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Structural variant VCF annotation, duplicate removal and comparison

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Sansa

Structural variant (SV) annotation.

Installation

The easiest way to get sansa is to download a statically linked binary from the sansa github release page or using bioconda.

conda install -c bioconda sansa

You can also build sansa from source using a recursive clone and make.

git clone --recursive https://github.com/dellytools/sansa.git

cd sansa/

make all

Usage

Sansa has several subcommands

sansa annotate for SV annotation

sansa markdup to mark duplicate SV sites in a multi-sample VCF file

sansa compvcf to compare multi-sample VCF files

SV annotation

Download an annotation database. Examples are gnomAD-SV or 1000 Genomes phase 3 and then run the annotation.

sansa annotate -d gnomad_v2.1_sv.sites.vcf.gz input.vcf.gz

The method generates two output files: anno.bcf with annotation SVs augmented by a unique ID (INFO/ANNOID) and query.tsv.gz with query SVs matched to annotation IDs.

bcftools can be used to extract all INFO fields you want as annotation. For instance, let's annotate with the VCF ID and EUR_AF for the European allele frequency in gnomad-SV. Always include INFO/ANNOID as the first column.

bcftools query -H -f "%INFO/ANNOID\t%ID\t%INFO/EUR_AF\n" anno.bcf | sed -e 's/^# //' > anno.tsv

Last is a simple join of query SVs with matched database SVs based on the first column (ANNOID).

join anno.tsv <(zcat query.tsv.gz | sort -k 1b,1) > results.tsv

SV annotation parameters

Sansa matches SVs based on the absolute difference in breakpoint locations (-b) and the size ratio (-r) of the smaller SV compared to the larger SV. By default, the SVs need to have their start and end breakpoint within 50bp and differ in size by less than 20% (-r 0.8).

sansa annotate -b 50 -r 0.8 -d gnomad_v2.1_sv.sites.vcf.gz input.vcf.gz

By default, sansa only reports the best matching SVs. You can change the matching strategy to all using -s.

sansa annotate -s all -d gnomad_v2.1_sv.sites.vcf.gz input.vcf.gz

You can also include unmatched query SVs in the output using -m.

sansa annotate -m -d gnomad_v2.1_sv.sites.vcf.gz input.vcf.gz

By default, SVs are only compared within the same SV type (DELs with DELs, INVs with INVs, and so on). For delly this comparison is INFO/CT aware. You can deactivate this SV type check using -n.

sansa annotate -n -d gnomad_v2.1_sv.sites.vcf.gz input.vcf.gz

Feature/Gene annotation

Based on a distance cutoff (-t) sansa matches SVs to nearby genes. The gene annotation file can be in gtf/gff2 or gff3 format.

sansa annotate -g Homo_sapiens.GRCh37.87.gtf.gz input.vcf.gz

sansa annotate -i Name -g Homo_sapiens.GRCh37.87.gff3.gz input.vcf.gz

The output has 2 columns for genes near the SV start breakpoint and genes near the SV end breakpoint. For each gene, the output lists the gene name and in paranthesis the distance (negative values: before SV breakpoint, 0: SV breakpoint within gene, positive values: after SV breakpoint) and the strand of the gene (+/-/*).

You can also use the Ensembl gene id or annotate exons instead of genes.

sansa annotate -i gene_id -g Homo_sapiens.GRCh37.87.gff3.gz input.vcf.gz

sansa annotate -f exon -i exon_id -g Homo_sapiens.GRCh37.87.gff3.gz input.vcf.gz

Gene and SV annotation can be run in a single command.

sansa annotate -g Homo_sapiens.GRCh37.87.gtf.gz -d gnomad_v2.1_sv.sites.vcf.gz input.vcf.gz

Discovering gene fusion candidates

Using delly and the INFO/CT values one can identify gene fusion candidates. Here is the mapping from gene strand to CT values with classical cancer genomics examples (GRCh37 coordinates).

chr start chr2 end svtype ct startfeature endfeature
chrA posStart chrA posEnd INV 3to3 geneA(0;+) geneB(0;-)
chrA posStart chrA posEnd INV 3to3 geneC(0;-) geneD(0;+)
10 89672219 10 90267336 INV 3to3 PTEN(0;+) RNLS(0;-)
chrA posStart chrA posEnd DEL 3to5 geneA(0;+) geneB(0;+)
chrA posStart chrA posEnd DEL 3to5 geneC(0;-) geneD(0;-)
21 39887792 21 42869743 DEL 3to5 ERG(0;-) TMPRSS2(0;-)
chrA posStart chrA posEnd DUP 5to3 geneA(0;+) geneB(0;+)
chrA posStart chrA posEnd DUP 5to3 geneC(0;-) geneD(0;-)
7 138547350 7 140491430 DUP 5to3 KIAA1549(0;-) BRAF(0;-)
chrA posStart chrA posEnd INV 5to5 geneA(0;+) geneB(0;-)
chrA posStart chrA posEnd INV 5to5 geneC(0;-) geneD(0;+)
8 32139712 8 33359541 INV 5to5 NRG1(0;+) TTI2(0;-)
chrA posA chrB posB BND 3to3 geneA(0;+) geneB(0;-)
chrA posA chrB posB BND 3to3 geneC(0;-) geneD(0;+)
14 68316364 5 58914908 BND 3to3 RAD51B(0;+) PDE4D(0;-)
chrA posA chrB posB BND 3to5 geneA(0;+) geneB(0;+)
chrA posA chrB posB BND 3to5 geneC(0;-) geneD(0;-)
21 42867595 7 14027003 BND 3to5 TMPRSS2(0;-) ETV1(0;-)
chrA posA chrB posB BND 5to3 geneA(0;+) geneB(0;+)
chrA posA chrB posB BND 5to3 geneC(0;-) geneD(0;-)
21 39826990 1 205637229 BND 5to3 ERG(0;-) SLC45A3(0;-)
chrA posA chrB posB BND 5to5 geneA(0;+) geneB(0;-)
chrA posA chrB posB BND 5to5 geneC(0;-) geneD(0;+)
3 169190498 2 47689038 BND 5to5 MECOM(0;-) MSH2(0;+)

Mark duplicates

For larger studies that employ single sample calling and then merge SVs across samples a common problem is to identify duplicate SV sites that occur due to SV breakpoint imprecisions. sansa markdup identifies duplicates sites based on genomic proximity, genotype concordance and SV allele similarity. By default, duplicate SVs need to have SV breakpoints within 50bp (-b 50), a reciprocal overlap of 80% (-s 0.8), a maximum SV allele divergence of 10% (-s 0.1) and a minimum fraction of shared SV carriers of 25% (-c 0.25). The SV allele comparison requires delly's INFO/CONSENSUS field as the SV haplotype.

sansa markdup -o rmdup.bcf pop.delly.bcf

Compare VCFs

Compare an input VCF/BCF file to a ground truth (base) VCF/BCF file.

sansa compvcf -a base.bcf input.bcf

To compare SV site lists that lack genotypes, you need to set the minimum allele count to zero (-e 0).

sansa compvcf -a base.bcf -e 0 input.bcf

Citation

Tobias Rausch, Thomas Zichner, Andreas Schlattl, Adrian M. Stuetz, Vladimir Benes, Jan O. Korbel.
DELLY: structural variant discovery by integrated paired-end and split-read analysis.
Bioinformatics. 2012 Sep 15;28(18):i333-i339.
https://doi.org/10.1093/bioinformatics/bts378

License

Sansa is distributed under the BSD 3-Clause license. Consult the accompanying LICENSE file for more details.