bam
file "${prefix}.hisat2_summary.txt" into alignment_logs
file "where_are_my_files.txt"
script:
index_base = hs2_indices[0].toString() - ~/.\d.ht2l?/
prefix = reads[0].toString() - ~/(_R1)?(_trimmed)?(_val_1)?(\.fq)?(\.fastq)?(\.gz)?$/
seqCenter = params.seqCenter ? "--rg-id ${prefix} --rg CN:${params.seqCenter.replaceAll('\\s','_')}" : ''
def rnastrandness = ''
if (forward_stranded && !unstranded){
rnastrandness = params.singleEnd ? '--rna-strandness F' : '--rna-strandness FR'
} else if (reverse_stranded && !unstranded){
rnastrandness = params.singleEnd ? '--rna-strandness R' : '--rna-strandness RF'
}
if (params.singleEnd) {
"""
hisat2 -x $index_base \\
-U $reads \\
$rnastrandness \\
--known-splicesite-infile $alignment_splicesites \\
-p ${task.cpus} \\
--met-stderr \\
--new-summary \\
--summary-file ${prefix}.hisat2_summary.txt $seqCenter \\
| samtools view -bS -F 4 -F 256 - > ${prefix}.bam
"""
} else {
"""
hisat2 -x $index_base \\
-1 ${reads[0]} \\
-2 ${reads[1]} \\
$rnastrandness \\
--known-splicesite-infile $alignment_splicesites \\
--no-mixed \\
--no-discordant \\
-p ${task.cpus} \\
--met-stderr \\
--new-summary \\
--summary-file ${prefix}.hisat2_summary.txt $seqCenter \\
| samtools view -bS -F 4 -F 8 -F 256 - > ${prefix}.bam
"""
}
}
process hisat2_sortOutput {
label 'mid_memory'
tag "${hisat2_bam.baseName}"
publishDir "${params.outdir}/HISAT2", mode: 'copy',
saveAs: { filename ->
if (!params.saveAlignedIntermediates && filename == "where_are_my_files.txt") filename
else if (params.saveAlignedIntermediates && filename != "where_are_my_files.txt") "aligned_sorted/$filename"
else null
}
input:
file hisat2_bam
file wherearemyfiles from ch_where_hisat2_sort.collect()
output:
file "${hisat2_bam.baseName}.sorted.bam" into bam_count, bam_rseqc, bam_preseq, bam_markduplicates, bam_featurecounts, bam_stringtieFPKM,bam_forSubsamp, bam_skipSubsamp
file "${hisat2_bam.baseName}.sorted.bam.bai" into bam_index_rseqc, bam_index_genebody
file "where_are_my_files.txt"
script:
def suff_mem = ("${(task.memory.toBytes() - 6000000000) / task.cpus}" > 2000000000) ? 'true' : 'false'
def avail_mem = (task.memory && suff_mem) ? "-m" + "${(task.memory.toBytes() - 6000000000) / task.cpus}" : ''
"""
samtools sort \\
$hisat2_bam \\
-@ ${task.cpus} ${avail_mem} \\
-o ${hisat2_bam.baseName}.sorted.bam
samtools index ${hisat2_bam.baseName}.sorted.bam
"""
}
}
/*
* STEP 4 - RSeQC analysis
*/
process rseqc {
label 'mid_memory'
tag "${bam_rseqc.baseName - '.sorted'}"
publishDir "${params.outdir}/rseqc" , mode: 'copy',
saveAs: {filename ->
if (filename.indexOf("bam_stat.txt") > 0) "bam_stat/$filename"
else if (filename.indexOf("infer_experiment.txt") > 0) "infer_experiment/$filename"
else if (filename.indexOf("read_distribution.txt") > 0) "read_distribution/$filename"
else if (filename.indexOf("read_duplication.DupRate_plot.pdf") > 0) "read_duplication/$filename"
else if (filename.indexOf("read_duplication.DupRate_plot.r") > 0) "read_duplication/rscripts/$filename"
else if (filename.indexOf("read_duplication.pos.DupRate.xls") > 0) "read_duplication/dup_pos/$filename"
else if (filename.indexOf("read_duplication.seq.DupRate.xls") > 0) "read_duplication/dup_seq/$filename"
else if (filename.indexOf("RPKM_saturation.eRPKM.xls") > 0) "RPKM_saturation/rpkm/$filename"
else if (filename.indexOf("RPKM_saturation.rawCount.xls") > 0) "RPKM_saturation/counts/$filename"
else if (filename.indexOf("RPKM_saturation.saturation.pdf") > 0) "RPKM_saturation/$filename"
else if (filename.indexOf("RPKM_saturation.saturation.r") > 0) "RPKM_saturation/rscripts/$filename"
else if (filename.indexOf("inner_distance.txt") > 0) "inner_distance/$filename"
else if (filename.indexOf("inner_distance_freq.txt") > 0) "inner_distance/data/$filename"
else if (filename.indexOf("inner_distance_plot.r") > 0) "inner_distance/rscripts/$filename"
else if (filename.indexOf("inner_distance_plot.pdf") > 0) "inner_distance/plots/$filename"
else if (filename.indexOf("junction_plot.r") > 0) "junction_annotation/rscripts/$filename"
else if (filename.indexOf("junction.xls") > 0) "junction_annotation/data/$filename"
else if (filename.indexOf("splice_events.pdf") > 0) "junction_annotation/events/$filename"
else if (filename.indexOf("splice_junction.pdf") > 0) "junction_annotation/junctions/$filename"
else if (filename.indexOf("junctionSaturation_plot.pdf") > 0) "junction_saturation/$filename"
else if (filename.indexOf("junctionSaturation_plot.r") > 0) "junction_saturation/rscripts/$filename"
else filename
}
when:
!params.skip_qc && !params.skip_rseqc
input:
file bam_rseqc
file index from bam_index_rseqc
file bed12 from bed_rseqc.collect()
output:
file "*.{txt,pdf,r,xls}" into rseqc_results
script:
"""
infer_experiment.py -i $bam_rseqc -r $bed12 > ${bam_rseqc.baseName}.infer_experiment.txt
junction_annotation.py -i $bam_rseqc -o ${bam_rseqc.baseName}.rseqc -r $bed12
bam_stat.py -i $bam_rseqc 2> ${bam_rseqc.baseName}.bam_stat.txt
junction_saturation.py -i $bam_rseqc -o ${bam_rseqc.baseName}.rseqc -r $bed12 2> ${bam_rseqc.baseName}.junction_annotation_log.txt
inner_distance.py -i $bam_rseqc -o ${bam_rseqc.baseName}.rseqc -r $bed12
read_distribution.py -i $bam_rseqc -r $bed12 > ${bam_rseqc.baseName}.read_distribution.txt
read_duplication.py -i $bam_rseqc -o ${bam_rseqc.baseName}.read_duplication
"""
}
/*
* Step 4.1 Subsample the BAM files if necessary
*/
bam_forSubsamp
.filter { it.size() > params.subsampFilesizeThreshold }
.map { [it, params.subsampFilesizeThreshold / it.size() ] }
.set{ bam_forSubsampFiltered }
bam_skipSubsamp
.filter { it.size() <= params.subsampFilesizeThreshold }
.set{ bam_skipSubsampFiltered }
process bam_subsample {
tag "${bam.baseName - '.sorted'}"
input:
set file(bam), val(fraction) from bam_forSubsampFiltered
output:
file "*_subsamp.bam" into bam_subsampled
script:
"""
samtools view -s $fraction -b $bam | samtools sort -o ${bam.baseName}_subsamp.bam
"""
}
/*
* Step 4.2 Rseqc genebody_coverage
*/
process genebody_coverage {
label 'mid_memory'
tag "${bam.baseName - '.sorted'}"
publishDir "${params.outdir}/rseqc" , mode: 'copy',
saveAs: {filename ->
if (filename.indexOf("geneBodyCoverage.curves.pdf") > 0) "geneBodyCoverage/$filename"
else if (filename.indexOf("geneBodyCoverage.r") > 0) "geneBodyCoverage/rscripts/$filename"
else if (filename.indexOf("geneBodyCoverage.txt") > 0) "geneBodyCoverage/data/$filename"
else if (filename.indexOf("log.txt") > -1) false
else filename
}
when:
!params.skip_qc && !params.skip_genebody_coverage
input:
file bam from bam_subsampled.concat(bam_skipSubsampFiltered)
file bed12 from bed_genebody_coverage.collect()
output:
file "*.{txt,pdf,r}" into genebody_coverage_results
script:
"""
samtools index $bam
geneBody_coverage.py \\
-i $bam \\
-o ${bam.baseName}.rseqc \\
-r $bed12
mv log.txt ${bam.baseName}.rseqc.log.txt
"""
}
/*
* STEP 5 - preseq analysis
*/
process preseq {
tag "${bam_preseq.baseName - '.sorted'}"
publishDir "${params.outdir}/preseq", mode: 'copy'
when:
!params.skip_qc && !params.skip_preseq
input:
file bam_preseq
output:
file "${bam_preseq.baseName}.ccurve.txt" into preseq_results
script:
"""
preseq lc_extrap -v -B $bam_preseq -o ${bam_preseq.baseName}.ccurve.txt
"""
}
/*
* STEP 6 Mark duplicates
*/
process markDuplicates {
tag "${bam.baseName - '.sorted'}"
publishDir "${params.outdir}/markDuplicates", mode: 'copy',
saveAs: {filename -> filename.indexOf("_metrics.txt") > 0 ? "metrics/$filename" : "$filename"}
when:
!params.skip_qc && !params.skip_dupradar
input:
file bam from bam_markduplicates
output:
file "${bam.baseName}.markDups.bam" into bam_md
file "${bam.baseName}.markDups_metrics.txt" into picard_results
file "${bam.baseName}.markDups.bam.bai"
script:
markdup_java_options = (task.memory.toGiga() > 8) ? ${params.markdup_java_options} : "\"-Xms" + (task.memory.toGiga() / 2 )+"g "+ "-Xmx" + (task.memory.toGiga() - 1)+ "g\""
"""
picard ${markdup_java_options} MarkDuplicates \\
INPUT=$bam \\
OUTPUT=${bam.baseName}.markDups.bam \\
METRICS_FILE=${bam.baseName}.markDups_metrics.txt \\
REMOVE_DUPLICATES=false \\
ASSUME_SORTED=true \\
PROGRAM_RECORD_ID='null' \\
VALIDATION_STRINGENCY=LENIENT
samtools index ${bam.baseName}.markDups.bam
"""
}
/*
* STEP 7 - dupRadar
*/
process dupradar {
label 'low_memory'
tag "${bam_md.baseName - '.sorted.markDups'}"
publishDir "${params.outdir}/dupradar", mode: 'copy',
saveAs: {filename ->
if (filename.indexOf("_duprateExpDens.pdf") > 0) "scatter_plots/$filename"
else if (filename.indexOf("_duprateExpBoxplot.pdf") > 0) "box_plots/$filename"
else if (filename.indexOf("_expressionHist.pdf") > 0) "histograms/$filename"
else if (filename.indexOf("_dupMatrix.txt") > 0) "gene_data/$filename"
else if (filename.indexOf("_duprateExpDensCurve.txt") > 0) "scatter_curve_data/$filename"
else if (filename.indexOf("_intercept_slope.txt") > 0) "intercepts_slopes/$filename"
else "$filename"
}
when:
!params.skip_qc && !params.skip_dupradar
input:
file bam_md
file gtf from gtf_dupradar.collect()
output:
file "*.{pdf,txt}" into dupradar_results
script: // This script is bundled with the pipeline, in nfcore/rnaseq/bin/
def dupradar_direction = 0
if (forward_stranded && !unstranded) {
dupradar_direction = 1
} else if (reverse_stranded && !unstranded){
dupradar_direction = 2
}
def paired = params.singleEnd ? 'single' : 'paired'
"""
dupRadar.r $bam_md $gtf $dupradar_direction $paired ${task.cpus}
"""
}
/*
* STEP 8 Feature counts
*/
process featureCounts {
label 'low_memory'
tag "${bam_featurecounts.baseName - '.sorted'}"
publishDir "${params.outdir}/featureCounts", mode: 'copy',
saveAs: {filename ->
if (filename.indexOf("biotype_counts") > 0) "biotype_counts/$filename"
else if (filename.indexOf("_gene.featureCounts.txt.summary") > 0) "gene_count_summaries/$filename"
else if (filename.indexOf("_gene.featureCounts.txt") > 0) "gene_counts/$filename"
else "$filename"
}
input:
file bam_featurecounts
file gtf from gtf_featureCounts.collect()
file biotypes_header from ch_biotypes_header.collect()
output:
file "${bam_featurecounts.baseName}_gene.featureCounts.txt" into geneCounts, featureCounts_to_merge
file "${bam_featurecounts.baseName}_gene.featureCounts.txt.summary" into featureCounts_logs
file "${bam_featurecounts.baseName}_biotype_counts*mqc.{txt,tsv}" into featureCounts_biotype
script:
def featureCounts_direction = 0
def extraAttributes = params.fcExtraAttributes ? "--extraAttributes ${params.fcExtraAttributes}" : ''
if (forward_stranded && !unstranded) {
featureCounts_direction = 1
} else if (reverse_stranded && !unstranded){
featureCounts_direction = 2
}
// Try to get real sample name
sample_name = bam_featurecounts.baseName - 'Aligned.sortedByCoord.out'
"""
featureCounts -a $gtf -g ${params.fcGroupFeatures} -o ${bam_featurecounts.baseName}_gene.featureCounts.txt $extraAttributes -p -s $featureCounts_direction $bam_featurecounts
featureCounts -a $gtf -g ${params.fcGroupFeaturesType} -o ${bam_featurecounts.baseName}_biotype.featureCounts.txt -p -s $featureCounts_direction $bam_featurecounts
cut -f 1,7 ${bam_featurecounts.baseName}_biotype.featureCounts.txt | tail -n +3 | cat $biotypes_header - >> ${bam_featurecounts.baseName}_biotype_counts_mqc.txt
mqc_features_stat.py ${bam_featurecounts.baseName}_biotype_counts_mqc.txt -s $sample_name -f rRNA -o ${bam_featurecounts.baseName}_biotype_counts_gs_mqc.tsv
"""
}
/*
* STEP 9 - Merge featurecounts
*/
process merge_featureCounts {
tag "${input_files[0].baseName - '.sorted'}"
publishDir "${params.outdir}/featureCounts", mode: 'copy'
input:
file input_files from featureCounts_to_merge.collect()
output:
file 'merged_gene_counts.txt'
script:
//if we only have 1 file, just use cat and pipe output to csvtk. Else join all files first, and then remove unwanted column names.
def single = input_files instanceof Path ? 1 : input_files.size()
def merge = (single == 1) ? 'cat' : 'csvtk join -t -f "Geneid,Start,Length,End,Chr,Strand,gene_name"'
"""
$merge $input_files | csvtk cut -t -f "-Start,-Chr,-End,-Length,-Strand" | sed 's/Aligned.sortedByCoord.out.markDups.bam//g' > merged_gene_counts.txt
"""
}
/*
* STEP 10 - stringtie FPKM
*/
process stringtieFPKM {
tag "${bam_stringtieFPKM.baseName - '.sorted'}"
publishDir "${params.outdir}/stringtieFPKM", mode: 'copy',
saveAs: {filename ->
if (filename.indexOf("transcripts.gtf") > 0) "transcripts/$filename"