271 lines
9.1 KiB
Plaintext
271 lines
9.1 KiB
Plaintext
nextflow.enable.dsl = 2
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OPTIONAL_FILE = file("$projectDir/data/OPTIONAL_FILE")
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process prepareAnnotationReference {
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label "wf_transcriptomes"
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cpus 1
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memory "6 GB"
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input:
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path ref_annotation
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tuple path(ref), path(ref_idx)
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output:
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stdout emit: warnings
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path "annotation.gtf", emit: annotation
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path "reference.fasta", emit: reference
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path "annotation_reference_summary.json", emit: summary
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path "unstranded_annotation.gtf", optional: true, emit: unstranded
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script:
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"""
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workflow-glue prepare_annotation_reference \
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--annotation "${ref_annotation}" \
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--reference "${ref}" \
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--out_dir prepared
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mv prepared/* .
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"""
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}
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process runJointBambu {
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label "wf_transcriptomes"
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cpus { params.threads ?: 4 }
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memory "32 GB"
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input:
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tuple val(aliases), path(bams, stageAs: "bams/??.bam"), path(bais, stageAs: "bams/??.bam.bai")
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path sample_sheet
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path annotation, stageAs: "annotation/*"
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path reference, stageAs: "reference/*"
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output:
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path "cohort", emit: dir
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path "cohort/transcripts.gtf", emit: gtf
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path "cohort/transcript_counts.tsv", emit: transcript_counts
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path "cohort/gene_counts.tsv", emit: gene_counts
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path "cohort/bambu_transcripts.rds", emit: transcript_rds
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path "cohort/bambu_genes.rds", emit: gene_rds
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path "cohort/transcript_metadata.tsv", emit: transcript_metadata
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script:
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def bam_list = bams instanceof Collection ? bams : [bams] // todo dont run joint on single sample anyway
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def alias_list = aliases instanceof Collection ? aliases : [aliases]
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String bams_arg = "--bams '${bam_list.join(",")}'"
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String aliases_arg = "--aliases '${alias_list.join(",")}'"
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String sample_sheet_arg = sample_sheet.name == OPTIONAL_FILE.name ? "" : "--sample_sheet ${sample_sheet}"
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String ndr_arg = params.ndr != null ? "--ndr ${params.ndr}" : ""
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"""
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supeRglue bambu \
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${bams_arg} \
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${aliases_arg} \
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${sample_sheet_arg} \
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--annotation "${annotation}" \
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--genome "${reference}" \
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--transcriptome_mode "${params.transcriptome_mode}" \
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--threads ${task.cpus} \
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${ndr_arg} \
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--out_dir cohort
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"""
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}
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process runPerSampleBambu {
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label "wf_transcriptomes"
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cpus { params.threads ?: 4 }
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memory "24 GB"
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input:
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tuple val(meta), path(bam), path(bai), path(stats)
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path annotation, stageAs: "annotation/*"
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path reference, stageAs: "reference/*"
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output:
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tuple val(meta), path("${meta.alias}"), emit: dir
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tuple val(meta), path("${meta.alias}/transcripts.gtf"), emit: gtf
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tuple val(meta), path("${meta.alias}/transcript_counts.tsv"), emit: transcript_counts
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tuple val(meta), path("${meta.alias}/gene_counts.tsv"), emit: gene_counts
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tuple val(meta), path("${meta.alias}/bambu_transcripts.rds"), emit: transcript_rds
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tuple val(meta), path("${meta.alias}/bambu_genes.rds"), emit: gene_rds
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tuple val(meta), path("${meta.alias}/transcript_metadata.tsv"), emit: transcript_metadata
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script:
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String bams_arg = "--bams '${bam.toString()}'"
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String aliases_arg = "--aliases '${meta.alias}'"
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String ndr_arg = params.ndr != null ? "--ndr ${params.ndr}" : ""
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"""
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supeRglue bambu \
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${bams_arg} \
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${aliases_arg} \
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--annotation "${annotation}" \
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--genome "${reference}" \
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--transcriptome_mode "${params.transcriptome_mode}" \
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--threads ${task.cpus} \
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${ndr_arg} \
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--out_dir "${meta.alias}"
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"""
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}
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process buildCohortTranscriptomeFasta {
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label "wf_transcriptomes"
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cpus 1
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memory "4 GB"
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input:
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path "transcripts.gtf"
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path reference
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output:
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path "cohort.transcriptome.fa", emit: fasta
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script:
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"""
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gffread -g "${reference}" -w cohort.transcriptome.fa transcripts.gtf
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"""
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}
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process buildSampleTranscriptomeFasta {
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label "wf_transcriptomes"
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cpus 1
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memory "4 GB"
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input:
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tuple val(meta), path("transcripts.gtf")
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path reference
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output:
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tuple val(meta), path("${meta.alias}.transcriptome.fa"), emit: fasta
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script:
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"""
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gffread -g "${reference}" -w "${meta.alias}.transcriptome.fa" transcripts.gtf
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"""
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}
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process runJointSqanti {
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label "wf_transcriptomes_sqanti"
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cpus { params.threads ?: 4 }
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memory "24 GB"
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input:
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path gtf
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path annotation, stageAs: "annotation/*"
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path reference, stageAs: "reference/*"
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output:
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path "sqanti_cohort", emit: dir
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path "sqanti_cohort/classification_summary.tsv", emit: summary
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script:
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String extra = params.sqanti_extra_args ?: ""
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String skip_orf = params.sqanti_skip_orf ? "--skipORF" : ""
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"""
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mkdir sqanti_cohort
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sqanti3_qc.py \
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--isoforms "${gtf}" \
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--refGTF "${annotation}" \
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--refFasta "${reference}" \
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${skip_orf} \
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--force_id_ignore \
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--report skip \
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-t ${task.cpus} \
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-d sqanti_cohort \
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-o cohort \
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${extra}
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workflow-glue summarise_sqanti --sqanti_dir sqanti_cohort \
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--output sqanti_cohort/classification_summary.tsv
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"""
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}
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process runPerSampleSqanti {
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label "wf_transcriptomes_sqanti"
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cpus { params.threads ?: 4 }
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memory "24 GB"
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input:
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tuple val(meta), path(gtf)
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path annotation, stageAs: "annotation/*"
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path reference, stageAs: "reference/*"
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output:
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tuple val(meta), path("${meta.alias}_sqanti"), emit: dir
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tuple val(meta), path("${meta.alias}_sqanti/classification_summary.tsv"), emit: summary
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script:
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String extra = params.sqanti_extra_args ?: ""
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String skip_orf = params.sqanti_skip_orf ? "--skipORF" : ""
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"""
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mkdir "${meta.alias}_sqanti"
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sqanti3_qc.py \
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--isoforms "${gtf}" \
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--refGTF "${annotation}" \
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--refFasta "${reference}" \
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${skip_orf} \
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--force_id_ignore \
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--report skip \
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-t ${task.cpus} \
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-d "${meta.alias}_sqanti" \
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-o "${meta.alias}" \
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${extra}
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workflow-glue summarise_sqanti --sqanti_dir "${meta.alias}_sqanti" \
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--output "${meta.alias}_sqanti/classification_summary.tsv"
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"""
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}
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workflow transcriptome_analysis {
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take:
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alignments
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ref_genome
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ref_annotation
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sample_sheet
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main:
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prepared_reference_annotation = prepareAnnotationReference(ref_annotation, ref_genome)
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prepared_reference_annotation.warnings.map { stdoutput ->
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if (stdoutput) {
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log.warn(stdoutput.trim())
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}
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}
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analysis_annotation = prepared_reference_annotation.annotation.first()
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analysis_reference = prepared_reference_annotation.reference.first()
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joint_bambu = runJointBambu(
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alignments
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| collect(flat: false)
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| map { rows ->
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// transform [meta, bam, bai] to [[alias1...aliasN], [bam1...bamN], [bai1...baiN]]
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tuple(
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rows.collect { it[0].alias },
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rows.collect { it[1] },
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rows.collect { it[2] }
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)
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},
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sample_sheet,
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analysis_annotation,
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analysis_reference
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)
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sample_bambu = runPerSampleBambu(alignments, analysis_annotation, analysis_reference)
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joint_fasta = buildCohortTranscriptomeFasta(joint_bambu.gtf, analysis_reference)
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sample_fastas = buildSampleTranscriptomeFasta(sample_bambu.gtf, analysis_reference)
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if (params.skip_sqanti) {
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joint_sqanti_dir = Channel.empty()
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sample_sqanti_dirs = Channel.empty()
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} else {
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joint_sqanti = runJointSqanti(joint_bambu.gtf, analysis_annotation, analysis_reference)
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sample_sqanti = runPerSampleSqanti(sample_bambu.gtf, analysis_annotation, analysis_reference)
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joint_sqanti_dir = joint_sqanti.dir
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sample_sqanti_dirs = sample_sqanti.dir
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}
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emit:
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annotation = ref_annotation
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annotation_reference_summary = prepared_reference_annotation.summary
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unstranded_annotation = prepared_reference_annotation.unstranded
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joint_dir = joint_bambu.dir
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joint_gtf = joint_bambu.gtf
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joint_fasta = joint_fasta.fasta
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joint_transcript_counts = joint_bambu.transcript_counts
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joint_gene_counts = joint_bambu.gene_counts
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joint_transcript_rds = joint_bambu.transcript_rds
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joint_gene_rds = joint_bambu.gene_rds
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joint_metadata = joint_bambu.transcript_metadata
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sample_dirs = sample_bambu.dir
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sample_gtf = sample_bambu.gtf
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sample_fastas = sample_fastas.fasta
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sample_transcript_counts = sample_bambu.transcript_counts
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sample_gene_counts = sample_bambu.gene_counts
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sample_transcript_rds = sample_bambu.transcript_rds
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sample_gene_rds = sample_bambu.gene_rds
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sample_metadata = sample_bambu.transcript_metadata
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joint_sqanti_dir = joint_sqanti_dir
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sample_sqanti_dirs = sample_sqanti_dirs
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}
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