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hash-cgMLST.nf
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hash-cgMLST.nf
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#!/usr/bin/env nextflow
// parameters
params.seqlist = "example_input.csv"
params.outputPath = "example_output"
params.krakendb = "minikraken2" //location of minikrakenDB
def firstFive( str ) {
return str.substring(0,5)
}
// initial logging
log.info "\n"
log.info "Spadeflow -- version 0.1"
log.info "Input sequence list : ${params.seqlist}"
log.info "Output path : ${params.outputPath}"
log.info "Container engine : ${workflow.containerEngine}"
log.info "\n"
// rename input parameters
outputPath = file(params.outputPath)
krakendb = file(params.krakendb)
//location for bbduk adapter sequences
bbduk_adapaters = "/opt/conda/opt/bbmap-38.22-1/resources/adapters.fa" //path within docker/singularity image
// set up initial channel based on CSV file
Channel
.fromPath(params.seqlist)
.splitCsv(header:true)
.map{ row-> tuple(row.file_type, row.file_name) }
.set { samples_ch }
process fetchReads {
input:
set file_type, file_name from samples_ch
output:
set file_name, file_type, file("*") into reads_ch
tag "$file_name"
executor = 'local'
script:
if (file_type=="bam") {
"""
scp -P 8081 ana:/mnt/microbio/ndm-hicf/ogre/pipeline_output/${file_name}/MAPPING/103e39d6-096c-46da-994d-91c5acbda565_R00000003/STD/${file_name}_v3.bam in.bam || scp -P 8081 ana:/mnt/microbio/ndm-hicf/ogre/pipeline_output/${file_name}/MAPPING/103e39d6-096c-46da-994d-91c5acbda565_R00000003/STD/${file_name}_v2.bam in.bam
"""
}
else if (file_type=="ebi") {
"""
${baseDir}/bin/download_ebi.py -a ${file_name} -o .
mv *_1.fastq.gz in.1.fq.gz
mv *_2.fastq.gz in.2.fq.gz
"""
}
}
process makeFastQ {
input:
set file_name, file_type, file("*") from reads_ch
output:
set file_name, file("in.1.fq.gz"), file("in.2.fq.gz") into fq_ch
tag "$file_name"
script:
if (file_type=="bam") {
"""
samtools sort -@${task.cpus} -n -o sorted.bam in.bam
bedtools bamtofastq -i sorted.bam \
-fq in.1.fq \
-fq2 in.2.fq
rm sorted.bam
gzip in.1.fq
gzip in.2.fq
"""
}
else {
"""
"""
}
}
//split raw reads into 3 channels - for QC and assembly and kraken2
fq_ch.into { fq_ch1; fq_ch2; fq_ch3}
process kraken2 {
input:
set file_name, file("in.1.fq.gz"), file("in.2.fq.gz") from fq_ch3
output:
file "*"
tag "$file_name"
publishDir "${outputPath}/${firstFive(file_name)}", mode: 'copy', pattern: "${file_name}*"
"""
kraken2 --report ${file_name}_kraken.txt --db ${krakendb} --paired in.1.fq.gz in.2.fq.gz > /dev/null
"""
}
process rawFastQC {
input:
set file_name, file("in.1.fq.gz"), file("in.2.fq.gz") from fq_ch1
output:
file "*"
tag "$file_name"
publishDir "${outputPath}/${firstFive(file_name)}", mode: 'copy', pattern: "${file_name}*"
"""
cat in.1.fq.gz in.2.fq.gz > ${file_name}.raw.fq.gz
fastqc --threads ${task.cpus} ${file_name}.raw.fq.gz > ${file_name}_raw_fastqc_log.txt
rm ${file_name}.raw.fq.gz
"""
}
//adapter trimming with bbDuk
process bbDuk {
input:
set file_name, file("in.1.fq.gz"), file("in.2.fq.gz") from fq_ch2
output:
set file_name, file("clean.1.fq.gz"), file("clean.2.fq.gz") into bbduk_out_ch
file("${file_name}_base_qual.txt")
file("${file_name}_length.txt")
tag "$file_name"
memory '8 GB' //not able to use 16GB standard
publishDir "${outputPath}/${firstFive(file_name)}", mode: 'copy', pattern: "${file_name}*"
"""
bbduk.sh in1=in.1.fq.gz in2=in.2.fq.gz out1=clean.1.fq out2=clean.2.fq \
ref=$bbduk_adapaters ktrim=r k=23 mink=11 hdist=1 tpe tbo \
qtrim=rl trimq=30 \
qchist=${file_name}_base_qual.txt \
lhist=${file_name}_length.txt \
-Xmx${task.memory.toGiga()}g threads=${task.cpus}
gzip clean.1.fq
gzip clean.2.fq
"""
}
//split cleaned reads into 2 channels - for QC and assembly
bbduk_out_ch.into { bbduk_out_ch1; bbduk_out_ch2; }
process cleanFastQC {
input:
set file_name, file("clean.1.fq.gz"), file("clean.2.fq.gz") from bbduk_out_ch1
output:
file "*"
tag "$file_name"
publishDir "${outputPath}/${firstFive(file_name)}", mode: 'copy', pattern: "${file_name}*"
"""
cat clean.1.fq.gz clean.2.fq.gz > ${file_name}.clean.fq.gz
fastqc --threads ${task.cpus} ${file_name}.clean.fq.gz > ${file_name}_clean_fastqc_log.txt
rm ${file_name}.clean.fq.gz
"""
}
process spades {
input:
set file_name, file("clean.1.fq.gz"), file("clean.2.fq.gz") from bbduk_out_ch2
output:
set file_name, file("${file_name}_spades_contigs.fa") into spades_out
tag "$file_name"
publishDir "${outputPath}/${firstFive(file_name)}", mode: 'copy', pattern: "${file_name}_*"
"""
spades.py --careful -o spades -1 clean.1.fq.gz -2 clean.2.fq.gz \
-t ${task.cpus} -m ${task.memory.toGiga()}
cp spades/contigs.fasta ${file_name}_spades_contigs.fa
cp spades/assembly_graph.fastg ${file_name}_spades_assembly_graph.fastg
cp spades/assembly_graph_with_scaffolds.gfa ${file_name}_spades_assembly_graph_with_scaffolds.gfa
cp spades/spades.log ${file_name}_spades.log
#remove spades directory to save space
rm -rf spades*
"""
}
//split assembly into 2 channels - for cgmlst and mslt
spades_out.into { spades_out_ch1; spades_out_ch2; }
process cgmlst {
input:
set file_name, file("${file_name}_spades_contigs.fa") from spades_out_ch1
output:
file "${file_name}_cgmlst.*"
tag "$file_name"
publishDir "${outputPath}/${firstFive(file_name)}", mode: 'copy', pattern: "${file_name}_cgmlst.*"
"""
#get stats
/opt/conda/opt/bbmap-38.22-1/stats.sh in=${file_name}_spades_contigs.fa > ${file_name}_cgmlst.stats
/opt/conda/opt/bbmap-38.22-1/statswrapper.sh in=${file_name}_spades_contigs.fa > ${file_name}_cgmlst.statlog
#run hash cgmlst
${baseDir}/bin/getCoreGenomeMLST.py -f ${file_name}_spades_contigs.fa \
-n ${file_name} \
-s ${baseDir}/ridom_scheme/files \
-d ${baseDir}/ridom_scheme/ridom_scheme.fasta \
-o ${file_name} \
-b blastn
"""
}
process mlst {
input:
set file_name, file("${file_name}_spades_contigs.fa") from spades_out_ch2
output:
file "${file_name}_mlst.txt"
tag "$file_name"
publishDir "${outputPath}/${firstFive(file_name)}", mode: 'copy', pattern: "${file_name}_mlst.txt"
"""
mlst --scheme cdifficile --legacy ${file_name}_spades_contigs.fa > ${file_name}_mlst.txt
"""
}