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📝 update snv hotspot refs #22

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Jul 18, 2024
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2 changes: 1 addition & 1 deletion README.md
Original file line number Diff line number Diff line change
Expand Up @@ -61,7 +61,7 @@ Most inputs have recommended values that should auto import both files and param
- `b_allele`: dbSNP_v153_ucsc-compatible.converted.vt.decomp.norm.common_snps.vcf.gz. dbSNP v153 was obtained from [the ftp site](https://ftp.ncbi.nih.gov/snp/archive/b153/VCF/GCF_000001405.38.gz). Then, using a awk/perl/bash script of your choice, convert NCBI accession names to UCSC-style chromosome names using [this table](https://hgdownload.soe.ucsc.edu/hubs/GCF/000/001/405/GCF_000001405.39/GCF_000001405.39.chromAlias.txt). Next, run the [VCF normalization tool](https://github.com/kids-first/kf-annotation-tools/blob/master/tools/normalize_vcf.cwl), then use bcftools to extract only common snps: `bcftools view --include INFO/COMMON=1 --types snps dbSNP_v153_ucsc-compatible.converted.vt.decomp.norm.vcf.gz -O z -o dbSNP_v153_ucsc-compatible.converted.vt.decomp.norm.common_snps.vcf.gz`. Lastly, use tabix to index the resultant file.
- `vep_cache`: homo_sapiens_merged_vep_105_indexed_GRCh38.tar.gz
- `genomic_hotspots`: tert.bed # bed file with TERT gene promoter region
- `protein_snv_hotspots`: protein_snv_cancer_hotspots_v2.ENS105_liftover.tsv
- `protein_snv_hotspots`: kfdrc_protein_snv_cancer_hotspots_20240718.txt
- `protein_indel_hotspots`: protein_indel_cancer_hotspots_v2.ENS105_liftover.tsv
- `echtvar_anno_zips`: gnomad.v3.1.1.custom.echtvar.zip
### Necessary for user to define:
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2 changes: 1 addition & 1 deletion workflows/kfdrc_mutect2_production_wf.cwl
Original file line number Diff line number Diff line change
Expand Up @@ -202,7 +202,7 @@ inputs:
protein_snv_hotspots: {type: 'File[]?', doc: "Column-name-containing, tab-delimited\
\ file(s) containing protein names and amino acid positions corresponding to\
\ hotspots", "sbg:suggestedValue": [{class: File, path: 645919782fe81458768c552c,
name: protein_snv_cancer_hotspots_v2.ENS105_liftover.tsv}]}
name: kfdrc_protein_snv_cancer_hotspots_20240718.txt}]}
protein_indel_hotspots: {type: 'File[]?', doc: "Column-name-containing, tab-delimited\
\ file(s) containing protein names and amino acid position ranges corresponding\
\ to hotspots", "sbg:suggestedValue": [{class: File, path: 645919782fe81458768c552d,
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4 changes: 2 additions & 2 deletions workflows/kfdrc_tumor_only_dna_wf.cwl
Original file line number Diff line number Diff line change
Expand Up @@ -65,7 +65,7 @@ doc: |
- `b_allele`: dbSNP_v153_ucsc-compatible.converted.vt.decomp.norm.common_snps.vcf.gz. dbSNP v153 was obtained from [the ftp site](https://ftp.ncbi.nih.gov/snp/archive/b153/VCF/GCF_000001405.38.gz). Then, using a awk/perl/bash script of your choice, convert NCBI accession names to UCSC-style chromosome names using [this table](https://hgdownload.soe.ucsc.edu/hubs/GCF/000/001/405/GCF_000001405.39/GCF_000001405.39.chromAlias.txt). Next, run the [VCF normalization tool](https://github.com/kids-first/kf-annotation-tools/blob/master/tools/normalize_vcf.cwl), then use bcftools to extract only common snps: `bcftools view --include INFO/COMMON=1 --types snps dbSNP_v153_ucsc-compatible.converted.vt.decomp.norm.vcf.gz -O z -o dbSNP_v153_ucsc-compatible.converted.vt.decomp.norm.common_snps.vcf.gz`. Lastly, use tabix to index the resultant file.
- `vep_cache`: homo_sapiens_merged_vep_105_indexed_GRCh38.tar.gz
- `genomic_hotspots`: tert.bed # bed file with TERT gene promoter region
- `protein_snv_hotspots`: protein_snv_cancer_hotspots_v2.ENS105_liftover.tsv
- `protein_snv_hotspots`: kfdrc_protein_snv_cancer_hotspots_20240718.txt
- `protein_indel_hotspots`: protein_indel_cancer_hotspots_v2.ENS105_liftover.tsv
- `echtvar_anno_zips`: gnomad.v3.1.1.custom.echtvar.zip
### Necessary for user to define:
Expand Down Expand Up @@ -204,7 +204,7 @@ inputs:
genomic_hotspots: {type: 'File[]?', doc: "Tab-delimited BED formatted file(s) containing hg38 genomic positions corresponding to
hotspots", "sbg:suggestedValue": [{class: File, path: 607713829360f10e3982a423, name: tert.bed}]}
protein_snv_hotspots: {type: 'File[]?', doc: "Column-name-containing, tab-delimited file(s) containing protein names and amino acid
positions corresponding to hotspots", "sbg:suggestedValue": [{class: File, path: 663d2bcc27374715fccd8c6a, name: protein_snv_cancer_hotspots_v2.ENS105_liftover.tsv}]}
positions corresponding to hotspots", "sbg:suggestedValue": [{class: File, path: 66980e845a58091951d53984, name: kfdrc_protein_snv_cancer_hotspots_20240718.txt}]}
protein_indel_hotspots: {type: 'File[]?', doc: "Column-name-containing, tab-delimited file(s) containing protein names and amino
acid position ranges corresponding to hotspots", "sbg:suggestedValue": [{class: File, path: 663d2bcc27374715fccd8c6f, name: protein_indel_cancer_hotspots_v2.ENS105_liftover.tsv}]}
mutect2_retain_info: {type: 'string?', doc: "csv string with INFO fields that you want to keep", default: "gnomad_3_1_1_AC,gnomad_3_1_1_AN,gnomad_3_1_1_AF,gnomad_3_1_1_nhomalt,gnomad_3_1_1_AC_popmax,gnomad_3_1_1_AN_popmax,gnomad_3_1_1_AF_popmax,gnomad_3_1_1_nhomalt_popmax,gnomad_3_1_1_AC_controls_and_biobanks,gnomad_3_1_1_AN_controls_and_biobanks,gnomad_3_1_1_AF_controls_and_biobanks,gnomad_3_1_1_AF_non_cancer,gnomad_3_1_1_primate_ai_score,gnomad_3_1_1_splice_ai_consequence,gnomad_3_1_1_AF_non_cancer_afr,gnomad_3_1_1_AF_non_cancer_ami,gnomad_3_1_1_AF_non_cancer_asj,gnomad_3_1_1_AF_non_cancer_eas,gnomad_3_1_1_AF_non_cancer_fin,gnomad_3_1_1_AF_non_cancer_mid,gnomad_3_1_1_AF_non_cancer_nfe,gnomad_3_1_1_AF_non_cancer_oth,gnomad_3_1_1_AF_non_cancer_raw,gnomad_3_1_1_AF_non_cancer_sas,gnomad_3_1_1_AF_non_cancer_amr,gnomad_3_1_1_AF_non_cancer_popmax,gnomad_3_1_1_AF_non_cancer_all_popmax,gnomad_3_1_1_FILTER,MQ,MQ0,QSI,HotSpotAllele"}
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