#!/usr/bin/env cwl-runner cwlVersion: v1.0 class: Workflow label: "gathered exome alignment and somatic variant detection" requirements: - class: SchemaDefRequirement types: - $import: ../types/labelled_file.yml - $import: ../types/sequence_data.yml - $import: ../types/vep_custom_annotation.yml - class: SubworkflowFeatureRequirement - class: StepInputExpressionRequirement inputs: reference: type: - string - File secondaryFiles: [.fai, ^.dict, .amb, .ann, .bwt, .pac, .sa] tumor_sequence: type: ../types/sequence_data.yml#sequence_data[] tumor_cram_name: type: string? default: 'tumor.cram' normal_sequence: type: ../types/sequence_data.yml#sequence_data[] normal_cram_name: type: string? default: 'normal.cram' bqsr_known_sites: type: File[] secondaryFiles: [.tbi] doc: "One or more databases of known polymorphic sites used to exclude regions around known polymorphisms from analysis." bqsr_intervals: type: string[] bait_intervals: type: File target_intervals: type: File label: "target_intervals: interval_list file of targets used in the sequencing experiment" doc: | target_intervals is an interval_list corresponding to the targets for the capture reagent. Bed files with this information can be converted to interval_lists with Picard BedToIntervalList. In general for a WES exome reagent bait_intervals and target_intervals are the same. target_interval_padding: type: int label: "target_interval_padding" doc: | The effective coverage of capture products generally extends out beyond the actual regions targeted. This parameter allows variants to be called in these wingspan regions, extending this many base pairs from each side of the target regions. default: 100 per_base_intervals: type: ../types/labelled_file.yml#labelled_file[] per_target_intervals: type: ../types/labelled_file.yml#labelled_file[] summary_intervals: type: ../types/labelled_file.yml#labelled_file[] omni_vcf: type: File secondaryFiles: [.tbi] picard_metric_accumulation_level: type: string qc_minimum_mapping_quality: type: int? default: 0 qc_minimum_base_quality: type: int? default: 0 strelka_cpu_reserved: type: int? default: 8 scatter_count: type: int doc: "scatters each supported variant detector (varscan, pindel, mutect) into this many parallel jobs" mutect_artifact_detection_mode: type: boolean mutect_max_alt_allele_in_normal_fraction: type: float? mutect_max_alt_alleles_in_normal_count: type: int? varscan_strand_filter: type: int? default: 0 varscan_min_coverage: type: int? default: 8 varscan_min_var_freq: type: float? default: 0.05 varscan_p_value: type: float? default: 0.99 varscan_max_normal_freq: type: float? pindel_insert_size: type: int default: 400 docm_vcf: type: File secondaryFiles: [.tbi] doc: "Common mutations in cancer that will be genotyped and passed through into the merged VCF if they have even low-level evidence of a mutation (by default, marked with filter DOCM_ONLY)" filter_docm_variants: type: boolean? default: true doc: "Determines whether variants found only via genotyping of DOCM sites will be filtered (as DOCM_ONLY) or passed through as variant calls" filter_somatic_llr_threshold: type: float default: 5 doc: "Sets the stringency (log-likelihood ratio) used to filter out non-somatic variants. Typical values are 10=high stringency, 5=normal, 3=low stringency. Low stringency may be desirable when read depths are low (as in WGS) or when tumor samples are impure." filter_somatic_llr_tumor_purity: type: float default: 1 doc: "Sets the purity of the tumor used in the somatic llr filter, used to remove non-somatic variants. Probably only needs to be adjusted for low-purity (< 50%). Range is 0 to 1" filter_somatic_llr_normal_contamination_rate: type: float default: 0 doc: "Sets the fraction of tumor present in the normal sample (range 0 to 1), used in the somatic llr filter. Useful for heavily contaminated adjacent normals. Range is 0 to 1" vep_cache_dir: type: - string - Directory vep_ensembl_assembly: type: string doc: "genome assembly to use in vep. Examples: GRCh38 or GRCm38" vep_ensembl_version: type: string doc: "ensembl version - Must be present in the cache directory. Example: 95" vep_ensembl_species: type: string doc: "ensembl species - Must be present in the cache directory. Examples: homo_sapiens or mus_musculus" synonyms_file: type: File? annotate_coding_only: type: boolean? hgvs_annotation: type: boolean? vep_pick: type: - "null" - type: enum symbols: ["pick", "flag_pick", "pick_allele", "per_gene", "pick_allele_gene", "flag_pick_allele", "flag_pick_allele_gene"] cle_vcf_filter: type: boolean default: false variants_to_table_fields: type: string[] default: [CHROM,POS,ID,REF,ALT,set,AC,AF] variants_to_table_genotype_fields: type: string[] default: [GT,AD] vep_to_table_fields: type: string[] default: [HGVSc,HGVSp] vep_custom_annotations: type: ../types/vep_custom_annotation.yml#vep_custom_annotation[] doc: "custom type, check types directory for input format" output_dir: type: string somalier_vcf: type: File tumor_sample_name: type: string normal_sample_name: type: string known_variants: type: File? secondaryFiles: [.tbi] doc: "Previously discovered variants to be flagged in this pipelines's output vcf" outputs: final_outputs: type: string[] outputSource: gatherer/gathered_files steps: somatic_exome: run: somatic_exome.cwl in: reference: reference tumor_sequence: tumor_sequence tumor_cram_name: tumor_cram_name normal_sequence: normal_sequence normal_cram_name: normal_cram_name bqsr_known_sites: bqsr_known_sites bqsr_intervals: bqsr_intervals bait_intervals: bait_intervals target_intervals: target_intervals target_interval_padding: target_interval_padding per_base_intervals: per_base_intervals per_target_intervals: per_target_intervals summary_intervals: summary_intervals omni_vcf: omni_vcf picard_metric_accumulation_level: picard_metric_accumulation_level qc_minimum_mapping_quality: qc_minimum_mapping_quality qc_minimum_base_quality: qc_minimum_base_quality strelka_cpu_reserved: strelka_cpu_reserved scatter_count: scatter_count mutect_artifact_detection_mode: mutect_artifact_detection_mode mutect_max_alt_allele_in_normal_fraction: mutect_max_alt_allele_in_normal_fraction mutect_max_alt_alleles_in_normal_count: mutect_max_alt_alleles_in_normal_count varscan_strand_filter: varscan_strand_filter varscan_min_coverage: varscan_min_coverage varscan_min_var_freq: varscan_min_var_freq varscan_p_value: varscan_p_value varscan_max_normal_freq: varscan_max_normal_freq pindel_insert_size: pindel_insert_size docm_vcf: docm_vcf vep_cache_dir: vep_cache_dir vep_ensembl_assembly: vep_ensembl_assembly vep_ensembl_version: vep_ensembl_version vep_ensembl_species: vep_ensembl_species synonyms_file: synonyms_file annotate_coding_only: annotate_coding_only hgvs_annotation: hgvs_annotation vep_pick: vep_pick cle_vcf_filter: cle_vcf_filter filter_somatic_llr_threshold: filter_somatic_llr_threshold filter_somatic_llr_tumor_purity: filter_somatic_llr_tumor_purity filter_somatic_llr_normal_contamination_rate: filter_somatic_llr_normal_contamination_rate variants_to_table_fields: variants_to_table_fields variants_to_table_genotype_fields: variants_to_table_genotype_fields vep_to_table_fields: vep_to_table_fields vep_custom_annotations: vep_custom_annotations somalier_vcf: somalier_vcf tumor_sample_name: tumor_sample_name normal_sample_name: normal_sample_name known_variants: known_variants out: [tumor_cram, tumor_mark_duplicates_metrics, tumor_insert_size_metrics, tumor_alignment_summary_metrics, tumor_hs_metrics, tumor_per_target_coverage_metrics, tumor_per_base_coverage_metrics, tumor_per_base_hs_metrics, tumor_summary_hs_metrics, tumor_flagstats, tumor_verify_bam_id_metrics, tumor_verify_bam_id_depth, normal_cram, normal_mark_duplicates_metrics, normal_insert_size_metrics, normal_alignment_summary_metrics, normal_hs_metrics, normal_per_target_coverage_metrics, normal_per_target_hs_metrics, normal_per_base_coverage_metrics, normal_per_base_hs_metrics, normal_summary_hs_metrics, normal_flagstats, normal_verify_bam_id_metrics, normal_verify_bam_id_depth, mutect_unfiltered_vcf, mutect_filtered_vcf, strelka_unfiltered_vcf, strelka_filtered_vcf, varscan_unfiltered_vcf, varscan_filtered_vcf, pindel_unfiltered_vcf, pindel_filtered_vcf, docm_filtered_vcf, final_vcf, final_filtered_vcf, final_tsv, vep_summary, tumor_snv_bam_readcount_tsv, tumor_indel_bam_readcount_tsv, normal_snv_bam_readcount_tsv, normal_indel_bam_readcount_tsv, somalier_concordance_metrics, somalier_concordance_statistics] gatherer: run: ../tools/gatherer.cwl in: output_dir: output_dir all_files: source: [somatic_exome/tumor_cram, somatic_exome/tumor_mark_duplicates_metrics, somatic_exome/tumor_insert_size_metrics, somatic_exome/tumor_alignment_summary_metrics, somatic_exome/tumor_hs_metrics, somatic_exome/tumor_per_target_coverage_metrics, somatic_exome/tumor_per_base_coverage_metrics, somatic_exome/tumor_per_base_hs_metrics, somatic_exome/tumor_summary_hs_metrics, somatic_exome/tumor_flagstats, somatic_exome/tumor_verify_bam_id_metrics, somatic_exome/tumor_verify_bam_id_depth, somatic_exome/normal_cram, somatic_exome/normal_mark_duplicates_metrics, somatic_exome/normal_insert_size_metrics, somatic_exome/normal_alignment_summary_metrics, somatic_exome/normal_hs_metrics, somatic_exome/normal_per_target_coverage_metrics, somatic_exome/normal_per_target_hs_metrics, somatic_exome/normal_per_base_coverage_metrics, somatic_exome/normal_per_base_hs_metrics, somatic_exome/normal_summary_hs_metrics, somatic_exome/normal_flagstats, somatic_exome/normal_verify_bam_id_metrics, somatic_exome/normal_verify_bam_id_depth, somatic_exome/mutect_unfiltered_vcf, somatic_exome/mutect_filtered_vcf, somatic_exome/strelka_unfiltered_vcf, somatic_exome/strelka_filtered_vcf, somatic_exome/varscan_unfiltered_vcf, somatic_exome/varscan_filtered_vcf, somatic_exome/pindel_unfiltered_vcf, somatic_exome/pindel_filtered_vcf, somatic_exome/docm_filtered_vcf, somatic_exome/final_vcf, somatic_exome/final_filtered_vcf, somatic_exome/final_tsv, somatic_exome/vep_summary, somatic_exome/tumor_snv_bam_readcount_tsv, somatic_exome/tumor_indel_bam_readcount_tsv, somatic_exome/normal_snv_bam_readcount_tsv, somatic_exome/normal_indel_bam_readcount_tsv] valueFrom: ${ function flatten(inArr, outArr) { var arrLen = inArr.length; for (var i = 0; i < arrLen; i++) { if (Array.isArray(inArr[i])) { flatten(inArr[i], outArr); } else { outArr.push(inArr[i]); } } return outArr; } var no_secondaries = flatten(self, []); var all_files = []; var arrLen = no_secondaries.length; for (var i = 0; i < arrLen; i++) { all_files.push(no_secondaries[i]); var secondaryLen = no_secondaries[i].secondaryFiles.length; for (var j = 0; j < secondaryLen; j++) { all_files.push(no_secondaries[i].secondaryFiles[j]); } } return all_files; } out: [gathered_files]