Skip to main content

GatherBatchEvidence

Runs CNV callers (cn.MOPS, GATK-gCNV) and combines single-sample raw evidence into a batch.

The following diagram illustrates the downstream workflows of the GatherBatchEvidence workflow in the recommended invocation order. You may refer to this diagram for the overall recommended invocation order.

Inputs​

This workflow takes as input the read counts, BAF, PE, SD, SR, and per-caller VCF files produced in the GatherSampleEvidence workflow, and contig ploidy and gCNV models from the TrainGCNV workflow. The following is the list of the inputs the GatherBatchEvidence workflow takes.

batch​

An identifier for the batch.

samples​

Sets the list of sample IDs.

counts​

Set to the GatherSampleEvidence.coverage_counts output.

Raw calls​

The following inputs set the per-caller raw SV calls, and should be set if the caller was run in the GatherSampleEvidence workflow. You may set each of the following inputs to the linked output from the GatherSampleEvidence workflow.

PE_files​

Set to the GatherSampleEvidence.pesr_disc output.

SR_files​

Set to the GatherSampleEvidence.pesr_split

SD_files​

Set to the GatherSampleEvidence.pesr_sd

matrix_qc_distance​

You may refer to this file for an example value.

min_svsize​

Sets the minimum size of SVs to include.

ped_file​

A pedigree file describing the familial relationshipts between the samples in the cohort. Please refer to this section for details.

run_matrix_qc​

Enables or disables running optional QC tasks.

gcnv_qs_cutoff​

You may refer to this file for an example value.

cn.MOPS files​

The workflow needs the following cn.MOPS files.

  • cnmops_chrom_file and cnmops_allo_file: FASTA index files (.fai) for respectively non-sex chromosomes (autosomes) and chromosomes X and Y (allosomes). The file format is explained on this page.

    You may use the following files for these fields:

    "cnmops_chrom_file": "gs://gcp-public-data--broad-references/hg38/v0/sv-resources/resources/v1/autosome.fai"
    "cnmops_allo_file": "gs://gcp-public-data--broad-references/hg38/v0/sv-resources/resources/v1/allosome.fai"

  • cnmops_exclude_list: You may use this file for this field.

GATK-gCNV inputs​

The following inputs are configured based on the outputs generated in the TrainGCNV workflow.

The workflow also enables setting a few optional arguments of gCNV. The arguments and their default values are provided here as the following, and each argument is documented on this page and this page.

Docker images​

The workflow needs the following Docker images, the latest versions of which are in this file.

  • cnmops_docker;
  • condense_counts_docker;
  • linux_docker;
  • sv_base_docker;
  • sv_base_mini_docker;
  • sv_pipeline_docker;
  • sv_pipeline_qc_docker;
  • gcnv_gatk_docker;
  • gatk_docker.

Static inputs​

You may refer to this reference file for values of the following inputs.

  • primary_contigs_fai;
  • cytoband;
  • ref_dict;
  • mei_bed;
  • genome_file;
  • sd_locs_vcf.

Optional Inputs​

The following is the list of a few optional inputs of the workflow, with an example of possible values.

  • "allosomal_contigs": [["chrX", "chrY"]]
  • "ploidy_sample_psi_scale": 0.001

Outputs​

  • Combined read count matrix, SR, PE, and BAF files
  • Standardized call VCFs
  • Depth-only (DEL/DUP) calls
  • Per-sample median coverage estimates
  • (Optional) Evidence QC plots