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main.nf
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#!/usr/bin/env nextflow
/*
* LncPipe was implemented by Dr. Qi Zhao from Sun Yat-sen University Cancer Center, China.
*
*
* LncPipe is a free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* See the GNU General Public License for more details.
*
*
*/
/*
* LncPipe: A nextflow-based lncRNA identification and analysis pipeline from RNA sequencing data
*
* Authors:
* Qi Zhao <[email protected]>: design and implement the pipeline.
* Yu Sun <[email protected]>: design and implement the analysis report sections.
* Zhixiang Zuo <[email protected]>: design the project and perform the testing.
*/
//pre-defined functions for render command
//=======================================================================================
ANSI_RESET = "\u001B[0m";
ANSI_BLACK = "\u001B[30m";
ANSI_RED = "\u001B[31m";
ANSI_GREEN = "\u001B[32m";
ANSI_YELLOW = "\u001B[33m";
ANSI_BLUE = "\u001B[34m";
ANSI_PURPLE = "\u001B[35m";
ANSI_CYAN = "\u001B[36m";
ANSI_WHITE = "\u001B[37m";
def print_red = { str -> ANSI_RED + str + ANSI_RESET }
def print_black = { str -> ANSI_BLACK + str + ANSI_RESET }
def print_green = { str -> ANSI_GREEN + str + ANSI_RESET }
def print_yellow = { str -> ANSI_YELLOW + str + ANSI_RESET }
def print_blue = { str -> ANSI_BLUE + str + ANSI_RESET }
def print_cyan = { str -> ANSI_CYAN + str + ANSI_RESET }
def print_purple = { str -> ANSI_PURPLE + str + ANSI_RESET }
def print_white = { str -> ANSI_WHITE + str + ANSI_RESET }
//Help information
// Nextflow version
version="v0.2.44"
//=======================================================================================
// Nextflow Version check
if( !nextflow.version.matches('0.30+') ) {
println print_yellow("This workflow requires Nextflow version 0.26 or greater -- You are running version ")+ print_red(nextflow.version)
}
//help information
params.help = null
if (params.help) {
log.info ''
log.info print_purple('------------------------------------------------------------------------')
log.info "LncPipe: a Nextflow-based Long non-coding RNA analysis Pipeline v$version"
log.info "LncPipe integrates several NGS processing tools to identify novel long non-coding RNAs from"
log.info "un-processed RNA sequencing data. To run this pipeline, users either need to install required tools manually"
log.info "or use the docker image for LncPipe that comes with all tools pre-installed. (note: docker needs to be installed on your system). More information on usage can be found at https://github.com/likelet/LncPipe ."
log.info "Bugs or new feature requests can be reported by opening issues in our github repository."
log.info print_purple('------------------------------------------------------------------------')
log.info ''
log.info print_yellow('Usage: ')
log.info print_yellow(' The typical command for running the pipeline is as follows (we do not recommend users passing configuration parameters through command line, please modify the config.file instead):\n') +
print_purple(' Nextflow run LncRNAanalysisPipe.nf \n') +
print_yellow(' General arguments: Input and output setting\n') +
print_cyan(' --inputdir <path> ') + print_green('Path to input data(optional), current path default\n') +
print_cyan(' --reads <*_fq.gz> ') + print_green('Filename pattern for pairing raw reads, e.g: *_{1,2}.fastq.gz for paired reads\n') +
print_cyan(' --out_folder <path> ') + print_green('The output directory where the results will be saved(optional), current path is default\n') +
print_cyan(' --aligner <hisat> ') + print_green('Aligner for reads mapping (optional),"hisat"(defalt)/"star"/"tophat"\n') +
print_cyan(' --qctools <fastp> ') + print_green('Tools for assess reads quality, fastp(default)/afterqc/fastqc/none(skip QC step)\n') +
print_cyan(' --detools <edger> ') + print_green('Tools for differential analysis, edger(default)/deseq/noiseq\n') +
print_cyan(' --quant <kallisto> ') + print_green('Tools for estimating abundance of transcript, kallisto(default)/htseq\n') +
'\n' +
print_yellow(' Options: General options for run this pipeline\n') +
print_cyan(' --merged_gtf <gtffile> ') + print_green('Start analysis with assemblies already produced and skip fastqc/alignment step, DEFAOUL NULL\n') +
print_cyan(' --design <file> ') + print_green('A flat file stored the experimental design information ( required when perform differential expression analysis)\n') +
print_cyan(' --singleEnd ') + print_green('Reads type, True for single ended \n') +
print_cyan(' --unstrand ') + print_green('RNA library construction strategy, specified for \'unstranded\' library \n') +
'\n' +
print_yellow(' References: If not specified in the configuration file or you wish to overwrite any of the references.\n') +
print_cyan(' --fasta ') + print_green('Path to Fasta reference(required)\n') +
print_cyan(' --gencode_annotation_gtf ') + print_green('An annotation file from GENCODE database in GTF format (required)\n') +
print_cyan(' --lncipedia_gtf ') + print_green('An annotation file from LNCipedia database in GTF format (required)\n') +
'\n' +
print_yellow(' LncPipeReporter Options: LncPipeReporter setting \n') +
print_cyan(' --lncRep_Output ') + print_green('Specify report file name, \"report.html\" default.\n') +
print_cyan(' --lncRep_theme ') + print_green('Plot theme setting in interactive plot, \"npg\" default.\n') +
print_cyan(' --lncRep_min_expressed_sample ') + print_green('Minimum expressed gene allowed in each sample, 50 default.\n') +
'\n' +
print_yellow(' Other options: Specify the email and \n') +
print_cyan(' --sam_processor ') + print_green('program to process samfile generated by hisat2 if aligner is hisat2. Default \"sambamba\". \n') +
print_cyan(' --mail ') + print_green('email info for reporting status of your LncPipe execution \n') +
log.info '------------------------------------------------------------------------'
log.info print_yellow('Contact information: [email protected]')
log.info print_yellow('Copyright (c) 2013-2017, Sun Yat-sen University Cancer Center.')
log.info '------------------------------------------------------------------------'
exit 0
}
//check parameters
/*
allowed_params = ["inputdir","reads","out_folder","aligner","qctools","detools","quant",
"merged_gtf","design","singleEnd","unstrand",
"fasta","gencode_annotation_gtf","lncipedia_gtf",
"lncRep_Output", "lncRep_theme","lncRep_min_expressed_sample",
"sam_processor","mail"]
params.each { entry ->
if (! allowed_params.contains(entry.key)) {
println("The parameter <${entry}.key> is not known");
System.exit(2);
}
}
*/
//default values
params.inputdir = ''
params.outdir = './'
params.multiqc_config = "$baseDir/assets/multiqc_config.yaml" // for generate qc and alignment result
params.merged_gtf = null// dose merged_gtf provided
singleEnd = params.singleEnd ? true : false
skip_combine = params.skip_combine ? true : false
unstrand = params.unstrand ? true : false
params.mail=false
//Checking parameters
log.info print_purple("You are running LncPipe with the following parameters:")
log.info print_purple("Checking parameters ...")
log.info print_yellow("=====================================")
log.info print_yellow("Species: ") + print_green(params.species)
log.info print_yellow("Fastq file extension: ") + print_green(params.reads)
log.info print_yellow("Design file: ") + print_green(params.design)
log.info print_yellow("Single end : ") + print_green(params.singleEnd)
log.info print_yellow("skip annotation process: ") + print_green(params.skip_combine)
log.info print_yellow("Input folder: ") + print_green(params.inputdir)
log.info print_yellow("Output folder: ") + print_green(params.outdir)
log.info print_yellow("Genome sequence location: ") + print_green(params.fasta)
log.info print_yellow("STAR index path: ") + print_green(params.star_index)
log.info print_yellow("HISAT2 index path: ") + print_green(params.hisat2_index)
log.info print_yellow("bowtie/tophat index path: ") + print_green(params.bowtie2_index)
log.info print_yellow("GENCODE annotation location: ") + print_green(params.gencode_annotation_gtf)
log.info print_yellow("lncipedia annotation location: ") + print_green(params.lncipedia_gtf)
log.info print_yellow("=====================================")
log.info "\n"
// run information of system file
//automatic set optimize resource for analysis based on current system resources
// read file
fasta = file(params.fasta)
if (!fasta.exists()) exit 1, "Reference genome not found: ${params.fasta}"
if(params.aligner=='star'){
star_index = file(params.star_index)
if (!star_index.exists()) exit 1, "STAR index not found: ${params.star_index}"
}else if(params.aligner =='hisat'){
hisat2_index = Channel.fromPath("${params.hisat2_index}*")
.ifEmpty { exit 1, "HISAT2 index not found: ${params.hisat2_index}" }
}else if(params.aligner =='tophat'){
bowtie2_index = Channel.fromPath("${params.bowtie2_index}*")
.ifEmpty { exit 1, "bowtie2 index for tophat not found: ${params.bowtie2_index}" }
}
inputdir = params.inputdir
multiqc_config = file(params.multiqc_config)
/*
*Step 1: Prepare Annotations
*/
println print_purple("Combining known annotations from GTFs")
if (params.species=="human") {
gencode_annotation_gtf = file(params.gencode_annotation_gtf)
if (!gencode_annotation_gtf.exists()) exit 1, "GENCODE annotation file not found: ${params.gencode_annotation_gtf}"
lncipedia_gtf = file(params.lncipedia_gtf)
if (!lncipedia_gtf.exists()) exit 1, "lncipedia annotation file not found: ${params.lncipedia_gtf}"
//Prepare annotations
annotation_channel = Channel.from(gencode_annotation_gtf, lncipedia_gtf)
annotation_channel.collectFile { file -> ['lncRNA.gtflist', file.name + '\n'] }
.set { LncRNA_gtflist }
process combine_public_annotation {
storeDir { params.outdir + "/Combined_annotations" }
input:
file lncRNA_gtflistfile from LncRNA_gtflist
file gencode_annotation_gtf
file lncipedia_gtf
output:
file "gencode_protein_coding.gtf" into proteinCodingGTF, proteinCodingGTF_forClass
file "known.lncRNA.gtf" into KnownLncRNAgtf
file "*_mod.gtf" into mod_file_for_rename
shell:
if(params.aligner=='hisat'){//fix the gtf format required by hisat
'''
set -o pipefail
touch filenames.txt
perl -lpe 's/ ([^"]\\S+) ;/ "$1" ;/g' !{gencode_annotation_gtf} > gencode_annotation_gtf_mod.gtf
perl -lpe 's/ ([^"]\\S+) ;/ "$1" ;/g' !{lncipedia_gtf} > lncipedia_mod.gtf
echo gencode_annotation_gtf_mod.gtf >>filenames.txt
echo lncipedia_mod.gtf >>filenames.txt
stringtie --merge -o merged_lncRNA.gtf filenames.txt
cat gencode_annotation_gtf_mod.gtf |grep "protein_coding" > gencode_protein_coding.gtf
gffcompare -r gencode_protein_coding.gtf -p !{task.cpus} merged_lncRNA.gtf
awk '$3 =="u"||$3=="x"{print $5}' gffcmp.merged_lncRNA.gtf.tmap |sort|uniq|perl !{baseDir}/bin/extract_gtf_by_name.pl merged_lncRNA.gtf - > merged.filter.gtf
mv merged.filter.gtf known.lncRNA.gtf
'''
}else {
'''
set -o pipefail
cuffmerge -o merged_lncRNA !{lncRNA_gtflistfile}
cat !{gencode_annotation_gtf} |grep "protein_coding" > gencode_protein_coding.gtf
cuffcompare -o merged_lncRNA -r gencode_protein_coding.gtf -p !{task.cpus} merged_lncRNA/merged.gtf
awk '$3 =="u"||$3=="x"{print $5}' merged_lncRNA/merged_lncRNA.merged.gtf.tmap |sort|uniq|perl !{baseDir}/bin/extract_gtf_by_name.pl merged_lncRNA/merged.gtf - > merged.filter.gtf
mv merged.filter.gtf known.lncRNA.gtf
'''
}
}
}
else {// for mouse or other species, user should provide known_protein_coding and known_lncRNA GTF file for analysis
KnownLncRNAgtf=file(params.known_lncRNA_gtf)
if (!KnownLncRNAgtf.exists()) exit 1, print_red("In non-human mode, known lncRNA GTF annotation file not found: ${params.known_lncRNA_gtf}")
known_coding_gtf=file(params.known_coding_gtf)
if (!known_coding_gtf.exists()) exit 1, print_red("In non-human mode, known protein coding GTF annotation file not found: ${params.known_coding_gtf}")
gencode_annotation_gtf = file(params.gencode_annotation_gtf)
if (!gencode_annotation_gtf.exists()) exit 1, print_red("GENCODE annotation file not found: ${params.gencode_annotation_gtf}")
gencode_annotation_gtf.into{proteinCodingGTF; proteinCodingGTF_forClass}
knownLncRNAgtf.set{knownLncRNAgtf}
}
// whether the merged gtf have already produced.
if (!params.merged_gtf) {
/*
* Step 2: Build read aligner (STAR/tophat/HISAT2) index, if not provided
*/
//star_index if not exist
/*if (params.aligner == 'star' && params.star_index == false && fasta) {
process Make_STARindex {
tag fasta
storeDir { params.outdir + "/STARIndex" }
input:
file fasta from fasta
file gencode_annotation_gtf
output:
file "star_index" into star_index
shell:
star_threads = ava_cpu- 1
"""
mkdir star_index
STAR \
--runMode genomeGenerate \
--runThreadN ${star_threads} \
--sjdbGTFfile $gencode_annotation_gtf \
--sjdbOverhang 149 \
--genomeDir star_index/ \
--genomeFastaFiles $fasta
"""
}
} else if (params.aligner == 'star' && params.star_index == false && !fasta) {
println print_red("No reference fasta sequence loaded! please specify ") + print_red("--fasta") + print_red(" with reference.")
} else if (params.aligner == 'tophat' && params.bowtie2_index == false && !fasta) {
process Make_bowtie2_index {
tag fasta
storeDir { params.outdir + "/bowtie2Index" }
input:
file fasta from fasta
output:
file "genome_bt2.*" into bowtie2_index
shell:
"""
bowtie2-build !{fasta} genome_bt2
"""
}
} else if (params.aligner == 'tophat' && !fasta) {
println print_red("No reference fasta equence loaded! please specify ") + print_red("--fasta") + print_red(" with reference.")
} else if (params.aligner == 'hisat' && !fasta) {
process Make_hisat_index {
tag fasta
storeDir { params.outdir + "/hisatIndex" }
input:
file fasta from fasta
file gencode_annotation_gtf
output:
file "genome_ht2.*" into hisat2_index
shell:
hisat2_index_threads = ava_cpu- 1
"""
#for human genome it will take more than 160GB memory and take really long time (6 more hours), thus we recommand to down pre-build genome from hisat website
extract_splice_sites.py !{gencode_annotation_gtf} >genome_ht2.ss
extract_exons.py !{gencode_annotation_gtf} > genome_ht2.exon
hisat2-build -p !{hisat2_index_threads} --ss genome_ht2.ss --exo genome_ht2.exon !{fasta} genome_ht2
"""
}
} else if (params.aligner == 'tophat' && params.hisat_index == false && !fasta) {
println print_red("No reference fasta sequence loaded! please specify ") + print_red("--fasta") + print_red(" with reference.")
}*/
println print_purple("Analysis from fastq file")
//Match the pairs on two channels
reads = params.inputdir + params.reads
/*
* Step 3: QC (FastQC/AfterQC/Fastp) of raw reads
*/
println print_purple("Perform quality control of raw fastq files ")
if (params.qctools == 'fastqc') {
Channel.fromFilePairs(reads, size: params.singleEnd ? 1 : 2)
.ifEmpty {
exit 1, print_red("Cannot find any reads matching: ${reads}\nNB: Path needs to be enclosed in quotes!\n")
}
.into { reads_for_fastqc; readPairs_for_discovery;readPairs_for_kallisto}
process Run_fastQC {
tag { fastq_tag }
label 'qc'
publishDir pattern: "*.html",
path: { params.outdir + "/QC" }, mode: 'copy', overwrite: true
input:
set val(samplename), file(fastq_file) from reads_for_fastqc
output:
file "*.html" into fastqc_for_waiting
shell:
fastq_tag = samplename
'''
fastqc -t !{task.cpus} !{fastq_file[0]} !{fastq_file[1]}
'''
}
}
else if (params.qctools == 'afterqc'){
Channel.fromFilePairs(reads, size: params.singleEnd ? 1 : 2)
.ifEmpty {
exit 1, print_red("Cannot find any reads matching: ${reads}\nPlz check your fasta string in nextflow.config file \n")
}.set { reads_for_fastqc}
process Run_afterQC {
tag { fastq_tag }
label 'qc'
publishDir pattern: "QC/*.html",
path: { params.outdir + "/QC" }, mode: 'copy', overwrite: true
input:
set val(samplename), file(fastq_file) from reads_for_fastqc
output:
file "QC/*.html" into fastqc_for_waiting
set val(fastq_tag), file('*.good.fq.gz') into readPairs_for_discovery,readPairs_for_kallisto
shell:
fastq_tag = samplename
if (params.singleEnd) {
'''
after.py -z -1 !{fastq_file[0]} -g ./
'''
} else {
'''
after.py -z -1 !{fastq_file[0]} -2 !{fastq_file[1]} -g ./
'''
}
}
}
else if (params.qctools == 'fastp'){
Channel.fromFilePairs(reads, size: params.singleEnd ? 1 : 2)
.ifEmpty {
exit 1, print_red("Cannot find any reads matching: ${reads}\nPlz check your fasta string in nextflow.config file \n")
}
.set { reads_for_fastqc}
process Run_FastP {
tag { fastq_tag }
label 'qc'
publishDir pattern: "*.html",
path: { params.outdir + "/QC" }, mode: 'copy', overwrite: true
input:
set val(samplename), file(fastq_file) from reads_for_fastqc
output:
file "*.html" into fastqc_for_waiting
set val(fastq_tag), file('*qc.fq.gz') into readPairs_for_discovery,readPairs_for_kallisto
shell:
fastq_tag = samplename
if (params.singleEnd) {
'''
fastp -i !{fastq_file[0]} -o !{samplename}.qc.gz -h !{samplename}_fastp.html
'''
} else {
'''
fastp -i !{fastq_file[0]} -I !{fastq_file[1]} -o !{samplename}_1.qc.fq.gz -O !{samplename}_2.qc.fq.gz -h !{samplename}_fastp.html
'''
}
}
}else{
Channel.fromFilePairs(reads, size: params.singleEnd ? 1 : 2)
.ifEmpty {
exit 1, print_red("Cannot find any reads matching: ${reads}\nPlz check your fasta string in nextflow.config file \n")
}
.into{readPairs_for_discovery; readPairs_for_kallisto;fastqc_for_waiting}
}
fastqc_for_waiting = fastqc_for_waiting.first()
/*
* Step 4: Initialize read alignment (STAR/HISAT2/tophat)
*/
if (params.aligner == 'star') {
process fastq_star_alignment_For_discovery {
tag { file_tag }
publishDir pattern: "",
path: { params.outdir + "/Star_alignment" }, mode: 'copy', overwrite: true
input:
set val(samplename), file(pair) from readPairs_for_discovery
file tempfiles from fastqc_for_waiting // just for waiting
file fasta
file star_index
output:
set val(file_tag_new), file("${file_tag_new}Aligned.sortedByCoord.out.bam") into mappedReads,forHtseqMappedReads
file "${file_tag_new}Log.final.out" into alignment_logs
shell:
println print_purple("Start mapping with STAR aligner " + samplename)
file_tag = samplename
file_tag_new = file_tag
if (params.singleEnd) {
println print_purple("Initial reads mapping of " + samplename + " performed by STAR in single-end mode")
"""
STAR --runThreadN !{task.cpus} \
--twopassMode Basic \
--genomeDir !{star_index} \
--readFilesIn !{pair} \
--readFilesCommand zcat \
--outSAMtype BAM SortedByCoordinate \
--chimSegmentMin 20 \
--outFilterIntronMotifs RemoveNoncanonical \
--outFilterMultimapNmax 20 \
--alignIntronMin 20 \
--alignIntronMax 1000000 \
--alignMatesGapMax 1000000 \
--outFilterType BySJout \
--alignSJoverhangMin 8 \
--alignSJDBoverhangMin 1 \
--outFileNamePrefix !{file_tag_new}
"""
} else {
println print_purple("Initial reads mapping of " + samplename + " performed by STAR in paired-end mode")
'''
STAR --runThreadN !{task.cpus} \
--twopassMode Basic --genomeDir !{star_index} \
--readFilesIn !{pair[0]} !{pair[1]} \
--readFilesCommand zcat \
--outSAMtype BAM SortedByCoordinate \
--chimSegmentMin 20 \
--outFilterIntronMotifs RemoveNoncanonical \
--outFilterMultimapNmax 20 \
--alignIntronMin 20 \
--alignIntronMax 1000000 \
--alignMatesGapMax 1000000 \
--outFilterType BySJout \
--alignSJoverhangMin 8 \
--alignSJDBoverhangMin 1 \
--outFileNamePrefix !{file_tag_new}
'''
}
}
}
else if (params.aligner == 'tophat')
{
process fastq_tophat_alignment_For_discovery {
tag { file_tag }
publishDir pattern: "",
path: { params.outdir + "/tophat_alignment" }, mode: 'copy', overwrite: true
input:
set val(samplename), file(pair) from readPairs_for_discovery
file tempfiles from fastqc_for_waiting // just for waiting
file fasta
file bowtie2_index from bowtie2_index.collect()
file gtf from gencode_annotation_gtf
output:
set val(samplename),file("${file_tag_new}_thout/accepted.bam") into mappedReads,forHtseqMappedReads
file "${file_tag_new}_thout/Alignment_summary.txt" into alignment_logs
//align_summary.txt as log file
shell:
println print_purple("Start mapping with tophat2 aligner " + samplename)
file_tag = samplename
file_tag_new = file_tag
index_base = bowtie2_index[0].toString() - ~/.\d.bt2/
strand_str="fr-firststrand"
if(unstrand){
strand_str="fr-unstranded"
}
if (params.singleEnd) {
println print_purple("Initial reads mapping of " + samplename + " performed by Tophat in single-end mode")
'''
tophat -p !{task.cpus} -G !{gtf} -–no-novel-juncs -o !{samplename}_thout --library-type !{strand_str} !{index_base} !{pair}
'''
} else {
println print_purple("Initial reads mapping of " + samplename + " performed by Tophat in paired-end mode")
'''
tophat -p !{task.cpus} -G !{gtf} -–no-novel-juncs -o !{samplename}_thout --library-type !{strand_str} !{index_base} !{pair[0]} !{pair[1]}
'''
}
}
}
else if (params.aligner == 'hisat') {
process fastq_hisat2_alignment_For_discovery {
tag { file_tag }
label 'para'
publishDir pattern: "",
path: { params.outdir + "/hisat_alignment" }, mode: 'copy', overwrite: true
input:
set val(samplename), file(pair) from readPairs_for_discovery
file tempfiles from fastqc_for_waiting // just for waiting
file fasta
file hisat2_id from hisat2_index.collect()
output:
set val(file_tag_new),file("${file_tag_new}.sort.bam") into hisat_mappedReads,forHtseqMappedReads
file "${file_tag_new}.hisat2_summary.txt" into alignment_logs
//align_summary.txt as log file
shell:
println print_purple("Start mapping with hisat2 aligner " + samplename)
file_tag = samplename
file_tag_new = file_tag
index_base = hisat2_id[0].toString() - ~/.\d.ht2/
if(unstrand){
if (params.singleEnd) {
println print_purple("Initial reads mapping of " + samplename + " performed by hisat2 in single-end mode")
'''
mkdir tmp
hisat2 -p !{task.cpus} --dta -x !{index_base} -U !{pair} -S !{file_tag_new}.sam 2>!{file_tag_new}.hisat2_summary.txt
sambamba view -S -f bam -t !{task.cpus} !{file_tag_new}.sam -o temp.bam
sambamba sort -o !{file_tag_new}.sort.bam --tmpdir ./tmp -t !{task.cpus} temp.bam
rm !{file_tag_new}.sam
rm temp.bam
'''
} else {
println print_purple("Initial reads mapping of " + samplename + " performed by hisat2 in paired-end mode")
'''
mkdir tmp
hisat2 -p !{task.cpus} --dta -x !{index_base} -1 !{pair[0]} -2 !{pair[1]} -S !{file_tag_new}.sam 2> !{file_tag_new}.hisat2_summary.txt
sambamba view -S -f bam -t !{hisat2_threads} !{file_tag_new}.sam -o temp.bam
sambamba sort -o !{file_tag_new}.sort.bam --tmpdir ./tmp -t !{task.cpus} temp.bam
rm !{file_tag_new}.sam
'''
}
}else {
if (params.singleEnd) {
println print_purple("Initial reads mapping of " + samplename + " performed by hisat2 in single-end mode")
'''
mkdir tmp
hisat2 -p !{task.cpus} --dta --rna-strandness !{params.hisat_strand} -x !{index_base} -U !{pair} -S !{file_tag_new}.sam 2>!{file_tag_new}.hisat2_summary.txt
sambamba view -S -f bam -t !{hisat2_threads} !{file_tag_new}.sam -o temp.bam
sambamba sort -o !{file_tag_new}.sort.bam --tmpdir ./tmp -t !{hisat2_threads} temp.bam
rm !{file_tag_new}.sam
rm temp.bam
'''
} else {
println print_purple("Initial reads mapping of " + samplename + " performed by hisat2 in paired-end mode")
'''
mkdir tmp
hisat2 -p !{task.cpus} --dta --rna-strandness !{params.hisat_strand} -x !{index_base} -1 !{pair[0]} -2 !{pair[1]} -S !{file_tag_new}.sam 2> !{file_tag_new}.hisat2_summary.txt
sambamba view -S -f bam -t !{task.cpus} !{file_tag_new}.sam -o temp.bam
sambamba sort -o !{file_tag_new}.sort.bam --tmpdir ./tmp -t !{task.cpus} temp.bam
rm !{file_tag_new}.sam
'''
}
}
}
}
/*
* Step 5: Transcript assembly using Stringtie
*/
if(params.aligner == 'hisat'){
process StringTie_assembly {
tag { file_tag }
input:
set val(samplename),file(alignment_bam) from hisat_mappedReads
file fasta
file gencode_annotation_gtf
output:
file "stringtie_${file_tag_new}_transcripts.gtf" into stringTieoutgtf, StringTieOutGtf_fn
shell:
file_tag = samplename
file_tag_new = file_tag
if(unstrand){
'''
#run stringtie
stringtie -p !{task.cpus} -G !{gencode_annotation_gtf} -l stringtie_!{file_tag_new} -o stringtie_!{file_tag_new}_transcripts.gtf !{alignment_bam}
'''
}else{
'''
#run stringtie
stringtie -p !{task.cpus} -G !{gencode_annotation_gtf} --rf -l stringtie_!{file_tag_new} -o stringtie_!{file_tag_new}_transcripts.gtf !{alignment_bam}
'''
}
}
// Create a file 'gtf_filenames' containing the filenames of each post processes cufflinks gtf
stringTieoutgtf.collectFile { file -> ['gtf_filenames.txt', file.name + '\n'] }
.set { GTFfilenames }
/*
* Step 6: Merged GTFs into one
*/
process StringTie_merge_assembled_gtf {
tag { file_tag }
label 'para'
publishDir pattern: "merged.gtf",
path: { params.outdir + "/Merged_assemblies" }, mode: 'copy', overwrite: true
input:
file gtf_filenames from GTFfilenames
file cufflinksgtf_file from StringTieOutGtf_fn.toList() // not used but just send the file in current running folder
file fasta
output:
file "merged.gtf" into mergeTranscripts_forCompare, mergeTranscripts_forExtract, mergeTranscripts_forCodeingProtential
shell:
'''
stringtie --merge -p !{task.cpus} -o merged.gtf !{gtf_filenames}
'''
}
}
else{
process Cufflinks_assembly {
tag { file_tag }
input:
set val(file_tag), file(alignment_bam) from mappedReads
file fasta
file gencode_annotation_gtf
output:
file "Cufout_${file_tag_new}_transcripts.gtf" into cuflinksoutgtf, cuflinksoutgtf_fn
shell:
file_tag_new = file_tag
strand_str="fr-firststrand"
if(unstrand){
strand_str="fr-unstranded"
}
if (params.aligner == 'tophat') {
'''
#run cufflinks
cufflinks -g !{gencode_annotation_gtf} \
-b !{fasta} \
--library-type !{strand_str}\
--max-multiread-fraction 0.25 \
--3-overhang-tolerance 2000 \
-o Cufout_!{file_tag_new} \
-p !{task.cpus} !{alignment_bam}
mv Cufout_!{file_tag_new}/transcripts.gtf Cufout_!{file_tag_new}_transcripts.gtf
'''
} else if (params.aligner == 'star') {
'''
#run cufflinks
cufflinks -g !{gencode_annotation_gtf} \
-b !{fasta} \
--library-type !{strand_str} \
--max-multiread-fraction 0.25 \
--3-overhang-tolerance 2000 \
-o Cufout_!{file_tag_new} \
-p !{task.cpus} !{alignment_bam}
mv Cufout_!{file_tag_new}/transcripts.gtf Cufout_!{file_tag_new}_transcripts.gtf
'''
}
}
// Create a file 'gtf_filenames' containing the filenames of each post processes cufflinks gtf
cuflinksoutgtf.collectFile { file -> ['gtf_filenames.txt', file.name + '\n'] }
.set { GTFfilenames }
/*
* Step 6: Merged GTFs into one
*/
process cuffmerge_assembled_gtf {
tag { file_tag }
label 'para'
publishDir pattern: "CUFFMERGE/merged.gtf",
path: { params.outdir + "/All_assemblies" }, mode: 'copy', overwrite: true
input:
file gtf_filenames from GTFfilenames
file cufflinksgtf_file from cuflinksoutgtf_fn.toList() // not used but just send the file in current running folder
file fasta
output:
file "CUFFMERGE/merged.gtf" into mergeTranscripts_forCompare, mergeTranscripts_forExtract, mergeTranscripts_forCodeingProtential
shell:
'''
mkdir CUFFMERGE
cuffmerge -o CUFFMERGE \
-s !{fasta} \
-p !{task.cpus} \
!{gtf_filenames}
'''
}
}
}
else {
println print_yellow("Raw reads quality check step was skipped due to provided ") + print_green("--merged_gtf") + print_yellow(" option\n")
println print_yellow("Reads mapping step was skipped due to provided ") + print_green("--merged_gtf") + print_yellow(" option\n")
merged_gtf = file(params.merged_gtf)
Channel.fromPath(merged_gtf)
.ifEmpty { exit 1, "Cannot find merged gtf : ${merged_gtf}" }
.into {
mergeTranscripts_forCompare; mergeTranscripts_forExtract; mergeTranscripts_forCodeingProtential
}
// add fastq when do quantification
reads = params.inputdir + params.reads
if (params.qctools == 'fastqc') {
Channel.fromFilePairs(reads, size: params.singleEnd ? 1 : 2)
.ifEmpty {
exit 1, print_red("Fastq file not found, plz check your file path : ${reads}\n")
}
.into { reads_for_fastqc; readPairs_for_discovery;readPairs_for_kallisto}
process Run_fastQC_2 {
tag { fastq_tag }
label 'qc'
publishDir pattern: "*.html",
path: { params.outdir + "/QC" }, mode: 'copy', overwrite: true
input:
set val(samplename), file(fastq_file) from reads_for_fastqc
output:
file "*.html" into fastqc_for_waiting
shell:
fastq_tag = samplename
'''
fastqc -t !{task.cpus} !{fastq_file[0]} !{fastq_file[1]}
'''
}
}
else if (params.qctools == 'afterqc'){
Channel.fromFilePairs(reads, size: params.singleEnd ? 1 : 2)
.ifEmpty {
exit 1, print_red("Fastq file not found : ${reads}\nPlz check your reads string in nextflow.config file \n")
}
.set { reads_for_fastqc}
process Run_afterQC_2 {
tag { fastq_tag }
label 'qc'
publishDir pattern: "QC/*.html",
path: { params.outdir + "/QC" }, mode: 'copy', overwrite: true
input:
set val(samplename), file(fastq_file) from reads_for_fastqc
output:
file "QC/*.html" into fastqc_for_waiting
set val(fastq_tag), file('*.good.fq.gz') into readPairs_for_discovery,readPairs_for_kallisto
shell:
fastq_tag = samplename
if (params.singleEnd) {
'''
after.py -z -1 !{fastq_file[0]} -g ./
'''
} else {
'''
after.py -z -1 !{fastq_file[0]} -2 !{fastq_file[1]} -g ./
'''
}
}
}
else if (params.qctools == 'fastp'){
Channel.fromFilePairs(reads, size: params.singleEnd ? 1 : 2)
.ifEmpty {
exit 1, print_red("Fastq file not found : ${reads}\nPlz check your reads string in nextflow.config file \n")
}
.set { reads_for_fastqc}
process Run_FastP_2 {
tag { fastq_tag }
label 'qc'
publishDir pattern: "*.html",
path: { params.outdir + "/QC" }, mode: 'copy', overwrite: true
input:
set val(samplename), file(fastq_file) from reads_for_fastqc
output:
file "*.html" into fastqc_for_waiting
set val(fastq_tag), file('*qc.fq.gz') into readPairs_for_discovery,readPairs_for_kallisto
shell:
fastq_tag = samplename
if (params.singleEnd) {
'''
fastp -i !{fastq_file[0]} -o !{samplename}.qc.gz -h !{samplename}_fastp.html
'''
} else {
'''
fastp -i !{fastq_file[0]} -I !{fastq_file[1]} -o !{samplename}_1.qc.fq.gz -O !{samplename}_2.qc.fq.gz -h !{samplename}_fastp.html
'''
}
}
}
else{
Channel.fromFilePairs(reads, size: params.singleEnd ? 1 : 2)
.ifEmpty {
exit 1, print_red("Cannot find any reads matching: ${reads}\nPlz check your reads string in nextflow.config file \n")
}
.into{readPairs_for_discovery; readPairs_for_kallisto;fastqc_for_waiting}
}
fastqc_for_waiting2 = fastqc_for_waiting.first()
}
/*
*Step 7: Compare assembled gtf with known annotations (GENCODE)
*/
process Merge_assembled_gtf_with_GENCODE {
tag { file_tag }
input:
file mergeGtfFile from mergeTranscripts_forCompare
file gencode_annotation_gtf
output:
file "merged_lncRNA.merged.gtf.tmap" into comparedGTF_tmap
shell:
'''
#!/bin/sh
gffcompare -r !{gencode_annotation_gtf} -p !{task.cpus} !{mergeGtfFile} -o merged_lncRNA
'''
}
/*
*Step 8: Filter GTFs to distinguish novel lncRNAs
*/
process Identify_novel_lncRNA_with_criterions {
input:
file comparedTmap from comparedGTF_tmap
file fasta
file mergedGTF from mergeTranscripts_forExtract
output:
file "novel.gtf.tmap" into noveltmap
file "novel.longRNA.fa" into novelLncRnaFasta
file "novel.longRNA.exoncount.txt" into novelLncRnaExonCount
shell:
'''
# filtering novel lncRNA based on cuffmerged trascripts
awk '$3 =="x"||$3=="u"||$3=="i"{print $0}' !{comparedTmap} > novel.gtf.tmap
# excluding length smaller than 200 nt
awk '$10 >200{print}' novel.gtf.tmap > novel.longRNA.gtf.tmap
# extract gtf
awk '{print $5}' novel.longRNA.gtf.tmap |perl !{baseDir}/bin/extract_gtf_by_name.pl !{mergedGTF} - >novel.longRNA.gtf
awk '{if($3=="exon"){print $0}}' novel.longRNA.gtf > novel.longRNA.format.gtf
perl !{baseDir}/bin/get_exoncount.pl novel.longRNA.format.gtf > novel.longRNA.exoncount.txt
# gtf2gff3
#check whether required
# get fasta from gtf
gffread novel.longRNA.gtf -g !{fasta} -w novel.longRNA.fa -W
'''
}
/*
*Step 9: Predict coding potential abilities using CPAT and PLEK (CNCI functionality coming soon!)
*/
novelLncRnaFasta.into { novelLncRnaFasta_for_PLEK; novelLncRnaFasta_for_CPAT; }
process Predict_coding_abilities_by_PLEK {
// as PLEK can not return valid exit status even run smoothly, we manually set the exit status into 0 to promote analysis
validExitStatus 0, 1, 2
input:
file novel_lncRNA_fasta from novelLncRnaFasta_for_PLEK
output:
file "novel.longRNA.PLEK.out" into novel_longRNA_PLEK_result
shell:
'''
PLEK.py -fasta !{novel_lncRNA_fasta} \
-out novel.longRNA.PLEK.out \
-thread !{task.cpus}
exit 0
'''
}
process Predict_coding_abilities_by_CPAT {
input:
file novel_lncRNA_fasta from novelLncRnaFasta_for_CPAT
output:
file "novel.longRNA.CPAT.out" into novel_longRNA_CPAT_result
shell:
if(params.species=="human"){
'''
cpat.py -g !{novel_lncRNA_fasta} \
-x !{baseDir}/bin/cpat_model/Human_Hexamer.tsv \
-d !{baseDir}/bin/cpat_model/Human_logitModel.RData \
-o novel.longRNA.CPAT.out
'''
}else if (params.species=="mouse"){
'''
cpat.py -g !{novel_lncRNA_fasta} \
-x !{baseDir}/bin/cpat_model/Mouse_Hexamer.tsv \
-d !{baseDir}/bin/cpat_model/Mouse_logitModel.RData \
-o novel.longRNA.CPAT.out
'''
}else if (params.species=="zebrafish"){
'''
cpat.py -g !{novel_lncRNA_fasta} \
-x !{baseDir}/bin/cpat_model/zebrafish_Hexamer.tsv \