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add bait regions to deepvariant for WES #633

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merged 5 commits into from
Oct 16, 2024
Merged

add bait regions to deepvariant for WES #633

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386302d
add bait regions to deepvariant
ramprasadn Oct 14, 2024
4b1b05f
update changelog
ramprasadn Oct 14, 2024
7e2d68a
Update CHANGELOG.md
ramprasadn Oct 15, 2024
d4f60d9
update schema
ramprasadn Oct 16, 2024
7e0cad7
Merge branch 'deepvar-for-regions' of github.com:nf-core/raredisease …
ramprasadn Oct 16, 2024
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1 change: 1 addition & 0 deletions CHANGELOG.md
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Expand Up @@ -18,6 +18,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0

### `Fixed`

- Restrict deepvariant analysis of WES samples to bait regions [#633](https://github.com/nf-core/raredisease/pull/633)
- bcftools annotate declaration in annotate CADD subworkflow [#624](https://github.com/nf-core/raredisease/pull/624)
- Rhocallviz subworkflow will only be invocated once per sample [#621](https://github.com/nf-core/raredisease/pull/621)
- Allow for VEP version 112 to be used and set it to default [#617](https://github.com/nf-core/raredisease/pull/617)
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2 changes: 1 addition & 1 deletion nextflow_schema.json
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Expand Up @@ -698,7 +698,7 @@
"type": "string",
"format": "path",
"fa_icon": "fas fa-align-center",
"description": "Interval in the reference that will be used in the software"
"description": "Interval in the reference that will be used in the software. Used only by sentieon."
},
"cnvnator_binsize": {
"type": "integer",
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2 changes: 2 additions & 0 deletions subworkflows/local/call_snv.nf
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Expand Up @@ -30,6 +30,7 @@ workflow CALL_SNV {
ch_dbsnp // channel: [optional] [ val(meta), path(vcf) ]
ch_dbsnp_tbi // channel: [optional] [ val(meta), path(tbi) ]
ch_call_interval // channel: [mandatory] [ path(intervals) ]
ch_bait_intervals // channel: [mandatory] [ path(intervals) ]
ch_ml_model // channel: [mandatory] [ path(model) ]
ch_par_bed // channel: [optional] [ val(meta), path(bed) ]
ch_case_info // channel: [mandatory] [ val(case_info) ]
Expand All @@ -54,6 +55,7 @@ workflow CALL_SNV {
ch_genome_bam_bai,
ch_genome_fasta,
ch_genome_fai,
ch_bait_intervals,
ch_par_bed,
ch_case_info,
ch_foundin_header,
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76 changes: 38 additions & 38 deletions subworkflows/local/prepare_references.nf
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Expand Up @@ -33,15 +33,15 @@ include { UNTAR as UNTAR_VEP_CACHE } from '../../modul

workflow PREPARE_REFERENCES {
take:
ch_genome_fasta // channel: [mandatory] [ val(meta), path(fasta) ]
ch_genome_fai // channel: [mandatory] [ val(meta), path(fai) ]
ch_genome_dictionary // channel: [mandatory] [ val(meta), path(fai) ]
ch_mt_fasta // channel: [mandatory for dedicated mt analysis] [ val(meta), path(fasta) ]
ch_gnomad_af_tab // channel: [optional; used in for snv annotation] [ val(meta), path(tab) ]
ch_known_dbsnp // channel: [optional; used only by sentieon] [ val(meta), path(vcf) ]
ch_target_bed // channel: [mandatory for WES] [ path(bed) ]
ch_vcfanno_extra_unprocessed // channel: [mandatory] [ val(meta), path(vcf) ]
ch_vep_cache // channel: [mandatory for annotation] [ path(cache) ]
ch_genome_fasta // channel: [mandatory] [ val(meta), path(fasta) ]
ch_genome_fai // channel: [mandatory] [ val(meta), path(fai) ]
ch_genome_dictionary // channel: [mandatory] [ val(meta), path(fai) ]
ch_mt_fasta // channel: [mandatory for dedicated mt analysis] [ val(meta), path(fasta) ]
ch_gnomad_af_tab // channel: [optional; used in for snv annotation] [ val(meta), path(tab) ]
ch_known_dbsnp // channel: [optional; used only by sentieon] [ val(meta), path(vcf) ]
ch_target_bed // channel: [mandatory for WES] [ path(bed) ]
ch_vcfanno_extra_unprocessed // channel: [mandatory] [ val(meta), path(vcf) ]
ch_vep_cache // channel: [mandatory for annotation] [ path(cache) ]

main:
ch_versions = Channel.empty()
Expand Down Expand Up @@ -170,34 +170,34 @@ workflow PREPARE_REFERENCES {
ch_versions = ch_versions.mix(RTGTOOLS_FORMAT.out.versions)

emit:
genome_bwa_index = Channel.empty().mix(ch_bwa, ch_sentieonbwa).collect() // channel: [ val(meta), path(index) ]
genome_bwamem2_index = BWAMEM2_INDEX_GENOME.out.index.collect() // channel: [ val(meta), path(index) ]
genome_bwameme_index = BWAMEME_INDEX_GENOME.out.index.collect() // channel: [ val(meta), path(index) ]
genome_chrom_sizes = GET_CHROM_SIZES.out.sizes.collect() // channel: [ path(sizes) ]
genome_fai = ch_fai // channel: [ val(meta), path(fai) ]
genome_dict = ch_dict // channel: [ val(meta), path(dict) ]
sdf = RTGTOOLS_FORMAT.out.sdf // channel: [ val (meta), path(intervals) ]
mt_intervals = ch_shiftfasta_mtintervals.intervals.collect() // channel: [ path(intervals) ]
mt_bwa_index = ch_bwa_mt // channel: [ val(meta), path(index) ]
mt_bwamem2_index = BWAMEM2_INDEX_MT.out.index.collect() // channel: [ val(meta), path(index) ]
mt_dict = GATK_SD_MT.out.dict.collect() // channel: [ val(meta), path(dict) ]
mt_fasta = ch_mt_fasta_in.collect() // channel: [ val(meta), path(fasta) ]
mt_fai = SAMTOOLS_FAIDX_MT.out.fai.collect() // channel: [ val(meta), path(fai) ]
mtshift_intervals = ch_shiftfasta_mtintervals.shift_intervals.collect() // channel: [ path(intervals) ]
mtshift_backchain = GATK_SHIFTFASTA.out.shift_back_chain.collect() // channel: [ val(meta), path(backchain) ]
mtshift_dict = GATK_SHIFTFASTA.out.dict // channel: [ val(meta), path(dict) ]
mtshift_fai = GATK_SHIFTFASTA.out.shift_fai.collect() // channel: [ val(meta), path(fai) ]
mtshift_fasta = GATK_SHIFTFASTA.out.shift_fa.collect() // channel: [ val(meta), path(fasta) ]
mtshift_bwa_index = ch_bwa_mtshift // channel: [ val(meta), path(index) ]
mtshift_bwamem2_index = BWAMEM2_INDEX_MT_SHIFT.out.index.collect() // channel: [ val(meta), path(index) ]

gnomad_af_idx = TABIX_GNOMAD_AF.out.tbi.collect() // channel: [ val(meta), path(fasta) ]
known_dbsnp_tbi = TABIX_DBSNP.out.tbi.collect() // channel: [ val(meta), path(fasta) ]
target_bed = Channel.empty().mix(ch_tbi, ch_bgzip_tbi).collect() // channel: [ val(meta), path(bed), path(tbi) ]
vcfanno_extra = ch_vcfanno_extra.ifEmpty([[]]) // channel: [ [path(vcf), path(tbi)] ]
bait_intervals = CAT_CAT_BAIT.out.file_out.map{ meta, inter -> inter}.collect() // channel: [ path(intervals) ]
target_intervals = GATK_BILT.out.interval_list.map{ meta, inter -> inter}.collect() // channel: [ path(interval_list) ]
vep_resources = UNTAR_VEP_CACHE.out.untar.map{meta, files -> [files]}.collect() // channel: [ path(cache) ]
versions = ch_versions // channel: [ path(versions.yml) ]
genome_bwa_index = Channel.empty().mix(ch_bwa, ch_sentieonbwa).collect() // channel: [ val(meta), path(index) ]
genome_bwamem2_index = BWAMEM2_INDEX_GENOME.out.index.collect() // channel: [ val(meta), path(index) ]
genome_bwameme_index = BWAMEME_INDEX_GENOME.out.index.collect() // channel: [ val(meta), path(index) ]
genome_chrom_sizes = GET_CHROM_SIZES.out.sizes.collect() // channel: [ path(sizes) ]
genome_fai = ch_fai // channel: [ val(meta), path(fai) ]
genome_dict = ch_dict // channel: [ val(meta), path(dict) ]
sdf = RTGTOOLS_FORMAT.out.sdf // channel: [ val (meta), path(intervals) ]
mt_intervals = ch_shiftfasta_mtintervals.intervals.collect() // channel: [ path(intervals) ]
mt_bwa_index = ch_bwa_mt // channel: [ val(meta), path(index) ]
mt_bwamem2_index = BWAMEM2_INDEX_MT.out.index.collect() // channel: [ val(meta), path(index) ]
mt_dict = GATK_SD_MT.out.dict.collect() // channel: [ val(meta), path(dict) ]
mt_fasta = ch_mt_fasta_in.collect() // channel: [ val(meta), path(fasta) ]
mt_fai = SAMTOOLS_FAIDX_MT.out.fai.collect() // channel: [ val(meta), path(fai) ]
mtshift_intervals = ch_shiftfasta_mtintervals.shift_intervals.collect() // channel: [ path(intervals) ]
mtshift_backchain = GATK_SHIFTFASTA.out.shift_back_chain.collect() // channel: [ val(meta), path(backchain) ]
mtshift_dict = GATK_SHIFTFASTA.out.dict // channel: [ val(meta), path(dict) ]
mtshift_fai = GATK_SHIFTFASTA.out.shift_fai.collect() // channel: [ val(meta), path(fai) ]
mtshift_fasta = GATK_SHIFTFASTA.out.shift_fa.collect() // channel: [ val(meta), path(fasta) ]
mtshift_bwa_index = ch_bwa_mtshift // channel: [ val(meta), path(index) ]
mtshift_bwamem2_index = BWAMEM2_INDEX_MT_SHIFT.out.index.collect() // channel: [ val(meta), path(index) ]

gnomad_af_idx = TABIX_GNOMAD_AF.out.tbi.collect() // channel: [ val(meta), path(fasta) ]
known_dbsnp_tbi = TABIX_DBSNP.out.tbi.collect() // channel: [ val(meta), path(fasta) ]
target_bed = Channel.empty().mix(ch_tbi, ch_bgzip_tbi).collect() // channel: [ val(meta), path(bed), path(tbi) ]
vcfanno_extra = ch_vcfanno_extra.ifEmpty([[]]) // channel: [ [path(vcf), path(tbi)] ]
bait_intervals = CAT_CAT_BAIT.out.file_out.map{ meta, inter -> inter}.collect().ifEmpty([[]]) // channel: [ path(intervals) ]
target_intervals = GATK_BILT.out.interval_list.map{ meta, inter -> inter}.collect() // channel: [ path(interval_list) ]
vep_resources = UNTAR_VEP_CACHE.out.untar.map{meta, files -> [files]}.collect() // channel: [ path(cache) ]
versions = ch_versions // channel: [ path(versions.yml) ]

}
15 changes: 11 additions & 4 deletions subworkflows/local/variant_calling/call_snv_deepvariant.nf
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Expand Up @@ -16,6 +16,7 @@ workflow CALL_SNV_DEEPVARIANT {
ch_bam_bai // channel: [mandatory] [ val(meta), path(bam), path(bai) ]
ch_genome_fasta // channel: [mandatory] [ val(meta), path(fasta) ]
ch_genome_fai // channel: [mandatory] [ val(meta), path(fai) ]
ch_bait_intervals // channel: [mandatory] [ path(intervals) ]
ch_par_bed // channel: [optional] [ val(meta), path(bed) ]
ch_case_info // channel: [mandatory] [ val(case_info) ]
ch_foundin_header // channel: [mandatory] [ path(header) ]
Expand All @@ -24,10 +25,16 @@ workflow CALL_SNV_DEEPVARIANT {
main:
ch_versions = Channel.empty()

ch_bam_bai.map { meta, bam, bai ->
return [meta, bam, bai, []]
}
.set { ch_deepvar_in }
if (params.analysis_type.equals("wes")) {
ch_bam_bai
.combine (ch_bait_intervals)
.set { ch_deepvar_in }
} else if (params.analysis_type.equals("wgs")) {
ch_bam_bai
.map { meta, bam, bai ->
return [meta, bam, bai, []] }
.set { ch_deepvar_in }
}

DEEPVARIANT ( ch_deepvar_in, ch_genome_fasta, ch_genome_fai, [[],[]], ch_par_bed )
DEEPVARIANT.out.gvcf
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1 change: 1 addition & 0 deletions workflows/raredisease.nf
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Expand Up @@ -517,6 +517,7 @@ workflow RAREDISEASE {
ch_dbsnp,
ch_dbsnp_tbi,
ch_call_interval,
ch_bait_intervals,
ch_ml_model,
ch_par_bed,
ch_case_info,
Expand Down
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