The VAAST Variant Prioritizer (VVP): ultrafast, easy to use whole genome variant prioritization tool

Abstract

BackgroundPrioritization of sequence variants for diagnosis and discovery of Mendelian diseases is challenging, especially in large collections of whole genome sequences (WGS). Fast, scalable solutions are needed for discovery research, for clinical applications, and for curation of massive public variant repositories such as dbSNP and gnomAD. In response, we have developed VVP, the VAAST Variant Prioritizer. VVP is ultrafast, scales to even the largest variant repositories and genome collections, and its outputs are designed to simplify clinical interpretation of variants of uncertain significance.ResultsWe show that scoring the entire contents of dbSNP (> 155 million variants) requires only 95 min using a machine with 4 cpus and 16 GB of RAM, and that a 60X WGS can be processed in less than 5 min. We also demonstrate that VVP can score variants anywhere in the genome, regardless of type, effect, or location. It does so by integrating sequence conservation, the type of sequence change, allele frequencies, variant burden, and zygosity. Finally, we also show that VVP scores are consistently accurate, and easily interpreted, traits not shared by many commonly used tools such as SIFT and CADD.ConclusionsVVP provides rapid and scalable means to prioritize any sequence variant, anywhere in the genome, and its scores are designed to facilitate variant interpretation using ACMG and NHS guidelines. These traits make it well suited for operation on very large collections of WGS sequences.Electronic supplementary materialThe online version of this article (10.1186/s12859-018-2056-y) contains supplementary material, which is available to authorized users.

De novo and recessive forms of congenital heart disease have distinct genetic and phenotypic landscapes

“…The 2391 trios were analyzed as trios using the VAAST Variant Prioritizer (VVP) 35 and VAAST burden tests. A typical VVP command was: VVP -d vvp_v2_background/1KG.050417.vvp.db -i 1-00004.vcf.gz -v CSQ,3,6,0,15 -c -n 1 -o 1-00004.scored_variants.out>1-00004_VVP.out.…”

“…In contrast, we identified many more candidate recessive genotypes on average, 1.3 proband −1 , compared to 0.2 proband −1 reported previously 3 . The increased numbers result from VAAST’s ability to identity compound heterozygous genotypes for which the combined burden of two moderately damaging variants is equal to that of a single, severely damaging de novo variant 19,20,35,36 . By contrast, the PCGC’s previously reported recessive genotypes 3 were restricted solely to cases for which both variants were loss-of-function alleles or missense variants predicted to be maximally damaging by MetaSVM.…”

Deep whole genome sequencing of multiple proband tissues and parental blood reveals the complex genetic etiology of congenital diaphragmatic hernias

“…As a background population, a VCF file with variants from 1000 Genomes phase 3 [74] were run through the same workflow. A VVP background database was made from the 1000 Genome filtered variants using the build_background function of VVP [121]. This background database and the filtered VCF file of variants discovered in this cohort were used as inputs to VVP to prioritize cohortdiscovered variants, which were then passed to VAAST3 to be scored and ranked.…”

FREQMAX provides an alternative approach for determining high‐resolution allele frequency thresholds in carrier screening

“…Furthermore, the overwhelming majority of VOUS alleles are believed to be benign (Pelak et al, 2010). Thus, the ability to efficiently identify benign variants among a set of VOUS alleles, without requiring the resource‐intensive process of manual downstream review, has been a recent focus of several genetic test providers and genetic studies (Bosio et al, 2019; Chen, 2019; Du et al, 2019; Flygare et al, 2018; Padilla et al, 2019; Ravichandran et al, 2019; Roca et al, 2018; Zhou & Zhao, 2018). Of the existing methods that are commonly used to identify benign variants, exclusion by allele frequency is among the most powerful and amenable to automation.…”