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main.nf
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main.nf
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#!/usr/bin/env nextflow
/*
========================================================================================
nf-core/cageseq
========================================================================================
nf-core/cageseq Analysis Pipeline.
#### Homepage / Documentation
https://github.com/nf-core/cageseq
----------------------------------------------------------------------------------------
*/
def helpMessage() {
log.info nfcoreHeader()
log.info"""
Usage:
The typical command for running the pipeline is as follows:
nextflow run nf-core/cageseq --input '*_R1.fastq.gz' -profile docker
Mandatory arguments:
--input [file] Path to input data (must be surrounded with quotes)
-profile [str] Configuration profile to use. Can use multiple (comma separated)
Available: docker, singularity, conda, test, awsbatch, <institute> and more
Trimming:
--save_trimmed [bool] Set to true to Save trimmed FastQ files
--trim_ecop [bool] Set to false to not trim the EcoP site
--trim_linker [bool] Set to false to not trim the linker
--trim_5g [bool] Set to false to not trim the additonal G at the 5' end
--trim_artifacts [bool] Set to false to not trim artifacts
--artifacts_5end [file] Path to 5 end artifact file, if not given the pipeline will use a default file with all possible artifacts
--artifacts_3end [file] Path to 3 end artifact file, if not given the pipeline will use a default file with all possible artifacts
References If not specified in the configuration file or you wish to overwrite any of the references
--fasta [file] Path to fasta reference
--genome [str] Name of iGenomes reference
--gtf [file] Path to gtf file, used to generate the STAR index, for STAR alignment and for the clustering QC
Ribosomal RNA removal:
--remove_ribo_rna [bool] Removes ribosomal RNA using SortMeRNA
--save_non_ribo_reads [bool] Save FastQ file intermediates after removing rRNA
--ribo_database_manifest [string] Path to file that contains file paths for rRNA databases, optional
Alignment:
--aligner [str] Specifies the aligner to use (available are: 'star', 'bowtie1')
--star_index [file] Path to STAR index, set to false if igenomes should be used
--bowtie_index [file] Path to bowtie index, set to false if igenomes should be used
Clustering:
--min_cluster [int] Minimum amount of reads to build a cluster with paraclu. Default ${params.min_cluster}
--tpm_cluster_threshold [int] --tpm_cluster_threshold [int] Threshold for expression count of ctss considered in paraclu clustering. Default: ${params.tpm_cluster_threshold}
Output:
--bigwig [bool] Set this option to get ctss files in bigwig-format, in addition to the default in bed-format
Skipping options:
--skip_initial_fastqc [bool] Skip FastQC run on input reads
--skip_trimming [bool] Skip all trimming steps
--skip_trimming_fastqc [bool] Skip FastQC run on trimmed reads
--skip_alignment [bool] Skip alignment step
--skip_samtools_stats [bool] Skip samtools stats QC step of aligned reads
--skip_ctss_generation [bool] Skip steps generating CTSS files including clustering, bed/bigwig and count table output generation
--skip_ctss_qc [bool] Skip running RSeQC's read distribution QC step on the clustered CTSS
Other options:
--outdir [file] The output directory where the results will be saved
--publish_dir_mode [str] Mode for publishing results in the output directory. Available: symlink, rellink, link, copy, copyNoFollow, move (Default: copy)
--email [email] Set this parameter to your e-mail address to get a summary e-mail with details of the run sent to you when the workflow exits
--email_on_fail [email] Same as --email, except only send mail if the workflow is not successful
--max_multiqc_email_size [str] Threshold size for MultiQC report to be attached in notification email. If file generated by pipeline exceeds the threshold, it will not be attached (Default: 25MB)
-name [str] Name for the pipeline run. If not specified, Nextflow will automatically generate a random mnemonic
AWSBatch options:
--awsqueue [str] The AWSBatch JobQueue that needs to be set when running on AWSBatch
--awsregion [str] The AWS Region for your AWS Batch job to run on
--awscli [str] Path to the AWS CLI tool
""".stripIndent()
}
// Show help message
if (params.help) {
helpMessage()
exit 0
}
/*
* SET UP CONFIGURATION VARIABLES
*/
// Check if genome exists in the config file
if (params.genomes && params.genome && !params.genomes.containsKey(params.genome)) {
exit 1, "The provided genome '${params.genome}' is not available in the iGenomes file. Currently the available genomes are ${params.genomes.keySet().join(", ")}"
}
params.star_index = params.genome ? params.genomes[ params.genome ].star ?: false : false
params.bowtie_index = params.genome ? params.genomes[ params.genome ].bowtie1 ?: false : false
params.fasta = params.genome ? params.genomes[ params.genome ].fasta ?: false : false
params.gtf = params.genome ? params.genomes[ params.genome ].gtf ?: false : false
// Get rRNA databases
// Default is set to bundled DB list in `assets/rrna-db-defaults.txt`
ribo_database = file(params.ribo_database_manifest)
if (ribo_database.isEmpty()) {exit 1, "File ${ribo_database.getName()} is empty!"}
Channel
.from( ribo_database.readLines() )
.map { row -> file(row) }
.set { fasta_sortmerna }
// Validate inputs
if (params.aligner != 'star' && params.aligner != 'bowtie1') {
exit 1, "Invalid aligner option: ${params.aligner}. Valid options: 'star', 'bowtie1'"
}
if( params.star_index && params.aligner == 'star' ){
star_index = Channel
.fromPath(params.star_index, checkIfExists: true)
.ifEmpty { exit 1, "STAR index not found: ${params.star_index}" }
}
else if( params.bowtie_index && params.aligner == 'bowtie1' ){
bowtie_index = Channel
.fromPath(params.bowtie_index, checkIfExists: true)
.ifEmpty { exit 1, "bowtie index not found: ${params.bowtie_index}" }
}
else if ( params.fasta ){
Channel
.fromPath(params.fasta, checkIfExists: true)
.ifEmpty { exit 1, "fasta file not found: ${params.fasta}" }
.into { fasta_star_index; fasta_bowtie_index}
}
else {
exit 1, "No reference genome specified!"
}
if( params.fasta ){
Channel
.fromPath(params.fasta, checkIfExists: true)
.ifEmpty { exit 1, "fasta file not found: ${params.fasta}" }
.set{fasta_rseqc}
} else {
exit 1, "No fasta file specified!"
}
if( params.gtf ){
Channel
.fromPath(params.gtf, checkIfExists: true)
.ifEmpty { exit 1, "GTF annotation file not found: ${params.gtf}" }
.into { gtf_make_STAR_index; gtf_star; gtf_rseqc}
} else {
exit 1, "No GTF annotation specified! Needed for STAR and clustering QC."
}
if( params.artifacts_5end ){
ch_5end_artifacts = Channel
.fromPath(params.artifacts_5end)
}
else {
ch_5end_artifacts = Channel
.fromPath("$projectDir/assets/artifacts_5end.fasta")
}
if( params.artifacts_3end ){
ch_3end_artifacts = Channel
.fromPath(params.artifacts_3end)
}
else {
ch_3end_artifacts = Channel
.fromPath("$projectDir/assets/artifacts_3end.fasta")
}
// Has the run name been specified by the user?
// this has the bonus effect of catching both -name and --name
custom_runName = params.name
if (!(workflow.runName ==~ /[a-z]+_[a-z]+/)) {
custom_runName = workflow.runName
}
// Check AWS batch settings
if (workflow.profile.contains('awsbatch')) {
// AWSBatch sanity checking
if (!params.awsqueue || !params.awsregion) exit 1, "Specify correct --awsqueue and --awsregion parameters on AWSBatch!"
// Check outdir paths to be S3 buckets if running on AWSBatch
// related: https://github.com/nextflow-io/nextflow/issues/813
if (!params.outdir.startsWith('s3:')) exit 1, "Outdir not on S3 - specify S3 Bucket to run on AWSBatch!"
// Prevent trace files to be stored on S3 since S3 does not support rolling files.
if (params.tracedir.startsWith('s3:')) exit 1, "Specify a local tracedir or run without trace! S3 cannot be used for tracefiles."
}
// Stage config files
ch_multiqc_config = file("$projectDir/assets/multiqc_config.yaml", checkIfExists: true)
ch_multiqc_custom_config = params.multiqc_config ? Channel.fromPath(params.multiqc_config, checkIfExists: true) : Channel.empty()
ch_output_docs = file("$projectDir/docs/output.md", checkIfExists: true)
ch_output_docs_images = file("$projectDir/docs/images/", checkIfExists: true)
/*
* Create a channel for input read files
*/
if (params.input_paths) {
Channel
.from(params.input_paths)
.map { row -> [ row[0].replaceAll("\\s","_"), file(row[1])] }
.ifEmpty { exit 1, "params.input was empty - no input files supplied" }
.into { ch_read_files_fastqc; read_files_trimming }
} else {
Channel
.fromPath( params.input )
.ifEmpty { exit 1, "Cannot find any reads matching: ${params.reads}\nNB: Path needs to be enclosed in quotes!\nNB: Path requires at least one * wildcard!\n" }
.into { ch_read_files_fastqc; read_files_trimming }
}
// Header log info
log.info nfcoreHeader()
def summary = [:]
if (workflow.revision){
summary['Pipeline Release'] = workflow.revision
}
summary['Run Name'] = custom_runName ?: workflow.runName
summary['Input'] = params.input
if (params.skip_initial_fastqc) {
summary['Skip Initial FastQC'] = 'Yes'
}
if (params.artifacts_5end){
summary["5' artifacts"] = params.artifacts_5end
}
if (params.artifacts_3end){
summary["3' artifacts"] = params.artifacts_3end
}
if (params.skip_trimming) {
summary['Skip Trimming'] = 'Yes'
} else {
summary['trim_ecop'] = params.trim_ecop
summary['trim_linker'] = params.trim_linker
summary['trim_5g'] = params.trim_5g
summary['trim_artifacts'] = params.trim_artifacts
summary['eco_site'] = params.eco_site
summary['linker_seq'] = params.linker_seq
}
summary['Remove rRNA'] = params.remove_ribo_rna
if (params.skip_trimming_fastqc){
summary['Skip Trimming FastQC'] = 'Yes'
}
if (params.skip_alignment){
summary['Skip Alignment'] = 'Yes'
}
else {
if (params.aligner == 'star') {
summary['Aligner'] = 'STAR'
if (params.star_index){
summary['STAR Index'] = params.star_index
} else if (params.fasta){
summary['Fasta Ref'] = params.fasta
}
} else if (params.aligner == 'bowtie1') {
summary['Aligner'] = 'bowtie1'
if (params.bowtie_index){
summary['bowtie Index'] = params.bowtie_index
} else if (params.fasta){
summary['Fasta Ref'] = params.fasta
}
}
}
if(params.skip_ctss_generation){
summary['Skip CTSS generation'] = 'Yes'
} else{
summary['Min. cluster'] = params.min_cluster
summary['Cluster Threshold'] = params.tpm_cluster_threshold
}
if(params.skip_ctss_qc) {
summary['Skip CTSS QC'] = 'Yes'
}
if(params.bigwig){
summary['bigwig output'] = 'Yes'
}
summary['Save Reference'] = params.save_reference
summary['Max Resources'] = "$params.max_memory memory, $params.max_cpus cpus, $params.max_time time per job"
if (workflow.containerEngine){
summary['Container'] = "$workflow.containerEngine - $workflow.container"
}
summary['Output dir'] = params.outdir
summary['Launch dir'] = workflow.launchDir
summary['Working dir'] = workflow.workDir
summary['Script dir'] = workflow.projectDir
summary['User'] = workflow.userName
if (workflow.profile.contains('awsbatch')) {
summary['AWS Region'] = params.awsregion
summary['AWS Queue'] = params.awsqueue
summary['AWS CLI'] = params.awscli
}
summary['Config Profile'] = workflow.profile
if (params.config_profile_description){
summary['Config Profile Description'] = params.config_profile_description
}
if (params.config_profile_contact){
summary['Config Profile Contact'] = params.config_profile_contact
}
if (params.config_profile_url){
summary['Config Profile URL'] = params.config_profile_url
}
summary['Config Files'] = workflow.configFiles.join(', ')
if (params.email || params.email_on_fail) {
summary['E-mail Address'] = params.email
summary['E-mail on failure'] = params.email_on_fail
summary['MultiQC maxsize'] = params.max_multiqc_email_size
}
log.info summary.collect { k,v -> "${k.padRight(18)}: $v" }.join("\n")
log.info "-\033[2m--------------------------------------------------\033[0m-"
// Check the hostnames against configured profiles
checkHostname()
Channel.from(summary.collect{ [it.key, it.value] })
.map { k,v -> "<dt>$k</dt><dd><samp>${v ?: '<span style=\"color:#999999;\">N/A</a>'}</samp></dd>" }
.reduce { a, b -> return [a, b].join("\n ") }
.map { x -> """
id: 'nf-core-cageseq-summary'
description: " - this information is collected when the pipeline is started."
section_name: 'nf-core/cageseq Workflow Summary'
section_href: 'https://github.com/nf-core/cageseq'
plot_type: 'html'
data: |
<dl class=\"dl-horizontal\">
$x
</dl>
""".stripIndent() }
.set { ch_workflow_summary }
process get_software_versions {
publishDir "${params.outdir}/pipeline_info", mode: params.publish_dir_mode,
saveAs: { filename ->
if (filename.indexOf(".csv") > 0) filename
else null
}
output:
file 'software_versions_mqc.yaml' into ch_software_versions_yaml
file "software_versions.csv"
script:
"""
echo $workflow.manifest.version > v_pipeline.txt
echo $workflow.nextflow.version > v_nextflow.txt
fastqc --version > v_fastqc.txt
multiqc --version > v_multiqc.txt
STAR --version > v_star.txt
bowtie --version > v_bowtie.txt
cutadapt --version > v_cutadapt.txt
samtools --version > v_samtools.txt
bedtools --version > v_bedtools.txt
read_distribution.py --version > v_rseqc.txt
sortmerna --version > v_sortmerna.txt
scrape_software_versions.py &> software_versions_mqc.yaml
"""
}
if(!params.skip_ctss_qc){
process convert_gtf {
tag "$gtf"
input:
file gtf from gtf_rseqc
output:
file "${gtf.baseName}.bed" into bed_rseqc
script:
"""
gtf2bed.pl $gtf > ${gtf.baseName}.bed
"""
}
}
if(!params.skip_ctss_generation){
process get_chrom_sizes{
input:
file fasta from fasta_rseqc.collect()
output:
file "*.txt" into (chrom_sizes_ctss,chrom_sizes_bw)
shell:
'''
cat !{fasta} | awk '$0 ~ ">" {if (NR > 1) {print c;} c=0;printf substr($0,2,100) "\t"; } $0 !~ ">" {c+=length($0);} END { print c; }' > chrom_sizes.txt
'''
}
}
/*
* STEP 1 - FastQC
*/
if(!params.skip_initial_fastqc){
process fastqc {
tag "$name"
label 'process_low'
publishDir "${params.outdir}/fastqc", mode: params.publish_dir_mode,
saveAs: { filename ->
filename.indexOf(".zip") > 0 ? "zips/$filename" : "$filename"
}
input:
set val(name), file(reads) from ch_read_files_fastqc
output:
file "*_fastqc.{zip,html}" into fastqc_results
script:
"""
fastqc --quiet --threads $task.cpus $reads
"""
}
} else {
fastqc_results = Channel.empty()
}
/*
* STEP 2 - Build STAR/bowtie1 index
*/
if(params.aligner == 'star' && !params.star_index && params.fasta && !params.skip_alignment){
process make_STAR_index {
label 'process_high'
tag "${fasta.baseName}"
publishDir path: { params.save_reference ? "${params.outdir}/reference_genome" : params.outdir },
saveAs: { params.save_reference ? it : null }, mode: params.publish_dir_mode
input:
file fasta from fasta_star_index
file gtf from gtf_make_STAR_index.collect()
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 \\
$avail_mem
"""
}
}
if(params.aligner == 'bowtie1' && !params.bowtie_index && params.fasta && !params.skip_alignment){
process make_bowtie_index {
label 'process_high'
tag "${fasta.baseName}"
publishDir path: { params.save_reference ? "${params.outdir}/reference_genome" : params.outdir },
saveAs: { params.save_reference ? it : null }, mode: params.publish_dir_mode
input:
file fasta from fasta_bowtie_index
output:
file "${fasta.baseName}.index*" into bowtie_index
script:
"""
bowtie-build --threads $task.cpus ${fasta} ${fasta.baseName}.index
"""
}
}
/*
* STEP 3 - Cut enzyme binding site at 5' and linker at 3'
*/
if(!params.skip_trimming && (params.trim_ecop || params.trim_linker)){
process trim_adapters {
tag "$name"
publishDir "${params.outdir}/trimmed/adapter_trimmed", mode: params.publish_dir_mode,
saveAs: {filename ->
if (filename.indexOf(".fastq.gz") == -1) "logs/$filename"
else if (params.save_trimmed) "$filename"
else null
}
input:
set val(name), file(reads) from read_files_trimming
output:
set val(name), file("*.fastq.gz") into trimmed_reads_trim_5g
file "*.output.txt" into cutadapt_results
script:
// Cut Both EcoP and Linker
if (params.trim_ecop && params.trim_linker){
"""
cutadapt -a ^${params.eco_site}...${params.linker_seq} \\
--match-read-wildcards \\
--minimum-length 15 --maximum-length 40 \\
--discard-untrimmed \\
--quality-cutoff 30 \\
--cores=$task.cpus \\
-o "${name}".adapter_trimmed.fastq.gz \\
$reads \\
> "${name}"_adapter_trimming.output.txt
"""
}
// Cut only EcoP site
else if (params.trim_ecop && !params.trim_linker){
"""
mkdir trimmed
cutadapt -g ^${params.eco_site} \\
-e 0 \\
--match-read-wildcards \\
--minimum-length 20 --maximum-length 40 \\
--discard-untrimmed \\
--quality-cutoff 30 \\
--cores=$task.cpus \\
-o "${name}".adapter_trimmed.fastq.gz \\
$reads \\
> "${name}"_adapter_trimming.output.txt
"""
}
// Cut only Linker
else if (!params.trim_ecop && params.trim_linker){
"""
mkdir trimmed
cutadapt -a ${params.linker_seq}\$ \\
-e 0 \\
--match-read-wildcards \\
--minimum-length 20 --maximum-length 40 \\
--discard-untrimmed \\
--quality-cutoff 30 \\
--cores=$task.cpus \\
-o "${name}".adapter_trimmed.fastq.gz \\
$reads \\
> "${name}"_adapter_trimming.output.txt
"""
}
}
} else {
read_files_trimming.set{ trimmed_reads_trim_5g }
cutadapt_results = Channel.empty()
}
/**
* STEP 4 - Remove added G from 5-end
*/
if (params.trim_5g && !params.skip_trimming){
process trim_5g {
tag "$name"
publishDir "${params.outdir}/trimmed/g_trimmed", mode: params.publish_dir_mode,
saveAs: {filename ->
if (filename.indexOf(".fastq.gz") == -1) "logs/$filename"
else if (params.save_trimmed) "$filename"
else null
}
input:
set val(name), file(reads) from trimmed_reads_trim_5g
output:
set val(name), file("*.fastq.gz") into processed_reads
script:
"""
cutadapt -g ^G \\
-e 0 --match-read-wildcards \\
--cores=$task.cpus \\
-o "${name}".g_trimmed.fastq.gz \\
$reads \\
> "${name}".g_trimming.output.txt
"""
}
}
else {
trimmed_reads_trim_5g.set{processed_reads}
}
/**
* STEP 5 - Remove artifacts
*/
if (params.trim_artifacts && !params.skip_trimming){
process trim_artifacts {
tag "$name"
publishDir "${params.outdir}/trimmed/artifacts_trimmed", mode: params.publish_dir_mode,
saveAs: {filename ->
if (filename.indexOf(".fastq.gz") == -1) "logs/$filename"
else if (params.save_trimmed) "$filename"
else null
}
input:
set val(name), file(reads) from processed_reads
file artifacts_5end from ch_5end_artifacts.collect()
file artifacts_3end from ch_3end_artifacts.collect()
output:
set val(name), file("*.fastq.gz") into further_processed_reads_sortmerna
file "*.output.txt" into artifact_cutting_results
script:
"""
cutadapt -a file:$artifacts_3end \\
-g file:$artifacts_5end -e 0.1 --discard-trimmed \\
--match-read-wildcards -m 15 -O 19 \\
--cores=$task.cpus \\
-o "${name}".artifacts_trimmed.fastq.gz \\
$reads \\
> ${reads.baseName}.artifacts_trimming.output.txt
"""
}
} else{
processed_reads.set{further_processed_reads_sortmerna}
artifact_cutting_results = Channel.empty()
}
/*
* STEP 6 - SortMeRNA - remove rRNA sequences on request
*/
if (params.remove_ribo_rna) {
process sortmerna {
label 'process_high'
tag "$name"
publishDir "${params.outdir}/SortMeRNA", mode: params.publish_dir_mode,
saveAs: {filename ->
if (filename.indexOf("_rRNA_report.txt") > 0) "logs/$filename"
else if (params.save_non_ribo_reads) "reads/$filename"
else null
}
input:
set val(name), file(reads) from further_processed_reads_sortmerna
file(fasta) from fasta_sortmerna.collect()
output:
set val(name), file("*.fq.gz") into further_processed_reads_alignment, further_processed_reads_fastqc;
file "*_rRNA_report.txt" into sortmerna_logs
script:
//concatenate reference files: ${db_fasta},${db_name}:${db_fasta},${db_name}:...
def Refs = ""
for (i=0; i<fasta.size(); i++) { Refs+= " --ref ${fasta[i]}" }
"""
sortmerna ${Refs} \\
--reads ${reads} \\
--num_alignments 1 \\
--threads $task.cpus \\
--workdir . \\
--fastx \\
--aligned rRNA-reads \\
--other non-rRNA-reads \\
-v
gzip --force < non-rRNA-reads.fastq > ${name}.fq.gz
mv rRNA-reads.log ${name}_rRNA_report.txt
"""
}
} else {
further_processed_reads_sortmerna.into { further_processed_reads_alignment; further_processed_reads_fastqc }
sortmerna_logs = Channel.empty()
}
// Post trimming QC, only needed if some trimming has been done
if(!params.skip_trimming_fastqc || (!params.skip_trimming || params.remove_ribo_rna)){
process trimmed_fastqc {
tag "$name"
publishDir "${params.outdir}/trimmed/fastqc", mode: params.publish_dir_mode,
saveAs: {filename -> filename.indexOf(".zip") > 0 ? "zips/$filename" : "$filename"}
input:
set val(name), file(reads) from further_processed_reads_fastqc
output:
path "*_fastqc.{zip,html}" into trimmed_fastqc_results
when:
(params.trim_ecop || params.trim_linker || params.trim_5g || params.trim_artifacts) && !params.skip_trimming
script:
"""
fastqc -q $reads
"""
}
} else {
trimmed_fastqc_results = Channel.empty()
}
/**
* STEP 7 - STAR/bowtie alignment
*/
if(!params.skip_alignment){
if (params.aligner == 'star') {
process star {
label 'process_high'
tag "$name"
publishDir "${params.outdir}/STAR", mode: params.publish_dir_mode,
saveAs: {filename ->
if (filename.indexOf(".bam") == -1) "logs/$filename"
else filename }
input:
set val(name), file(reads) from further_processed_reads_alignment
file index from star_index.collect()
file gtf from gtf_star.collect()
output:
set val(name), file("*.bam") into star_aligned
file "*.out" into star_alignment_logs
file "*SJ.out.tab"
script:
"""
STAR --genomeDir $index \\
--sjdbGTFfile $gtf \\
--readFilesIn $reads \\
--runThreadN $task.cpus \\
--outSAMtype BAM SortedByCoordinate \\
--outFilterScoreMinOverLread 0 --outFilterMatchNminOverLread 0 \\
--seedSearchStartLmax 20 \\
--outFilterMismatchNmax 1 \\
--readFilesCommand zcat \\
--runDirPerm All_RWX \\
--outFileNamePrefix $name \\
--outFilterMultimapNmax 1
"""
}
star_aligned.into { bam_stats; bam_aligned }
} else{
star_alignment_logs = Channel.empty()
}
if (params.aligner == 'bowtie1'){
process bowtie {
label 'process_high'
tag "$name"
publishDir "${params.outdir}/bowtie", mode: params.publish_dir_mode,
saveAs: {filename ->
if (filename.indexOf(".bam") == -1) "logs/$filename"
else filename }
input:
set val(name), file(reads) from further_processed_reads_alignment
file index_array from bowtie_index.collect()
output:
set val(name), file("*.bam") into bam_stats, bam_aligned
file "*.out" into bowtie_alignment_logs
script:
index = index_array[0].baseName - ~/.\d$/
"""
bowtie --sam \\
-m 1 \\
--best \\
--strata \\
-k 1 \\
--tryhard \\
--threads $task.cpus \\
--phred33-quals \\
--chunkmbs 64 \\
--seedmms 2 \\
--seedlen 20 \\
--maqerr 70 \\
${index} \\
-q ${reads} \\
--un ${reads.baseName}.unAl > ${name}.sam 2> ${name}.out
samtools sort -@ $task.cpus -o ${name}.bam ${name}.sam
"""
}
}else{
bowtie_alignment_logs= Channel.empty()
}
} else {
further_processed_reads_sortmerna.into{bam_stats; bam_aligned}
star_alignment_logs = Channel.empty()
bowtie_alignment_logs = Channel.empty()
}
if(!params.skip_samtools_stats && !params.skip_samtools_stats){
process samtools_stats {
tag "$name"
label 'process_low'
input:
set val(name), file(bam_count) from bam_stats
output:
file "*.{flagstat,idxstats,stats}" into bam_flagstat_mqc
script:
"""
samtools idxstats $bam_count > ${bam_count}.idxstats
"""
}
} else {
bam_flagstat_mqc = Channel.empty()
}
if(!params.skip_ctss_generation){
/**
* STEP 8 - group CAGE tags
*/
process get_ctss {
tag "$name"
publishDir "${params.outdir}/ctss", mode: params.publish_dir_mode,
saveAs: {filename ->
if (filename.indexOf(".bed") != -1) "bed/$filename"
else if (filename.indexOf(".bw") != -1) "bigwig/$filename"
else filename }
input:
set val(name), file(bam_count) from bam_aligned
output:
set val(name), file("*.ctss.bed") into (ctss_samples,ctss_bw)
file("*.ctss.bed") into (ctss_counts, ctss_counts_qc)
shell:
'''
make_ctss.sh -q 20 -i !{bam_count.baseName} -n !{name}
'''
}
if(params.bigwig){
process make_bigwig{
tag "$name"
publishDir "${params.outdir}/ctss/bigwig", mode: params.publish_dir_mode
input:
set val(name), file(ctss_file) from ctss_bw
file chrom_sizes from chrom_sizes_bw
output:
file("*.ctss.bw")
script:
"""
bedtools genomecov -bg -i ${name}.ctss.bed -g ${chrom_sizes} > ${name}.bedgraph
sort -k1,1 -k2,2n ${name}.bedgraph > ${name}_sorted.bedgraph
bedGraphToBigWig ${name}_sorted.bedgraph ${chrom_sizes} ${name}.ctss.bw
"""
}
}
/**
* STEP 9 - Cluster CTSS files
*/
ctss_counts = ctss_counts.collect().dump(tag:"ctss_counts")
process cluster_ctss {
label "process_high"
publishDir "${params.outdir}/ctss/clusters", mode: params.publish_dir_mode
input:
file ctss from ctss_counts.collect()
output:
file "*.bed" into ctss_clusters
shell:
'''
process_ctss.sh -t !{params.tpm_cluster_threshold} !{ctss}
paraclu !{params.min_cluster} "ctss_all_pos_4Ps" > "ctss_all_pos_clustered"
paraclu !{params.min_cluster} "ctss_all_neg_4Ps" > "ctss_all_neg_clustered"
paraclu-cut "ctss_all_pos_clustered" > "ctss_all_pos_clustered_simplified"
paraclu-cut "ctss_all_neg_clustered" > "ctss_all_neg_clustered_simplified"
cat "ctss_all_pos_clustered_simplified" "ctss_all_neg_clustered_simplified" > "ctss_all_clustered_simplified"
awk -F '\t' '{print $1"\t"$3"\t"$4"\t"$1":"$3".."$4","$2"\t"$6"\t"$2}' "ctss_all_clustered_simplified" > "ctss_all_clustered_simplified.bed"
'''
}
/*
* STEP 10 - Generate count files
*/
process generate_counts {
tag "$name"
input:
set val(name), file(ctss) from ctss_samples
file clusters from ctss_clusters.collect()
output:
file "*.txt" into count_files
file "*.bed" into count_qc
shell:
'''
intersectBed -a !{clusters} -b !{ctss} -loj -s > !{ctss}_counts_tmp
echo !{name} > !{ctss}_counts.txt
bedtools groupby -i !{ctss}_counts_tmp -g 1,2,3,4,6 -c 11 -o sum > !{ctss}_counts.bed
awk -v OFS='\t' '{if($6=="-1") $6=0; print $6 }' !{ctss}_counts.bed >> !{ctss}_counts.txt
'''
}
/*
* STEP 11 - Generate count matrix
*/
process generate_count_matrix {
publishDir "${params.outdir}/ctss/", mode: params.publish_dir_mode
input:
file counts from count_files.collect()
file clusters from ctss_clusters.collect()
output:
file "*.tsv" into count_matrix
shell:
'''
echo 'coordinates' > coordinates
awk '{ print $4}' !{clusters} >> coordinates
paste -d "\t" coordinates !{counts} >> count_table.tsv
'''
}
/**
* STEP 12 - QC for clustered ctss
*/
if(!params.skip_ctss_qc){
process ctss_qc {
tag "$clusters"
publishDir "${params.outdir}/rseqc" , mode: params.publish_dir_mode,
saveAs: {filename ->
if (filename.indexOf("read_distribution.txt") > 0) "read_distribution/$filename"
else filename
}
input:
file clusters from ctss_counts_qc
file gtf from bed_rseqc.collect()
file chrom_sizes from chrom_sizes_ctss
output:
file "*.txt" into rseqc_results
script:
"""
bedtools bedtobam -i $clusters -g $chrom_sizes > ${clusters.baseName}.bam
read_distribution.py -i ${clusters.baseName}.bam -r $gtf > ${clusters.baseName}.read_distribution.txt
"""
}
} else {
rseqc_results = Channel.empty()
}
} else {
count_qc = Channel.empty()
rseqc_results = Channel.empty()
}
/*
* STEP 13 - MultiQC
*/
process multiqc {
publishDir "${params.outdir}/MultiQC", mode: params.publish_dir_mode
input:
file multiqc_config from ch_multiqc_config
file mqc_custom_config from ch_multiqc_custom_config.collect().ifEmpty([])
file ('software_versions/*') from ch_software_versions_yaml.collect()
file ('fastqc/*') from fastqc_results.collect().ifEmpty([])
file ('trimmed/*') from cutadapt_results.collect().ifEmpty([])
file ('artifacts_trimmed/*') from artifact_cutting_results.collect().ifEmpty([])
file ('trimmed/fastqc/*') from trimmed_fastqc_results.collect().ifEmpty([])
file ('sortmerna/*') from sortmerna_logs.collect().ifEmpty([])
file ('alignment/*') from star_alignment_logs.collect().ifEmpty([])
file ('alignment/*') from bowtie_alignment_logs.collect().ifEmpty([])
file ('alignment/samtools_stats/*') from bam_flagstat_mqc.collect().ifEmpty([])
file ('rseqc/*') from rseqc_results.collect().ifEmpty([])
file workflow_summary from ch_workflow_summary.collectFile(name: "workflow_summary_mqc.yaml")
output:
file "*multiqc_report.html" into ch_multiqc_report
file "*_data"
file "multiqc_plots"
script:
rtitle = custom_runName ? "--title \"$custom_runName\"" : ''
rfilename = custom_runName ? "--filename " + custom_runName.replaceAll('\\W','_').replaceAll('_+','_') + "_multiqc_report" : ''
custom_config_file = params.multiqc_config ? "--config $mqc_custom_config" : ''
"""
multiqc . -f $rtitle $rfilename $custom_config_file
"""
}
/*
* STEP 14 - Output Description HTML
*/
process output_documentation {
publishDir "${params.outdir}/pipeline_info", mode: params.publish_dir_mode
input:
file output_docs from ch_output_docs
file images from ch_output_docs_images
output:
file "results_description.html"
script: