pipelines_immuno.cwl

Documentation for immuno.cwl

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Overview

Immunotherapy Workflow

Inputs

Name	Label	Description	Type	Secondary Files
reference_annotation		Annotated transcripts in GTF format	File
rna_sequence		Raw data from rna sequencing; this custom type holds both the data file(s) and readgroup information. Data file(s) may be either a bam file, or paired fastqs. Readgroup information should be given as a series of key:value pairs, each separated by a space. This means that spaces within a value must be double quoted. The first key must be ID; consult the read group description in the header section of the SAM file specification for other, optional keys. Below is an example of an element of the input array: readgroup: "ID:xxx PU:xxx SM:xxx LB:xxx PL:ILLUMINA CN:WUGSC" sequence: fastq1: class: File path: /path/to/reads1.fastq fastq2: class: File path: /path/to/reads2.fastq OR bam: class: File path: /path/to/reads.bam	../types/sequence_data.yml#sequence_data[]
rna_sample_name			string
trimming_adapters			File
trimming_adapter_trim_end			string
trimming_adapter_min_overlap			int
trimming_max_uncalled			int
trimming_min_readlength			int
kallisto_index			File
gene_transcript_lookup_table			File
strand			['null', {'type': 'enum', 'symbols': ['first', 'second', 'unstranded']}]
refFlat			File
ribosomal_intervals			File
star_aligner_genome_dir		Path to the directory where STAR aligner genome indices are stored. Consult the STAR manual to generate new indices.	['string', 'Directory']
star_fusion_genome_dir		Path to the directory where STAR fusion resources are stored. This includes a reference genome and corresponding protein coding gene annotation set. These may be downloaded or generated by a helper script; see the star-fusion manual for more info.	['string', 'Directory']
examine_coding_effect		Describe the effect of predicted fusions on coding regions	boolean?
fusioninspector_mode		If/how to validate fusion transcripts; see STAR-Fusion manual for more info	['null', {'type': 'enum', 'symbols': ['inspect', 'validate']}]
cdna_fasta		Fasta with transcripts, used to verify strand	File
agfusion_database		agfusion reference database	File
agfusion_annotate_noncanonical		Annotate all gene transcripts, not just canonical isoforms	boolean?
reference	reference: Reference fasta file for a desired assembly	reference contains the nucleotide sequence for a given assembly (hg37, hg38, etc.) in fasta format for the entire genome. This is what reads will be aligned to. Appropriate files can be found on ensembl at https://ensembl.org/info/data/ftp/index.html When providing the reference secondary files corresponding to reference indices must be located in the same directory as the reference itself. These files can be created with samtools index, bwa index, and picard CreateSequenceDictionary.	['string', 'File']	['.fai', '^.dict', '.amb', '.ann', '.bwt', '.pac', '.sa']
tumor_sequence	tumor_sequence: MT sequencing data and readgroup information	tumor_sequence represents the sequencing data for the MT sample as either FASTQs or BAMs with accompanying readgroup information. The readgroup field should contain an entire read group header line, as described in the SAM file specification. This is a list of strings, beginning with @RG and followed by key:value pairs; each element of the list should be separated by a tab (\t). Keys ID and SM are required; see below for a formatting example: readgroup: "@RG\tID:xxx\tSM:xx" sequence: fastq1: class: File path: /path/to/reads1.fastq fastq2: class: File path: /path/to/reads2.fastq OR bam: class: File path: /path/to/reads.bam	../types/sequence_data.yml#sequence_data[]
tumor_filename	tumor/MT aligned bam filename	the filename to be used for bam files produced by the pipeline containing aligned tumor/mutant reads	string?
normal_sequence	normal_sequence: WT sequencing data and readgroup information	normal_sequence represents the sequencing data for the WT sample as either FASTQs or BAMs with accompanying readgroup information. The readgroup field should contain an entire read group header line, as described in the SAM file specification. This is a list of strings, beginning with @RG and followed by key:value pairs; each element of the list should be separated by a tab (\t). Keys ID and SM are required; see below for a formatting example: readgroup: "@RG\tID:xxx\tSM:xx" sequence: fastq1: class: File path: /path/to/reads1.fastq fastq2: class: File path: /path/to/reads2.fastq OR bam: class: File path: /path/to/reads.bam	../types/sequence_data.yml#sequence_data[]
normal_filename	normal/WT aligned bam filename	the filename to be used for bam files produced by the pipeline containing aligned normal/wild-type reads	string?
bqsr_known_sites	bqsr_known_sites: One or more databases of known polymorphic sites used to exclude regions around known polymorphisms from analysis.	Known polymorphic indels recommended by GATK for a variety of tools including the BaseRecalibrator. This is part of the GATK resource bundle available at http://www.broadinstitute.org/gatk/guide/article?id=1213 File should be in vcf format, and tabix indexed.	File[]	['.tbi']
bqsr_intervals	bqsr_intervals: Array of strings specifying regions for base quality score recalibration	bqsr_intervals provides an array of genomic intervals for which to apply GATK base quality score recalibrations. Typically intervals are given for the entire chromosome (chr1, chr2, etc.), these names should match the format in the reference file.	string[]
bait_intervals	bait_intervals: interval_list file of baits used in the sequencing experiment	bait_intervals is an interval_list corresponding to the baits used in sequencing reagent. These are essentially coordinates for regions you were able to design probes for in the reagent. Typically the reagent provider has this information available in bed format and it can be converted to an interval_list with Picard BedToIntervalList. AstraZeneca also maintains a repo of baits for common sequencing reagents available at https://github.com/AstraZeneca-NGS/reference_data	File
target_intervals	target_intervals: interval_list file of targets used in the sequencing experiment	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.	File
target_interval_padding	target_interval_padding: number of bp flanking each target region in which to allow variant calls	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.	int
per_base_intervals			../types/labelled_file.yml#labelled_file[]
per_target_intervals			../types/labelled_file.yml#labelled_file[]
summary_intervals			../types/labelled_file.yml#labelled_file[]
omni_vcf			File	['.tbi']
picard_metric_accumulation_level			string
qc_minimum_mapping_quality			int?
qc_minimum_base_quality			int?
strelka_cpu_reserved			int?
scatter_count		scatters each supported variant detector (varscan, pindel, mutect) into this many parallel jobs	int
mutect_artifact_detection_mode			boolean
mutect_max_alt_allele_in_normal_fraction			float?
mutect_max_alt_alleles_in_normal_count			int?
varscan_strand_filter			int?
varscan_min_coverage			int?
varscan_min_var_freq			float?
varscan_p_value			float?
varscan_max_normal_freq			float?
pindel_insert_size			int
docm_vcf		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)	File	['.tbi']
filter_docm_variants		Determines whether variants found only via genotyping of DOCM sites will be filtered (as DOCM_ONLY) or passed through as variant calls	boolean?
vep_cache_dir			['string', 'Directory']
vep_ensembl_assembly		genome assembly to use in vep. Examples: GRCh38 or GRCm38	string
vep_ensembl_version		ensembl version - Must be present in the cache directory. Example: 95	string
vep_ensembl_species		ensembl species - Must be present in the cache directory. Examples: homo_sapiens or mus_musculus	string
synonyms_file			File?
annotate_coding_only			boolean?
vep_pick			['null', {'type': 'enum', 'symbols': ['pick', 'flag_pick', 'pick_allele', 'per_gene', 'pick_allele_gene', 'flag_pick_allele', 'flag_pick_allele_gene']}]
cle_vcf_filter			boolean
variants_to_table_fields			string[]
variants_to_table_genotype_fields			string[]
vep_to_table_fields			string[]
vep_custom_annotations		custom type, check types directory for input format	../types/vep_custom_annotation.yml#vep_custom_annotation[]
manta_call_regions			File?	['.tbi']
manta_non_wgs			boolean?
manta_output_contigs			boolean?
somalier_vcf			File
validated_variants		An optional VCF with variants that will be flagged as 'VALIDATED' if found in this pipeline's main output VCF	File?	['.tbi']
gvcf_gq_bands			string[]
gatk_haplotypecaller_intervals			{'type': 'array', 'items': {'type': 'array', 'items': 'string'}}
ploidy			int?
optitype_name			string?
reference_dict			File
clinical_mhc_classI_alleles	Clinical HLA typing results, limited to MHC Class I alleles; element format: HLA-X*01:02[/HLA-X...]	used to provide clinical HLA typing results in the format HLA-X*01:02[/HLA-X...] when available.	string[]?
clinical_mhc_classII_alleles	Clinical HLA typing results, limited to MHC Class II alleles	used to provide clinical HLA typing results; separated from class I due to nomenclature inconsistencies	string[]?
hla_source_mode	Source for HLA types used for epitope prediction: in silico and clinical, or just clinical	Control whether HLA types passed to pvacseq should be a consensus of optitype predictions and clinical calls, if provided, or if only clinical calls should be used. In this case, optitype predictions and mismatches between optitype and clinical calls will still be reported. Selecting clinical_only without providing clinical calls will result in an error.	{'type': 'enum', 'symbols': ['consensus', 'clinical_only']}
readcount_minimum_base_quality			int?
readcount_minimum_mapping_quality			int?
prediction_algorithms			string[]
epitope_lengths_class_i			int[]?
epitope_lengths_class_ii			int[]?
binding_threshold			int?
percentile_threshold			int?
allele_specific_binding_thresholds			boolean?
minimum_fold_change			float?
top_score_metric			['null', {'type': 'enum', 'symbols': ['lowest', 'median']}]
additional_report_columns			['null', {'type': 'enum', 'symbols': ['sample_name']}]
expression_tool			string?
fasta_size			int?
downstream_sequence_length			string?
exclude_nas			boolean?
phased_proximal_variants_vcf			File?	['.tbi']
maximum_transcript_support_level			['null', {'type': 'enum', 'symbols': ['1', '2', '3', '4', '5']}]
normal_cov			int?
tdna_cov			int?
trna_cov			int?
normal_vaf			float?
tdna_vaf			float?
trna_vaf			float?
expn_val			float?
net_chop_method	net_chop_method: NetChop prediction method to use ('cterm' for C term 3.0, '20s' for 20S 3.0)	net_chop_method is used to specify which NetChop prediction method to use ("cterm" for C term 3.0, "20s" for 20S 3.0). C-term 3.0 is trained with publicly available MHC class I ligands and the authors believe that is performs best in predicting the boundaries of CTL epitopes. 20S is trained with in vitro degradation data.	['null', {'type': 'enum', 'symbols': ['cterm', '20s']}]
net_chop_threshold	net_chop_threshold: NetChop prediction threshold	net_chop_threshold specifies the threshold to use for NetChop prediction; increasing the threshold results in better specificity, but worse sensitivity.	float?
netmhc_stab	netmhc_stab: sets an option whether to run NetMHCStabPan or not	netmhc_stab sets an option that decides whether it will run NetMHCStabPan after all filtering and add stability predictions to predicted epitopes.	boolean?
run_reference_proteome_similarity	run_reference_proteome_similarity: sets an option whether to run reference proteome similarity or not	run_reference_proteome_similarity sets an option that decides whether it will run reference proteome similarity after all filtering and BLAST peptide sequences against the reference proteome to see if they appear elsewhere in the proteome.	boolean?
blastp_db	blastp_db: sets the reference proteome database to use with BLASTp	blastp_db sets the reference proteome database to use with BLASTp when enabling run_reference_proteome_similarity	['null', {'type': 'enum', 'symbols': ['refseq_select_prot', 'refseq_protein']}]
pvacseq_threads	pvacseq_threads: Number of threads to use for parallelizing pvacseq prediction	pvacseq_threads specifies the number of threads to use for parallelizing peptide-MHC binding prediction calls.	int?
tumor_sample_name	tumor_sample_name: Name of the tumor sample	tumor_sample_name is the name of the tumor sample being processed. When processing a multi-sample VCF the sample name must be a sample ID in the input VCF #CHROM header line.	string
normal_sample_name	normal_sample_name: Name of the normal sample	normal_sample_name is the name of the normal sample to use for phasing of germline variants.	string
tumor_purity			float?
iedb_retries			int?
pvacfuse_keep_tmp_files			boolean?
reference_genome_name			string?
dna_sequencing_platform			string?
dna_sequencing_instrument			string?
dna_sequencing_kit			string?
dna_sequencing_type			string?
dna_single_or_paired_end			string?
normal_dna_spike_in_error_rate			string?
tumor_dna_spike_in_error_rate			string?
normal_dna_total_DNA			string?
tumor_dna_total_DNA			string?
rna_sequencing_platform			string?
rna_sequencing_instrument			string?
rna_sequencing_kit			string?
rna_sequencing_type			string?
rna_single_or_paired_end			string?
rna_spike_in_error_rate			string?
rna_total_RNA			string?
rna_RIN_score			string?
rna_freq_normalization_method			string?
rna_annotation_file			string?

Outputs

Name	Label	Description	Type	Secondary Files
final_bigwig			File
final_bam	Sorted BAM from tumor RNA	Sorted BAM file of sequencing read alignments by STAR with duplicate reads tagged	File	['.bai']
stringtie_transcript_gtf	Transcript GTF assembled from tumor RNA by StringTie	GTF file containing the transcripts assembled from the tumor RNA sample, created by StringTie	File
stringtie_gene_expression_tsv	Gene abundance table from tumor RNA by StringTie	Tab-delimited file containing gene abundances in FPKM and TPM, created by StringTie	File
transcript_abundance_tsv	Transcript-level abundance table by kallisto	Tab-delimited file containing transcript-level abundance estimates in TPM, created by kallisto	File
transcript_abundance_h5	Transcript-level abundance table in HDF5 format by kallisto	HDF5 binary file containing transcript-level abundance esimates, bootstrap estimate, and so on, created by kallisto	File
gene_abundance	Gene-level abundance output by tximport with kallisto output	Tab-delimited file containing the abundance estimates summarized in the gene level with kallisto output by Bioconductor tximport tool	File
metrics	RNA-seq Diagnosis/quality metrics from tumor RNA	RNA-seq Diagnosis/quality metrics showing the distribution of the bases within the transcripts, created by picard CollectRnaSeqMetrics tool	File
chart	Plot for RNA-seq diagnosis/quality metrics	PDF file for the plot of RNA sequencing coverage at the normalized position across transcript as RNA-seq diagnosis/quality metrics, created by picard CollectRnaSeqMetrics tool	File?
rnaseq_cram			File	['.crai', '^.crai']
star_fusion_out			File
star_junction_out			File
star_fusion_log			File
star_fusion_predict			File
star_fusion_abridge			File
strand_info			File[]
annotated_fusion_predictions			Directory
coding_region_effects			File?
fusioninspector_evidence			File[]?
tumor_cram	Sorted CRAM from tumor DNA	Sorted CRAM file of sequencing read alignments by bwa-mem from a tumor DNA sample with duplicate reads tagged	File
tumor_mark_duplicates_metrics	Sequencing duplicate metrics from tumor DNA	Duplication metrics on duplicate sequencing reads from a tumor DNA sample, identified by picard MarkDuplicates tool	File
tumor_insert_size_metrics	Paired-end sequencing diagnosis/quality metrics from tumor DNA	Diagnosis/quality metrics including the insert size distribution and read orientation of the paired-end libraries from a tumor DNA sample	File
tumor_alignment_summary_metrics	Sequencign alignment summary from tumor DNA	Diagnosis/quality metrics summarizing the quality of sequencing read alignments from a tumor DNA sample, reported by the picard CollectAlignmentSummaryMetrics tool	File
tumor_hs_metrics	Sequencing coverage summary of target intervals from tumor DNA	Diagnosis/quality metrics specific for sequencing data generated through hybrid-selection (e.g. whole exome) from a tumor DNA sample, for example to assess target coverage of WES	File
tumor_per_target_coverage_metrics	Sequencing per-target coverage summary of target intervals from tumor DNA	Diagnosis/quality metrics showing detailed sequencing coverage per target interval (optional, 59 genes recommended by ACMG for clinical exome and genome sequencing for example) from a tumor DNA sample	File[]
tumor_per_target_hs_metrics	Sequencing coverage summary of target intervals from tumor DNA	Diagnosis/quality metrics for sequencing coverage for target intervals (optional, 59 genes recommended by ACMG for clinical exome and genome sequencing for example) from a tumor DNA sample	File[]
tumor_per_base_coverage_metrics	Sequencing per-base coverage summary at target sites from tumor DNA	Diagnosis/quality metrics showing detailed sequencing coverage per target site (optional, known variant sites of clinical significance from ClinVar for example) from a tumor DNA sample	File[]
tumor_per_base_hs_metrics	Sequencing coverage summary at target sites from tumor DNA	Diagnosis/quality metrics for sequencing coverage at target sites (optional, known variant sites of clinical significance from ClinVar for example) from a tumor DNA sample	File[]
tumor_summary_hs_metrics			File[]
tumor_flagstats	Sequencing count metrics based on SAM FLAG field from tumor sample	Summary with the count numbers of alignments for each FLAG type from a tumor DNA sample, including 13 categories based on the bit flags in the FLAG field	File
tumor_verify_bam_id_metrics	Sequencing quality assessment metric for tumor sample contamination	verifyBamID output files containing the contamination estimate in a tumor DNA sample, across all readGroups and per readGroup separately	File
tumor_verify_bam_id_depth	Sequencing quality assessment metric for tumor sample genotyping	verifyBamID output files showing the sequencing depth distribution at the marker positions from Omni genotype data with a tumor DNA sample, across all readGroups and per readGroup separately	File
normal_cram	Sorted CRAM from normal DNA	Sorted CRAM file of sequencing read alignments by bwa-mem from a normal DNA sample with duplicate reads tagged	File
normal_mark_duplicates_metrics	Sequencing duplicate metrics from normal DNA	Duplication metrics on duplicate sequencing reads from a normal DNA sample, identified by picard MarkDuplicates tool	File
normal_insert_size_metrics	Paired-end sequencing diagnosis/quality metrics from normal DNA	Diagnosis/quality metrics including the insert size distribution and read orientation of the paired-end libraries from a normal DNA sample	File
normal_alignment_summary_metrics	Sequencign alignment summary from normal DNA	Diagnosis/quality metrics summarizing the quality of sequencing read alignments from a normal DNA sample, reported by the picard CollectAlignmentSummaryMetrics tool	File
normal_hs_metrics	Sequencing coverage summary of target intervals from normal DNA	Diagnosis/quality metrics specific for sequencing data generated through hybrid-selection (e.g. whole exome) from a normal DNA sample, for example to assess target coverage	File
normal_per_target_coverage_metrics	Sequencing per-target coverage summary of target intervals from normal DNA	Diagnosis/quality metrics showing detailed sequencing coverage per target interval (optional, 59 genes recommended by ACMG for clinical exome and genome sequencing for example) from a normal DNA sample	File[]
normal_per_target_hs_metrics	Sequencing coverage summary of target intervals from normal DNA	Diagnosis/quality metrics for sequencing coverage for target intervals (optional, 59 genes recommended by ACMG for clinical exome and genome sequencing for example) from a normal DNA sample	File[]
normal_per_base_coverage_metrics	Sequencing per-base coverage summary at target sites from normal DNA	Diagnosis/quality metrics showing detailed sequencing coverage per target site (optional, known variant sites of clinical significance from ClinVar for example) from a normal DNA sample	File[]
normal_per_base_hs_metrics	Sequencing coverage summary at target sites from normal DNA	Diagnosis/quality metrics for sequencing coverage at target sites (optional, known variant sites of clinical significance from ClinVar for example) from a normal DNA sample	File[]
normal_summary_hs_metrics			File[]
normal_flagstats	Sequencing count metrics based on SAM FLAG field from normal sample	Summary with the count numbers of alignments for each FLAG type from a normal DNA sample, including 13 categories based on the bit flags in the FLAG field	File
normal_verify_bam_id_metrics	Sequencing quality assessment metric for normal sample contamination	verifyBamID output files containing the contamination estimate in a normal DNA sample, across all readGroups and per readGroup separately	File
normal_verify_bam_id_depth	Sequencing quality assessment metric for normal sample genotyping	verifyBamID output files showing the sequencing depth distribution at the marker positions from Omni genotype data with a normal DNA sample, across all readGroups and per readGroup separately	File
mutect_unfiltered_vcf			File	['.tbi']
mutect_filtered_vcf			File	['.tbi']
strelka_unfiltered_vcf			File	['.tbi']
strelka_filtered_vcf			File	['.tbi']
varscan_unfiltered_vcf			File	['.tbi']
varscan_filtered_vcf			File	['.tbi']
pindel_unfiltered_vcf			File	['.tbi']
pindel_filtered_vcf			File	['.tbi']
docm_filtered_vcf			File	['.tbi']
somatic_final_vcf			File	['.tbi']
final_filtered_vcf			File	['.tbi']
final_tsv			File
somatic_vep_summary			File
tumor_snv_bam_readcount_tsv			File
tumor_indel_bam_readcount_tsv			File
normal_snv_bam_readcount_tsv			File
normal_indel_bam_readcount_tsv			File
intervals_antitarget			File?
intervals_target			File?
normal_antitarget_coverage			File
normal_target_coverage			File
reference_coverage			File?
cn_diagram			File?
cn_scatter_plot			File?
tumor_antitarget_coverage			File
tumor_target_coverage			File
tumor_bin_level_ratios			File
tumor_segmented_ratios			File
diploid_variants			File?	['.tbi']
somatic_variants			File?	['.tbi']
all_candidates			File	['.tbi']
small_candidates			File	['.tbi']
tumor_only_variants			File?	['.tbi']
somalier_concordance_metrics			File
somalier_concordance_statistics			File
cram			File
mark_duplicates_metrics			File
insert_size_metrics			File
insert_size_histogram			File
alignment_summary_metrics			File
hs_metrics			File
per_target_coverage_metrics			File[]
per_target_hs_metrics			File[]
per_base_coverage_metrics			File[]
per_base_hs_metrics			File[]
summary_hs_metrics			File[]
flagstats			File
verify_bam_id_metrics			File
verify_bam_id_depth			File
germline_raw_vcf			File	['.tbi']
germline_final_vcf			File	['.tbi']
germline_filtered_vcf			File	['.tbi']
germline_vep_summary			File
optitype_tsv			File
optitype_plot			File
phased_vcf			File	['.tbi']
allele_string			string[]
consensus_alleles			string[]
hla_call_files			Directory
annotated_vcf			File
annotated_tsv			File
pvacseq_predictions			Directory
pvacfuse_predictions			Directory
unaligned_normal_dna_fastqc_data			File[]
unaligned_normal_dna_table_metrics			File[]
unaligned_normal_dna_md5sums			File
unaligned_normal_dna_table1			File
unaligned_tumor_dna_fastqc_data			File[]
unaligned_tumor_dna_table_metrics			File[]
unaligned_tumor_dna_md5sums			File
unaligned_tumor_dna_table1			File
unaligned_tumor_rna_fastqc_data			File[]
unaligned_tumor_rna_table_metrics			File[]
unaligned_tumor_rna_md5sums			File
unaligned_tumor_rna_table1			File
aligned_normal_dna_fastqc_data			File[]
aligned_normal_dna_table_metrics			File
aligned_normal_dna_md5sums			File
aligned_normal_dna_table2			File
aligned_tumor_dna_fastqc_data			File[]
aligned_tumor_dna_table_metrics			File
aligned_tumor_dna_md5sums			File
aligned_tumor_dna_table2			File
aligned_tumor_rna_fastqc_data			File[]
aligned_tumor_rna_table_metrics			File
aligned_tumor_rna_md5sums			File
aligned_tumor_rna_table3			File

Steps

Name	CWL Run
rnaseq	pipelines/rnaseq_star_fusion.cwl
somatic	pipelines/somatic_exome.cwl
germline	pipelines/germline_exome_hla_typing.cwl
fda_metrics	subworkflows/generate_fda_metrics.cwl
phase_vcf	subworkflows/phase_vcf.cwl
extract_alleles	tools/extract_hla_alleles.cwl
hla_consensus	tools/hla_consensus.cwl
intersect_passing_variants	tools/intersect_known_variants.cwl
pvacseq	subworkflows/pvacseq.cwl
pvacfuse	tools/pvacfuse.cwl