SV Annotation Module¶
A Nextflow workflow which annotates a joint-called Structural Variant VCF with:
- gene consequences, using GATK
SVAnnotateagainst the MANE GTF - population allele frequencies, using SVAFotate against gnomAD-SV
This is a re-implementation of the same core steps we (CPG) use internally. Our internal usage centres around the GATK-SV workflow, and our CPG-Flow wrapped implementation of it. The terminal stage of this workflow is Annotation, which is done using GATK's SvAnnotate tool for consequence prediction, and a complex interval-overlap-resolution step to match variants to gnomAD frequencies.
Instead of re-implementing the exact process here, I've split the annotation into two phases:
- Consequence: handled using SVAnnotate, and exact replica of the GATK-SV process
- Pop.Freq: handled using SVAFotate
These two steps, and pre-processing of relevant input files, are engaged only if an SV file is included in the input TSV file, with the same core conceit as small variants and Mito data - a single joint-called VCF should contain the whole group of Samples being processed, which should also match the Pedigree and Small-variant data.
A separate sub-workflow, SV_ANNOTATION has been created to handle these steps. SV_ANNOTATION publishes an annotated
VCF per cohort, RunSmallFilteringSv filters and labels it with CategoryBooleanSV1, and ValidateMOI folds the result
into the report.
To utilise this functionality, add a sv column to the input TSV, pointing to a SV joint-call. This has been tested on
the output of GATK-SV (multiple variant callers, with resolved calls) and GATK's gCNV.