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main.nf
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main.nf
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#!/usr/bin/env nextflow
/*
* christopher.barrington chez crick.ac.uk
* gavin.kelly chez crick.ac.uk
* harshil.patel chez crick.ac.uk
* nourdine.bah chez crick.ac.uk
* philip.east chez crick.ac.uk
* richard.mitter chez crick.ac.uk
*/
// groovy modules
import groovy.io.FileType
import groovy.json.JsonSlurper
import groovy.json.JsonOutput
// the java modules
import java.nio.file.Paths
// custom module
import qcpipeline.Project
import qcpipeline.Sample
import qcpipeline.Fastq
publish_mode = "symlink"
publish_overwrite = true
//// all the fastq files of the project
//fastq_files = []
//params.directories.each{ path ->
// def dir = new File(path)
// dir.eachFileMatch(FileType.FILES, ~/.*\.fastq\.gz/) { f ->
// Fastq fastq = new Fastq(f)
// fastq.setSpecies(params.species)
// fastq.setSequencing_type(params.type.toLowerCase().replaceAll(" |-", ""))
// fastq_files.add(fastq)
// }
//}
//
///*|||||||||||||||||||||*/
//Channel.from(fastq_files)
///*|||||||||||||||||||||*/
// //// test
// //.map{
// // [ it.getFile().getBaseName().replaceAll("_R\\d_001.fastq", ""), it ]
// //}
// //.groupTuple()
// //.take(3)
// //.map{ it[1] }
// //.flatten()
// //// test
// .into{ fastqs; to_read_length }
/*|||*/
Channel
/*|||*/
.fromPath(params.csv)
.splitCsv(header:true)
.map{
Fastq fastq = new Fastq(
new File(it["file"]),
it["type"].toLowerCase().replaceAll(" |-", ""),
it["species"]
)
}
//// test
//.map{
// [ it.getFile().getBaseName().replaceAll("_R\\d_001.fastq", ""), it ]
//}
//.groupTuple()
//.take(3)
//.map{ it[1] }
//.flatten()
//// test
.into{ fastqs; to_read_length }
/*||||||||||*/
to_read_length
/*||||||||||*/
.map{ [ it.getBasename() , it.getFile() ] }
.set{ to_read_length }
///////////////////////////////////////////////////////////////////////////////
// ------------------------------------------------------------------------- //
// ------------------------------------------------------------------------- //
// ---------------------------- PARAMETERS --------------------------------- //
// ------------------------------------------------------------------------- //
// ------------------------------------------------------------------------- //
///////////////////////////////////////////////////////////////////////////////
// choose the species
genomes = [:]
genomes["homo sapiens"] = ["version":"GRCh38", "release":"86"]
genomes["mus musculus"] = ["version":"GRCm38", "release":"86"]
// configuration
fastq_screen_conf = absolute_path( "conf/fastq_screen.conf" )
multiqc_conf_file = absolute_path( "conf/multiqc.yml" )
// script locations
py_dir = absolute_path("scripts/py")
cpp_dir = absolute_path("scripts/cpp")
qc_genes_dir = absolute_path("scripts/qc_genes_list/txt")
///////////////////////////////////////////////////////////////////////////////
// ------------------------------------------------------------------------- //
// ------------------------------------------------------------------------- //
// ------------------------- VARIOUS FUNCTIONS ----------------------------- //
// ------------------------------------------------------------------------- //
// ------------------------------------------------------------------------- //
///////////////////////////////////////////////////////////////////////////////
/* ----------------------- */
def get_file(species, name) {
/* ----------------------- */
version = genomes[ species.toLowerCase() ]["version"]
release = genomes[ species.toLowerCase() ]["release"]
genome = params.genomes[version][release]
return genome[name]
}
/* ------------------------------------------ */
def get_star_index(species, rough_read_length) {
/* ------------------------------------------ */
version = genomes[ species.toLowerCase() ]["version"]
release = genomes[ species.toLowerCase() ]["release"]
genome = params.genomes[version][release]
return genome.star[ rough_read_length + "bp" ].index
}
/* ----------------------------------------------- */
def get_rsem_star_index(species, rough_read_length) {
/* ----------------------------------------------- */
version = genomes[ species.toLowerCase() ]["version"]
release = genomes[ species.toLowerCase() ]["release"]
genome = params.genomes[version][release]
return genome.rsem.rsem_star[ rough_read_length + "bp" ].index
}
/* --------------------------- */
def flatten_paired_end(channel) {
/* --------------------------- */
// the .transpose() nextflow operator can be used here instead
def single_end = channel[2]
if (single_end) {
return channel
} else {
return [ *channel[0..2], channel[3][0], *channel[0..2], channel[3][1] ]
}
}
/* ------------------------ */
def sort_files(path1, path2) {
/* ------------------------ */
def f1 = Paths.get( path1.toString() ).getFileName()
def f2 = Paths.get( path2.toString() ).getFileName()
if ( f1 == f2 ) {
return 0
} else if ( f1 > f2 ) {
return 1
} else {
return -1
}
}
/* ------------------- */
def absolute_path(path) {
/* ------------------- */
def f = new File(path)
if ( ! f.isAbsolute() ) {
return Paths.get(workflow.projectDir.toString(), path).toString()
} else {
return path
}
}
/* -------------- */
def get_lims(name) {
/* -------------- */
return name.replaceAll("_.*", "")
}
/* -------------------------- */
def get_experiment_info(fastq) {
/* -------------------------- */
// fastq info
def species = fastq.getSpecies()
def read_length = fastq.getRead_length()
def rough_read_length = fastq.getRough_read_length()
def type = fastq.getSequencing_type()
def machine = fastq.getMachine().getName()
def run = fastq.getRun().getNumber()
def lane = fastq.getLane().getNumber()
// annotation
def star_index = get_star_index( species , rough_read_length )
def rsem_star_index = get_star_index( species , rough_read_length )
def fasta = get_file( species , "fasta" )
def bed = get_file( species , "bed" )
def refflat = get_file( species , "refflat" )
def rrna_list = get_file( species , "rrna_list" )
def rrna_interval_list = get_file( species , "rrna_interval_list" )
def gtf = get_file( species , "gtf" )
def rnaseqc_gtf = get_file( species , "rnaseqc_gtf" )
def info = [
[ "Species" , species ],
[ "Read Length" , read_length ],
[ "Rough Read Length" , rough_read_length ],
[ "Sequencing Type" , type ],
[ "Machine" , machine ],
[ "Run" , run ],
[ "Lane" , lane ],
[ "STAR Index" , star_index ],
[ "RSEM-STAR Index" , rsem_star_index ],
[ "FASTA" , fasta ],
[ "GTF" , gtf ],
[ "BED" , bed ],
[ "REFFLAT" , refflat ],
[ "RNASeqC GTF" , rnaseqc_gtf ],
[ "Ribosomal RNAs" , rrna_list ],
[ "Ribosomal RNAs Intervals" , rrna_interval_list ]
]
return info
}
///////////////////////////////////////////////////////////////////////////////
// ------------------------------------------------------------------------- //
// ------------------------------------------------------------------------- //
// ---------------------------- READ LENGTH -------------------------------- //
// ------------------------------------------------------------------------- //
// ------------------------------------------------------------------------- //
///////////////////////////////////////////////////////////////////////////////
///////////////////
process read_length {
///////////////////
tag { basename }
input:
set val(basename), val(fastq) from to_read_length
output:
set val(basename), stdout into lengths
script:
template "read_length.sh"
}
/*||*/
fastqs
/*||*/
.map{ [ it.getBasename() , it ] }
.combine(lengths)
.filter{ it[0] == it[2] }
.map{ it[1].addReadLength( it[3].toInteger() ) }
.set{ fastqs }
///////////////////////////////////////////////////////////////////////////////
// ------------------------------------------------------------------------- //
// ------------------------------------------------------------------------- //
// --------------------------- CREATE PROJECT ------------------------------ //
// ------------------------------------------------------------------------- //
// ------------------------------------------------------------------------- //
///////////////////////////////////////////////////////////////////////////////
// all the fastq files with their read length
fastq_list =
fastqs
.toSortedList()
.get()
.toList()
// finally create the project
project = new Project(fastq_list)
project_outdir = project.getId()
///////////////////////////////////////////////////////////////////////////////
// ------------------------------------------------------------------------- //
// ------------------------------------------------------------------------- //
// ------------------------------- FASTQC ---------------------------------- //
// ------------------------------------------------------------------------- //
// ------------------------------------------------------------------------- //
///////////////////////////////////////////////////////////////////////////////
//////////////
process fastqc {
//////////////
tag { basename }
input:
set \
val(flowcell),
val(name),
val(fastq) from Channel.from( project.getFastqC() )
output:
set \
val(flowcell),
val(name),
file("*.fastqc") into fastqc
script:
basename = flowcell + "_" + name
outdir = basename + ".fastqc"
// to avoid multiple the multiqc general statistics table
new_fastq = basename + ".fastq.gz"
template "fastqc.sh"
}
///////////////////////////////////////////////////////////////////////////////
// ------------------------------------------------------------------------- //
// ------------------------------------------------------------------------- //
// ------------------------------ CUTADAPT --------------------------------- //
// ------------------------------------------------------------------------- //
// ------------------------------------------------------------------------- //
///////////////////////////////////////////////////////////////////////////////
////////////////
process cutadapt {
////////////////
tag { basename }
input:
set \
val(flowcell),
val(name),
val(single_end),
val(fastq) from Channel.from( project.getCutadapt() )
output:
set \
val(flowcell),
val(name),
val(single_end),
file('*.log') into cutadapt_log
set \
val(flowcell),
val(name),
val(single_end),
file('*.cutadapt.fastq.gz') \
into \
cutadapt,
cutadapt_fastq_screen,
cutadapt_align,
cutadapt_multiqc
script:
basename = flowcell + "_" + name
if (single_end) {
fastq = fastq[0]
output = basename + ".cutadapt.fastq.gz"
logfile = basename + ".log"
// to avoid multiple the multiqc general statistics table
new_fastq = basename + ".fastq.gz"
template "cutadapt/single_end.sh"
} else {
fastq1 = fastq[0]
fastq2 = fastq[1]
output1 = basename + "_1.cutadapt.fastq.gz"
output2 = basename + "_2.cutadapt.fastq.gz"
logfile = basename + ".log"
// to avoid multiple the multiqc general statistics table
new_fastq1 = basename + "_1.fastq.gz"
new_fastq2 = basename + "_2.fastq.gz"
template "cutadapt/paired_end.sh"
}
}
/*|| separate the two fastq files if it's paired-end and add a tag ||*/
/*|| corresponding to the read number ||*/
/*||||*/
cutadapt
/*||||*/
.map{ flatten_paired_end(it) } // .transpose() can be used here instead
.flatten()
.collate(4)
.map{[
*it[0..2],
it[3] ==~ /.*_1.cutadapt.fastq.gz$/ ? "1" : "2",
it[3]
]}
.into{ cutadapt_fastqc; cutadapt_strandedness }
///////////////////////////////////////////////////////////////////////////////
// ------------------------------------------------------------------------- //
// ------------------------------------------------------------------------- //
// -------------------------- FASTQC CUTADAPT ------------------------------ //
// ------------------------------------------------------------------------- //
// ------------------------------------------------------------------------- //
///////////////////////////////////////////////////////////////////////////////
///////////////////////
process fastqc_cutadapt {
///////////////////////
tag { basename }
input:
set \
val(flowcell),
val(name),
val(single_end),
val(read_num),
file(fastq) from cutadapt_fastqc
output:
set \
val(flowcell),
val(name),
val(single_end),
val(read_num),
file("*fastqc*") into fastqc_cutadapt
script:
basename = flowcell + "_" + name + "_R" + read_num
basename = "cutadapt_" + basename
outdir = basename + ".fastqc"
template "fastqc_cutadapt.sh"
}
///////////////////////////////////////////////////////////////////////////////
// ------------------------------------------------------------------------- //
// ------------------------------------------------------------------------- //
// -------------------------- FASTQ SCREEN --------------------------------- //
// ------------------------------------------------------------------------- //
// ------------------------------------------------------------------------- //
///////////////////////////////////////////////////////////////////////////////
////////////////////
process fastq_screen {
////////////////////
tag { basename }
input:
set \
val(flowcell),
val(name),
val(single_end),
file(fastq) from cutadapt_fastq_screen.transpose()
output:
set \
val(flowcell),
val(name),
val(single_end),
file("*.html") into fscreen_html
set \
val(flowcell),
val(name),
val(single_end),
file("*.txt") into fscreen_txt
script:
basename = flowcell + "_" + name
template "fastq_screen.sh"
}
///////////////////////////////////////////////////////////////////////////////
// ------------------------------------------------------------------------- //
// ------------------------------------------------------------------------- //
// -------------------- STRANDEDNESS SEQUENCING TYPE ---------------------- //
// ------------------------------------------------------------------------- //
// ------------------------------------------------------------------------- //
///////////////////////////////////////////////////////////////////////////////
/*||||||||||||||||||||||||*/
rnaseq_cutadapt_strandedness =
Channel.create()
/*||||||||||||||||||||||||||||*/
non_rnaseq_cutadapt_strandedness =
Channel.create()
/*|||||||||||||||||*/
cutadapt_strandedness
.choice(rnaseq_cutadapt_strandedness, non_rnaseq_cutadapt_strandedness) {
it = project.getSequencingType( get_lims(it[1]) ) == "rnaseq" ? 0 : 1
}
///////////////////////////////////////////////////////////////////////////////
// ------------------------------------------------------------------------- //
// ------------------------------------------------------------------------- //
// ----------------------------- SAMPLING ---------------------------------- //
// ------------------------------------------------------------------------- //
// ------------------------------------------------------------------------- //
///////////////////////////////////////////////////////////////////////////////
///////////////////////////////////////////////////////////////////////////////
// ------------------------------ SEQTK ------------------------------------ //
///////////////////////////////////////////////////////////////////////////////
////////////////
process sampling {
////////////////
tag { basename }
input:
set \
val(flowcell),
val(name),
val(single_end),
val(read_num),
file(fastq) from rnaseq_cutadapt_strandedness
output:
set \
val(flowcell),
val(name),
val(single_end),
val(read_num),
file("*.sampled.fastq.gz") into sampling
script:
n = 1000
basename = flowcell + "_" + name + "_R" + read_num
filename = basename + ".sampled.fastq.gz"
template "seqtk/sample.sh"
}
///////////////////////////////////////////////////////////////////////////////
// ------------------------------- STAR ------------------------------------ //
///////////////////////////////////////////////////////////////////////////////
/*||||*/
sampling
/*||||*/
.groupTuple(by:[0,1,2])
.map{ [ *it[0..2] , it[4].sort{ x,y -> sort_files(x,y) } ] }
.set{ sampling }
/*|| add species and read length ||*/
/*||||*/
sampling
.map{[
*it[0..2],
project.getSpecies( get_lims(it[1]) ),
project.getRoughReadLength( get_lims(it[1]) ),
it[3]
]}
.set{ sampling }
/*|| add rsem star index ||*/
/*||||*/
sampling
.map{[
*it[0..2],
get_star_index( it[3] , it[4] ),
it[5]
]}
.set{ sampling }
////////////////////
process sampled_star {
////////////////////
tag { basename }
input:
set \
val(flowcell),
val(name),
val(single_end),
val(genome),
file(fastq) from sampling
output:
set \
val(flowcell),
val(name),
val(single_end),
file("*.Aligned.sortedByCoord.out.bam") into sampled_bam
script:
basename = flowcell + "_" + name
cpus = task.cpus
template "star.sh"
}
///////////////////////////////////////////////////////////////////////////////
// ------------------------------- SAMTOOLS -------------------------------- //
///////////////////////////////////////////////////////////////////////////////
////////////////////
process sampled_sort {
////////////////////
tag { basename }
input:
set \
val(flowcell),
val(name),
val(single_end),
file(bam) from sampled_bam
output:
set \
val(flowcell),
val(name),
val(single_end),
file("*.bam"),
file("*.bai") \
into \
sampled_picard_rg,
sampled_picard_rg_multiqc,
sampled_sorted_bam,
sampled_sorted_bam_multiqc
script:
basename = flowcell + "_" + name
filename = basename + ".sorted.bam"
template "samtools/sort_index.sh"
}
///////////////////////////////////////////////////////////////////////////////
// -------------------------------- PICARD --------------------------------- //
///////////////////////////////////////////////////////////////////////////////
//////////////////////////////
//process sampled_picard_group {
//////////////////////////////
//
// tag { basename }
//
// input:
// set \
// val(flowcell),
// val(name),
// val(single_end),
// file(bam),
// file(bai) from sampled_sorted_bam
//
// output:
// set \
// val(flowcell),
// val(name),
// val(single_end),
// file("*.rg.bam") \
// into \
// sampled_picard_rg,
// sampled_picard_rg_multiqc
//
// script:
//
// basename = flowcell + "_" + name
// filename = basename + ".rg.bam"
// tmp_dirname = "tmp"
//
// template "picard/group.sh"
//}
////////////////////////////////
process sampled_picard_duplicate {
////////////////////////////////
tag { basename }
input:
set \
val(flowcell),
val(name),
val(single_end),
file(bam),
file(bai) from sampled_picard_rg
output:
set \
val(flowcell),
val(name),
val(single_end),
file("*.dupmarked.bam") \
into \
sampled_picard_duplicate,
sampled_picard_duplicate_multiqc
script:
basename = flowcell + "_" + name
filename = basename + ".dupmarked.bam"
metrics_filename = basename + ".marked_duplicates"
tmp_dirname = "tmp"
template "picard/duplicates.sh"
}
///////////////////////////////////////////////////////////////////////////////
// ------------------------------- SAMTOOLS -------------------------------- //
///////////////////////////////////////////////////////////////////////////////
////////////////////////////
process sampled_picard_index {
////////////////////////////
tag { basename }
input:
set \
val(flowcell),
val(name),
val(single_end),
file(bam) from sampled_picard_duplicate
output:
// !! this output triggers a WARNING because we try to publish the bam
// file a second time (the first time was with process
// "sampled_picard_duplicate"
set \
val(flowcell),
val(name),
val(single_end),
file(bam),
file("*.bai") \
into\
sampled_bam_infer_experiment,
sampled_bam_rnaseqc,
sampled_picard_index_multiqc
script:
basename = flowcell + "_" + name
template "samtools/index.sh"
}
///////////////////////////////////////////////////////////////////////////////
// --------------------------------- RSEQC --------------------------------- //
///////////////////////////////////////////////////////////////////////////////
/*|| add bed file via species ||*/
/*||||||||||||||||||||||||*/
sampled_bam_infer_experiment
.map{[
*it[0..2],
get_file( project.getSpecies( get_lims(it[1]) ) , "bed" ),
*it[3..4]
]}
.set{ sampled_bam_infer_experiment }
////////////////////////////////
process sampled_infer_experiment {
////////////////////////////////
tag { basename }
input:
set \
val(flowcell),
val(name),
val(single_end),
val(bed),
file(bam),
file(bai) from sampled_bam_infer_experiment
output:
set \
val(flowcell),
val(name),
val(single_end),
file("*.infer_experiment*") \
into \
sampled_infer_experiment,
sampled_infer_experiment_multiqc
script:
basename = flowcell + "_" + name
metrics_filename = basename + ".infer_experiment"
template "rseqc/infer_experiment.sh"
}
///////////////////////////////////////////////////////////////////////////////
// ------------------------------- RNASEQC --------------------------------- //
///////////////////////////////////////////////////////////////////////////////
/*|||||||||||||||*/
sampled_bam_rnaseqc
.map{[
*it[0..2],
get_file(
project.getSpecies( get_lims(it[1]) ),
"fasta"
),
get_file(
project.getSpecies( get_lims(it[1]) ),
"rrna_list"
),
get_file(
project.getSpecies( get_lims(it[1]) ),
"rnaseqc_gtf"
),
*it[3..4]
]}
.set{ sampled_bam_rnaseqc }
///////////////////////
process sampled_rnaseqc {
///////////////////////
tag { basename }
input:
set \
val(flowcell),
val(name),
val(single_end),
val(fasta),
val(rrna),
val(gtf),
file(bam),
file(bai) from sampled_bam_rnaseqc
output:
set \
val(flowcell),
val(name),
val(single_end),
file("*.rnaseqc") into sampled_rnaseqc, sampled_rnaseqc_multiqc
script:
basename = flowcell + "_" + name
metrics_filename = basename + ".rnaseqc"
if (single_end) {
single_end_arg = "-singleEnd"
} else {
single_end_arg = ""
}
template "rnaseqc.sh"
}
///////////////////////////////////////////////////////////////////////////////
// ------------------------------- MULTIQC --------------------------------- //
///////////////////////////////////////////////////////////////////////////////
/*||||||||||||||||||||||||||||*/
sampled_infer_experiment_multiqc
.concat(sampled_rnaseqc_multiqc)
.groupTuple(by:[0,1,2])
.set{ to_sampled_multiqc }
///////////////////////
process sampled_multiqc {
///////////////////////
tag { basename }
input:
set \
val(flowcell),
val(name),
val(single_end),
file(metrics) from to_sampled_multiqc
output:
set \
val(flowcell),
val(name),
val(single_end),
file("multiqc_data/multiqc_rseqc_infer_experiment.json"),
file("multiqc_data/multiqc_rna_seqc.json") into sampled_multiqc
script:
basename = flowcell + "_" + name
multiqc_data_format = "json"
multiqc_template = "custom"
multiqc_conf = multiqc_conf_file
template "multiqc/sampled.sh"
}
///////////////////////////////////////////////////////////////////////////////
// --------------------------- STRANDEDNESS -------------------------------- //
///////////////////////////////////////////////////////////////////////////////
////////////////////
process strandedness {
////////////////////
tag { basename }
echo true
executor "local"
input:
set \
val(flowcell),
val(name),
val(single_end),
file(rseqc_json),
file(rnaseqc_json) from sampled_multiqc
output:
set \
val(flowcell),
val(name),
val(single_end),
val(strandedness) \
into \
strandedness,
strandedness_align
script:
basename = flowcell + "_" + name
prefix = single_end ? "se" : "pe"
// get the json
slurper = new JsonSlurper()
rseqc = slurper.parse( new File( rseqc_json.toRealPath().toString() ) )
metrics = rseqc[ basename + ".infer_experiment" ]
// compute the metrics
sense = metrics[ prefix + "_sense" ]
antisense = metrics[ prefix + "_antisense" ]
failed = metrics["failed"]
normalised_sense = sense / (sense + antisense) * 100.0
normalised_antisense = antisense / (sense + antisense) * 100.0
// threshold
if ( normalised_sense < 30 ) {
strandedness = "reverse"
} else if ( normalised_antisense > 80 ) {
strandedness = "forward"
} else {
strandedness = "none"
}
"""
"""
}
///////////////////////////////////////////////////////////////////////////////
// ------------------------------------------------------------------------- //
// ------------------------------------------------------------------------- //
// ----------------------- ALIGNMENT SEQUENCING TYPE ---------------------- //
// ------------------------------------------------------------------------- //
// ------------------------------------------------------------------------- //
///////////////////////////////////////////////////////////////////////////////