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#!/usr/bin/env nextflow
/*
========================================================================================
nf-core/pikavirus
========================================================================================
nf-core/pikavirus Analysis Pipeline.
#### Homepage / Documentation
https://github.com/nf-core/pikavirus
----------------------------------------------------------------------------------------
*/
log.info Headers.nf_core(workflow, params.monochrome_logs)
println(params.outdir)
////////////////////////////////////////////////////
/* -- PRINT HELP -- */
////////////////////////////////////////////////////+
def json_schema = "$projectDir/nextflow_schema.json"
if (params.help) {
def command = "nextflow run nf-core/pikavirus --input samplesheet.csv -profile docker"
log.info NfcoreSchema.params_help(workflow, params, json_schema, command)
exit 0
}
////////////////////////////////////////////////////
/* -- VALIDATE PARAMETERS -- */
////////////////////////////////////////////////////+
if (params.validate_params) {
NfcoreSchema.validateParameters(params, json_schema, log)
}
////////////////////////////////////////////////////
/* -- Collect configuration parameters -- */
////////////////////////////////////////////////////
// Check AWS batch settings
if (workflow.profile.contains('awsbatch')) {
// AWSBatch sanity checking
if (!params.awsqueue || !params.awsregion) exit 1, 'Specify correct --awsqueue and --awsregion parameters on AWSBatch!'
// Check outdir paths to be S3 buckets if running on AWSBatch
// related: https://github.com/nextflow-io/nextflow/issues/813
if (!params.outdir.startsWith('s3:')) exit 1, 'Outdir not on S3 - specify S3 Bucket to run on AWSBatch!'
// Prevent trace files to be stored on S3 since S3 does not support rolling files.
if (params.tracedir.startsWith('s3:')) exit 1, 'Specify a local tracedir or run without trace! S3 cannot be used for tracefiles.'
}
// Stage config files
ch_multiqc_config = file("$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) { ch_input = file(params.input, checkIfExists: true) } else { exit 1, "Samplesheet file (-input) not specified!" }
////////////////////////////////////////////////////
/* -- PRINT PARAMETER SUMMARY -- */
////////////////////////////////////////////////////
log.info NfcoreSchema.params_summary_log(workflow, params, json_schema)
// Header log info
def summary = [:]
if (workflow.revision) summary['Pipeline Release'] = workflow.revision
summary['Run Name'] = workflow.runName
summary['Input'] = params.input
summary['Trimming'] = params.trimming
if (params.remove_control) summary['Sequencing control'] = params.control_sequence
summary['Kraken scouting'] = params.kraken_scouting
if (params.kraken_scouting) summary['Kraken database'] = params.kraken2_db
summary['Kaiju discovery'] = params.kaiju
if (params.translated_analysis) summary ['Kaiju database'] = params.kaiju_db
summary['Virus Search'] = params.virus
if (params.virus) summary['Virus Ref'] = params.vir_ref_dir
if (params.virus) summary['Virus Index File'] = params.vir_dir_repo
summary['Bacteria Search'] = params.bacteria
if (params.bacteria) summary['Bacteria Ref'] = params.bact_ref_dir
if (params.bacteria) summary['Bacteria Index File'] = params.bact_dir_repo
summary['Fungi Search'] = params.fungi
if (params.fungi) summary['Fungi Ref'] = params.fungi_ref_dir
if (params.fungi) summary['Fungi Index File'] = params.fungi_dir_repo
summary['Mash kmer size'] = params.mash_kmer_size
summary['Mash hash amount'] = params.mash_hash_amount
summary['Mash winner strategy'] = params.mash_winner_strategy
summary['Mash identity threshold'] = params.mash_identity_threshold
summary['Mash min shared hashes'] = params.mash_min_shared_hashes
summary['Mash pvalue threshold '] = params.mash_pvalue_threshold
summary['Skip phage-named assemblies from mapping'] = params.skip_phage_assemblies
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-pikavirus-summary'
description: " - this information is collected when the pipeline is started."
section_name: 'nf-core/pikavirus Workflow Summary'
section_href: 'https://github.com/nf-core/pikavirus'
plot_type: 'html'
data: |
<dl class=\"dl-horizontal\">
$x
</dl>
""".stripIndent() }
.set { ch_workflow_summary }
/*
* Parse software version numbers
*/
println(params.outdir)
process get_software_versions {
errorStrategy 'ignore'
publishDir "${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 $workflow.nextflow.version > v_nextflow.txt
fastqc --version &> v_fastqc.txt &
fastp --version 2> v_fastp.txt
bowtie2 --version > v_bowtie2.txt
mash --version &> v_mash.txt &
samtools --version | head -n 1 > v_samtools.txt
bedtools --version > v_bedtools.txt
kraken2 --version > v_kraken2.txt
# spades.py -v &> v_spades.txt &
# quast -v &> v_quast.txt &
# kaiju -help &> tmp &
# head -n 1 tmp > v_kaiju.txt
ivar -v | head -n 1 > v_ivar.txt
muscle -version > v_muscle.txt
scrape_software_versions.py &> software_versions_mqc.yaml
"""
}
process CHECK_SAMPLESHEET {
tag "$samplesheet"
publishDir "${params.outdir}", mode: params.publish_dir_mode,
saveAs: { filename ->
if (filename.endsWith(".tsv")) "preprocess/sra/$filename"
else "pipeline_info/$filename"
}
input:
path(samplesheet) from ch_input
output:
path "samplesheet.valid.csv" into ch_samplesheet_reformat
path "sra_run_info.tsv" optional true
script: // These scripts are bundled with the pipeline, in nf-core/viralrecon/bin/
run_sra = !params.skip_sra && !isOffline()
"""
awk -F, '{if(\$1 != "" && \$2 != "") {print \$0}}' $samplesheet > nonsra_id.csv
check_samplesheet.py nonsra_id.csv nonsra.samplesheet.csv
awk -F, '{if(\$1 != "" && \$2 == "" && \$3 == "") {print \$1}}' $samplesheet > sra_id.list
if $run_sra && [ -s sra_id.list ]
then
fetch_sra_runinfo.py sra_id.list sra_run_info.tsv --platform ILLUMINA --library_layout SINGLE,PAIRED
sra_runinfo_to_samplesheet.py sra_run_info.tsv sra.samplesheet.csv
fi
if [ -f nonsra.samplesheet.csv ]
then
head -n 1 nonsra.samplesheet.csv > samplesheet.valid.csv
else
head -n 1 sra.samplesheet.csv > samplesheet.valid.csv
fi
tail -n +2 -q *sra.samplesheet.csv >> samplesheet.valid.csv
"""
}
// Function to get list of [ sample, single_end?, is_sra?, is_ftp?, [ fastq_1, fastq_2 ], [ md5_1, md5_2] ]
def validate_input(LinkedHashMap sample) {
def sample_id = sample.sample_id
def single_end = sample.single_end.toBoolean()
def is_sra = sample.is_sra.toBoolean()
def is_ftp = sample.is_ftp.toBoolean()
def fastq_1 = sample.fastq_1
def fastq_2 = sample.fastq_2
def md5_1 = sample.md5_1
def md5_2 = sample.md5_2
def array = []
if (!is_sra) {
if (single_end) {
array = [ sample_id, single_end, is_sra, is_ftp, [ file(fastq_1, checkIfExists: true) ] ]
} else {
array = [ sample_id, single_end, is_sra, is_ftp, [ file(fastq_1, checkIfExists: true), file(fastq_2, checkIfExists: true) ] ]
}
} else {
array = [ sample_id, single_end, is_sra, is_ftp, [ fastq_1, fastq_2 ], [ md5_1, md5_2 ] ]
}
return array
}
/*
* Create channels for input fastq files
*/
ch_samplesheet_reformat
.splitCsv(header:true, sep:',')
.map { validate_input(it) }
.into { ch_reads_all
ch_reads_sra }
/*
* Download and check SRA data
*/
if (!params.skip_sra || !isOffline()) {
ch_reads_sra
.filter { it[2] }
.into { ch_reads_sra_ftp
ch_reads_sra_dump }
process SRA_FASTQ_FTP {
tag "$sample"
label 'process_medium'
errorStrategy 'retry'
publishDir "${params.outdir}/preprocess/sra", mode: params.publish_dir_mode,
saveAs: { filename ->
if (filename.endsWith(".md5")) "md5/$filename"
else params.save_sra_fastq ? filename : null
}
when:
is_ftp
input:
tuple val(sample), val(single_end), val(is_sra), val(is_ftp), val(fastq), val(md5) from ch_reads_sra_ftp
output:
tuple val(sample), val(single_end), val(is_sra), val(is_ftp), path("*.fastq.gz") into ch_sra_fastq_ftp
script:
if (single_end) {
"""
curl -L ${fastq[0]} -o ${sample}.fastq.gz
echo "${md5[0]} ${sample}.fastq.gz" > ${sample}.fastq.gz.md5
md5sum -c ${sample}.fastq.gz.md5
"""
} else {
"""
curl -L ${fastq[0]} -o ${sample}_1.fastq.gz
echo "${md5[0]} ${sample}_1.fastq.gz" > ${sample}_1.fastq.gz.md5
md5sum -c ${sample}_1.fastq.gz.md5
curl -L ${fastq[1]} -o ${sample}_2.fastq.gz
echo "${md5[1]} ${sample}_2.fastq.gz" > ${sample}_2.fastq.gz.md5
md5sum -c ${sample}_2.fastq.gz.md5
"""
}
}
process SRA_FASTQ_DUMP {
tag "$sample"
label 'process_medium'
errorStrategy 'retry'
publishDir "${params.outdir}/preprocess/sra", mode: params.publish_dir_mode,
saveAs: { filename ->
if (filename.endsWith(".log")) "log/$filename"
else params.save_sra_fastq ? filename : null
}
when:
!is_ftp
input:
tuple val(sample), val(single_end), val(is_sra), val(is_ftp) from ch_reads_sra_dump.map { it[0..3] }
output:
tuple val(sample), val(single_end), val(is_sra), val(is_ftp), path("*.fastq.gz") into ch_sra_fastq_dump
path "*.log"
script:
prefix = "${sample.split('_')[0..-2].join('_')}"
pe = single_end ? "" : "--readids --split-e"
rm_orphan = single_end ? "" : "[ -f ${prefix}.fastq.gz ] && rm ${prefix}.fastq.gz"
"""
parallel-fastq-dump \\
--sra-id $prefix \\
--threads $task.cpus \\
--outdir ./ \\
--tmpdir ./ \\
--gzip \\
$pe \\
> ${prefix}.fastq_dump.log
$rm_orphan
"""
}
ch_reads_all
.filter { !it[2] }
.concat(ch_sra_fastq_ftp, ch_sra_fastq_dump)
.set { ch_reads_all }
}
ch_reads_all
.map { [ it[0].split('_')[0..-2].join('_'), it[1], it[4] ] }
.groupTuple(by: [0, 1])
.map { [ it[0], it[1], it[2].flatten() ] }
.set { ch_reads_all }
/*
* Merge FastQ files with the same sample identifier (resequenced samples)
*/
process CAT_FASTQ {
tag "$sample"
input:
tuple val(sample), val(single_end), path(reads) from ch_reads_all
output:
tuple val(sample), val(single_end), path("*.merged.fastq.gz") into ch_cat_fastqc,
ch_cat_fortrim
val(sample) into samplechannel_translated,
samplechannel_trim_fastqc,
samplechannel_trimmed_fastqc,
samplechannel_krona,
control_results_template,
virus_results_template,
bacteria_results_template,
fungi_results_template
tuple val(sample), val(single_end) into sample_pe_template
script:
readList = reads.collect{it.toString()}
if (!single_end) {
if (readList.size > 2) {
def read1 = []
def read2 = []
readList.eachWithIndex{ v, ix -> ( ix & 1 ? read2 : read1 ) << v }
"""
cat ${read1.sort().join(' ')} > ${sample}_1.merged.fastq.gz
cat ${read2.sort().join(' ')} > ${sample}_2.merged.fastq.gz
"""
} else {
"""
ln -s ${reads[0]} ${sample}_1.merged.fastq.gz
ln -s ${reads[1]} ${sample}_2.merged.fastq.gz
"""
}
} else {
if (readList.size > 1) {
"""
cat ${readList.sort().join(' ')} > ${sample}.merged.fastq.gz
"""
} else {
"""
ln -s $reads ${sample}.merged.fastq.gz
"""
}
}
}
/*
* PREPROCESSING: KAIJU DATABASE
*/
if (params.kaiju && params.translated_analysis) {
if (params.kaiju_db.endsWith('.gz') || params.kaiju_db.endsWith('.tar') || params.kaiju_db.endsWith('.tgz')){
process UNCOMPRESS_KAIJUDB {
errorStrategy 'retry'
input:
path(database) from params.kaiju_db
output:
path("kaijudb") into kaiju_db
script:
"""
mkdir "kaijudb"
tar -zxf $database -C "kaijudb"
"""
}
} else {
kaiju_db = Channel.fromPath(params.kaiju_db)
}
}
/*
* STEP 1.1 - FastQC
*/
process RAW_SAMPLES_FASTQC {
tag "$samplename"
label "process_medium"
publishDir "${params.outdir}/${samplename}/raw_fastqc", mode: params.publish_dir_mode,
saveAs: { filename ->
filename.indexOf(".zip") > 0 ? "zips/$filename" : "$filename"
}
input:
set val(samplename), val(single_end), path(reads) from ch_cat_fastqc
output:
tuple val(samplename), path("*_fastqc.{zip,html}")
tuple val(samplename), path("*_fastqc.zip") into raw_fastqc_multiqc
path("*_fastqc.zip") into raw_fastqc_multiqc_global
script:
"""
fastqc --quiet --threads $task.cpus $reads
"""
}
/*
* STEP 1.2 - TRIMMING
*/
if (params.trimming) {
process FASTP_TRIM {
tag "$samplename"
label "process_medium"
publishDir "${params.outdir}/${samplename}", mode: params.publish_dir_mode,
saveAs: { filename ->
if (filename.endsWith(".fastq") && params.rescue_trimmed) "trimmed_sequences/$filename"
else if (filename.endsWith(".html")) filename
}
input:
tuple val(samplename), val(single_end), path(reads) from ch_cat_fortrim
output:
tuple val(samplename), val(single_end), path("*fail.fastq.gz")
tuple val(samplename), val(single_end), path("*trim.fastq.gz") into trimmed_paired_fastqc, trimmed_remove_control
tuple val(samplename), path("*.json") into fastp_multiqc
tuple val(samplename), path("*.html") into fastp_report
path("*.json") into fastp_multiqc_global
script:
detect_adapter = single_end ? "" : "--detect_adapter_for_pe"
reads1 = single_end ? "--in1 ${reads} --out1 ${samplename}_trim.fastq.gz --failed_out ${samplename}_fail.fastq.gz" : "--in1 ${reads[0]} --out1 ${samplename}_1_trim.fastq.gz --unpaired1 ${samplename}_1_fail.fastq.gz"
reads2 = single_end ? "" : "--in2 ${reads[1]} --out2 ${samplename}_2_trim.fastq.gz --unpaired2 ${samplename}_2_fail.fastq.gz"
"""
fastp \\
$detect_adapter \\
--cut_front \\
--cut_tail \\
--length_required 35 \\
--thread $task.cpus \\
--json ${samplename}_trim_fastp.json \\
$reads1 \\
$reads2
"""
}
/*
* STEP 1.3 - FastQC on trimmed reads
*/
process TRIMMED_SAMPLES_FASTQC {
tag "$samplename"
label "process_medium"
publishDir "${params.outdir}/${samplename}/trimmed_fastqc", mode: params.publish_dir_mode
input:
tuple val(samplename), val(single_end), path(reads) from trimmed_paired_fastqc
output:
tuple val(samplename), path("*_fastqc.{zip,html}")
tuple val(samplename), path("*_fastqc.zip") into trimmed_fastqc_multiqc
path("*_fastqc.zip") into trimmed_fastqc_multiqc_global
script:
"""
fastqc --quiet --threads $task.cpus $reads
"""
}
if (params.remove_control) {
Channel.fromPath(params.control_sequence).set { control_genome }
process BOWTIE2_REMOVE_SEQUENCING_CONTROL {
tag "$samplename"
label "process_high"
input:
tuple val(samplename), val(single_end), path(reads), path(control_sequence) from trimmed_remove_control.combine(control_genome)
output:
tuple val(samplename), val(single_end), path("*_mapped_sorted.bam") into control_alignment
tuple val(samplename), val(single_end), path("*.fastq.gz") into trimmed_virus, trimmed_bact, trimmed_fungi,
reads_for_assembly, trimmed_skip_hostremoval,
trimmed_map_virus, trimmed_map_bact, trimmed_map_fungi,
trimmed_kraken2
script:
samplereads = single_end ? "-U ${reads}" : "-1 ${reads[0]} -2 ${reads[1]}"
unmapped = single_end ? "--un-gz ${samplename}_unmapped.fastq.gz" : "--un-conc-gz ${samplename}_unmapped_R%.fastq.gz"
"""
bowtie2-build \\
--seed 1 \\
--threads $task.cpus \\
$control_sequence \\
"control_sequence"
bowtie2 \\
--threads $task.cpus \\
-x "control_sequence" \\
$unmapped \\
$samplereads | samtools view \\
-@ $task.cpus \\
-b \\
-h \\
-O BAM \\
-o "${control_sequence}_mapped.bam"
samtools sort \\
-@ $task.cpus \\
-o "${control_sequence}_mapped_sorted.bam" \\
"${control_sequence}_mapped.bam"
"""
}
process SAMTOOLS_CONTROL {
tag "$samplename"
label "process_medium"
input:
tuple val(samplename), val(single_end), path(sortedbam) from control_alignment
output:
tuple val(samplename), val(single_end), path(sortedbam), path("*idxstats"), path("*flagstat") into control_alignment_bams
script:
prefix = sortedbam.join().minus("_mapped_sorted.bam")
"""
samtools index $sortedbam
samtools idxstats $sortedbam > "${prefix}.sorted.bam.idxstats"
samtools flagstat -O tsv $sortedbam > "${prefix}.sorted.bam.flagstat"
"""
}
process BEDTOOLS_SEQUENCING_CONTROL {
tag "$samplename"
label "process_medium"
input:
tuple val(samplename), val(single_end), path(mapped), path(idxstat), path(flagstat) from control_alignment_bams
output:
tuple val(samplename), path("*_coverage.txt"), path(idxstat), path(flagstat) into coverage_stats_control
script:
prefix = mapped.join().minus("_mapped_sorted.bam")
"""
bedtools genomecov -ibam $mapped > "${prefix}_coverage.txt"
"""
}
process COVERAGE_STATS_SEQUENCING_CONTROL {
tag "$samplename"
label "process_medium"
input:
tuple val(samplename), path(coveragefile), path(idxstat), path(flagstat) from coverage_stats_control
output:
tuple val(samplename), path("*.tsv") into control_coverage_results
script:
"""
coverage_analysis_control.py $samplename $coveragefile $idxstat $flagstat
"""
}
} else {
trimmed_remove_control.into { trimmed_virus
trimmed_bact
trimmed_fungi
reads_for_assembly
trimmed_skip_hostremoval
trimmed_map_virus
trimmed_map_bact
trimmed_map_fungi
trimmed_kraken2 }
nofile_path_control_coverage = Channel.fromPath("NONE_control_coverage")
control_results_template.combine(nofile_path_control_coverage).set { control_coverage_results }
}
} else {
ch_cat_fortrim.into { trimmed_virus
trimmed_bact
trimmed_fungi
reads_for_assembly
trimmed_skip_hostremoval
trimmed_map_virus
trimmed_map_bact
trimmed_map_fungi }
trimmed_fastqc_multiqc_global = Channel.fromPath("NONE_trimmedfastqc_global")
fastp_multiqc_global = Channel.fromPath("NONE_fastp_global")
nofile_path_trimmed_fastqc = Channel.fromPath("NONE_trimmedfastqc")
nofile_path_fastp = Channel.fromPath("NONE_fastp")
nofile_path_control_coverage = Channel.fromPath("NONE_control_coverage")
control_results_template.combine(nofile_path_control_coverage).set { control_coverage_results }
samplechannel_trim_fastqc.combine(nofile_path_fastp).set { fastp_multiqc }
samplechannel_trimmed_fastqc.combine(nofile_path_trimmed_fastqc).set { trimmed_fastqc_multiqc }
}
if (params.kraken_scouting || params.translated_analysis) {
if (params.kraken2_db.endsWith('.gz') || params.kraken2_db.endsWith('.tar') || params.kraken2_db.endsWith('.tgz')) {
Channel.fromPath(params.kraken2_db).set { kraken2_compressed }
process UNCOMPRESS_KRAKEN2DB {
errorStrategy 'retry'
input:
path(database) from kraken2_compressed
output:
path("kraken2db") into kraken2_db_files
script:
"""
tar -zxf $database
if [ -f "hash.k2d" ];
then
mkdir kraken2db
mv *.k2d kraken2db
mv *.kmer_distrib kraken2db
mv seqid2taxid.map kraken2db
mv inspect.txt kraken2db
mv README_assembly_summary.txt kraken2db
else
mv */ kraken2db
fi
"""
}
} else {
Channel.fromPath(params.kraken2_db).set { kraken2_db_files }
}
process SCOUT_KRAKEN2 {
tag "$samplename"
label "process_high"
input:
tuple val(samplename), val(single_end), path(reads), path(kraken2db) from trimmed_kraken2.combine(kraken2_db_files)
output:
tuple val(samplename), path("*.report")
tuple val(samplename), path("*.krona") into kraken2_krona
tuple val(samplename), path("*.report"), path("*.kraken") into kraken2_host
tuple val(samplename), val(single_end), file("*_unclassified.fastq") into unclassified_reads
script:
paired_end = single_end ? "" : "--paired"
unclass_name = single_end ? "${samplename}_unclassified.fastq" : "${samplename}_#_unclassified.fastq"
"""
kraken2 --db $kraken2db \\
${paired_end} \\
--threads $task.cpus \\
--report ${samplename}.report \\
--output ${samplename}.kraken \\
--unclassified-out ${unclass_name} \\
${reads}
cat ${samplename}.kraken | cut -f 2,3 > results.krona
"""
}
if (params.kraken_scouting) {
process KRONA_DB {
errorStrategy 'retry'
output:
path("taxonomy/") into krona_taxonomy_db_kraken
script:
"""
ktUpdateTaxonomy.sh taxonomy
"""
}
process KRONA_KRAKEN_RESULTS {
tag "$samplename"
label "process_medium"
publishDir "${params.outdir}/${samplename}/kraken2_krona_results", mode: params.publish_dir_mode
input:
tuple val(samplename), path(kronafile), path(taxonomy) from kraken2_krona.combine(krona_taxonomy_db_kraken)
output:
tuple val(samplename), path("*.krona.html") into krona_scouting_results
script:
outfile = "${samplename}_kraken.krona.html"
"""
ktImportTaxonomy $kronafile -tax $taxonomy -o $outfile
"""
}
}
if (params.host_removal) {
process REMOVE_HOST_KRAKEN2 {
tag "$samplename"
label "process_medium"
input:
tuple val(samplename), val(single_end), path(reads), path(report), path(output) from trimmed_paired_extract_host.join(kraken2_host_extraction)
output:
tuple val(samplename), val(single_end), path("*_host_extracted.fastq") into reads_for_assembly
script:
read = single_end ? "-s ${reads}" : "-s1 ${reads[0]} -s2 ${reads[1]}"
outputfile = single_end ? "--output $mergedfile" : "-o ${samplename}_1_host_extracted.fastq -o2 ${samplename}_2_host_extracted.fastq"
mergedfile = single_end ? "${samplename}_host_extracted.fastq": "${samplename}_merged.fastq"
merge_outputfile = single_end ? "" : "cat *_host_extracted.fastq > $mergedfile"
"""
extract_kraken_reads.py \\
-k $output \\
-r $report \\
--exclude \\
--taxid ${params.host_taxid} \\
--fastq-output \\
$read \\
$outputfile
$merge_outputfile
"""
}
} else {
trimmed_skip_hostremoval.set { reads_for_assembly }
}
} else {
Channel.fromPath("NONE_krona").set { nofile_path_krona }
samplechannel_krona.combine(nofile_path_krona).set { krona_scouting_results }
}
if (params.virus) {
Channel.fromPath(params.vir_dir_repo).into { virus_datasheet_coverage
virus_datasheet_len
virus_datasheet_selection
virus_datasheet_group_by_species }
if (params.vir_ref_dir.endsWith('.gz') || params.vir_ref_dir.endsWith('.tar') || params.vir_ref_dir.endsWith('.tgz')) {
process UNCOMPRESS_VIRUS_REF {
errorStrategy 'retry'
input:
path(ref_vir) from params.vir_ref_dir
output:
path("viralrefs") into virus_ref_directory, virus_references
script:
"""
mkdir "viralrefs"
tar -xvf $ref_vir --strip-components=1 -C "viralrefs"
"""
}
} else {
Channel.fromPath(params.vir_ref_dir).into { virus_ref_directory
virus_references }
}
process MASH_GENERATE_REFERENCE_SKETCH_VIRUS {
label "process_high"
input:
path(ref) from virus_ref_directory
output:
path("*.msh") into reference_sketch_virus
script:
"""
find ${ref}/ -name "*" -type f > reference_list.txt
mash sketch -k $params.mash_kmer_size -s $params.mash_hash_amount -o reference -l reference_list.txt
"""
}
process MASH_DETECT_VIRUS_REFERENCES {
tag "$samplename"
label "process_high"
publishDir "${params.outdir}/mash_results", mode: params.publish_dir_mode
input:
tuple val(samplename), val(single_end), path(reads), path(refsketch) from trimmed_virus.combine(reference_sketch_virus)
output:
tuple val(samplename), path(mashout) into mash_result_virus_references
script:
mashout = "mash_screen_results_virus_${samplename}.txt"
winstrat = params.mash_winner_strategy ? "-w" : ""
"""
echo -e "#Identity\tShared_hashes\tMedian_multiplicity\tP-value\tQuery_id\tQuery_comment" > $mashout
mash screen $winstrat $refsketch $reads >> $mashout
"""
}
process SELECT_FINAL_VIRUS_REFERENCES {
tag "$samplename"
label "process_low"
publishDir "${params.outdir}/${samplename}/virus_coverage", mode: params.publish_dir_mode,
saveAs: { filename ->
if (filename.endsWith(".tsv")) filename
}
input:
tuple val(samplename), path(mashresult), path(refdir), path(datasheet_virus) from mash_result_virus_references.combine(virus_references).combine(virus_datasheet_selection)
output:
tuple val(samplename), path("Final_fnas/*") optional true into bowtie_virus_references
tuple val(samplename), path("not_found.tsv") optional true into failed_virus_samples
path("skipped_assemblies.tsv") optional true
script:
skip_phage = params.skip_phage_assemblies ? "--skip-phage-assemblies" : ""
skipped_outfile_name = "${samplename}_skipped_assemblies"
"""
extract_significative_references.py \\
--mash-result $mashresult \\
--refdir $refdir \\
--ref-sheet $datasheet_virus \\
--identity-threshold $params.mash_identity_threshold \\
--shared-hashes-threshold $params.mash_min_shared_hashes \\
--p-value-threshold $params.mash_pvalue_threshold \\
--skipped-outfile-name $skipped_outfile_name \\
$skip_phage
"""
}
trimmed_map_virus.join(bowtie_virus_references).set { bowtie_virus_channel }
// Channel is: [ val(samplesheet), path(reads), path(a lot of files) ]
// the following code turns it into [ val(samplesheet), path (reads), path(only one single file)]
def rawlist_virus = bowtie_virus_channel.toList().get()
def bowtielist_virus = []
for (line in rawlist_virus) {
if (line[3] instanceof java.util.ArrayList){
last_list = line[3]
}
else {
last_list = [line[3]]
}
for (reference in last_list) {
def ref_slice = [line[0],line[1],line[2],reference]
bowtielist_virus.add(ref_slice)
}
}
def reads_virus_mapping = Channel.fromList(bowtielist_virus)
process BOWTIE2_MAPPING_VIRUS {
tag "${samplename} : ${reference_sequence}"
label "process_high"
input:
tuple val(samplename), val(single_end), path(reads), path(reference_sequence) from reads_virus_mapping
output:
tuple val(samplename), path(reference_sequence), val(single_end), path("*sorted.bam") into bowtie_alingment_bam_virus, bowtie_alingment_bam_virus_ivar, bowtie_alignment_bam_virus_uniqreads
tuple val(samplename), val(single_end), path("*sorted.bam"), path(reference_sequence) into ivar_virus
script:
samplereads = single_end ? "-U ${reads}" : "-1 ${reads[0]} -2 ${reads[1]}"
prefix = "${reference_sequence}_vs_${samplename}_virus"
"""
bowtie2-build \\
--seed 1 \\
--threads $task.cpus \\
$reference_sequence \\
"index"
bowtie2 \\
--threads $task.cpus \\
-x "index" \\
$samplereads | samtools view \\
-@ $task.cpus \\
-b \\
-h \\
-O BAM \\
-o "${prefix}.bam"
samtools sort \\
-@ $task.cpus \\
-o "${prefix}.sorted.bam" \\
"${prefix}.bam"
"""
}
process SAMTOOLS_VIRUS {
tag "${samplename} : ${reference_sequence}"
label "process_medium"
input:
tuple val(samplename), path(reference_sequence), val(single_end), path(sortedbam) from bowtie_alingment_bam_virus_ivar
output:
tuple val(samplename), val(single_end), path("*.flagstat"), path("*.idxstats"), path("*.stats")
script:
prefix = sortedbam.join()
"""
samtools index $sortedbam
samtools flagstat -O tsv $sortedbam > "${prefix}.flagstat"
samtools idxstats $sortedbam > "${prefix}.idxstats"
samtools stats $sortedbam > "${prefix}.stats"
"""
}
process IVAR_CONSENSUS_VIRUS {
tag "${samplename} : ${prefix}"
label "process_medium"
publishDir "${params.outdir}/${samplename}/virus_consensus"
input: