Variant Annotation, Analysis and Search Tool - VAAST 2
VAAST 2 (the Variant Annotation, Analysis & Search Tool) is a probabilistic search tool for identifying damaged genes and their disease-causing variants in personal genome sequences. VAAST 2 builds upon existing phylogenetic conservation, amino acid substitution (AAS) and aggregative approaches to variant prioritization, combining elements of all into a single unified likelihood-framework that allows users to identify damaged genes and deleterious variants with greater accuracy, and in an easy-to-use fashion. VAAST 2 can score both coding (SNV, indel and splice site) and non-coding variants (SNV), evaluating the cumulative impact of both types of variants simultaneously. VAAST 2 can identify rare variants causing rare genetic diseases, and it can also use both rare and common variants to identify genes responsible for common diseases. VAAST 2 thus has a much greater scope of use than any existing methodology to prioritize candidate disease genes in sets of unlreated affected genome sequences.
Pedigree VAAST - pVAAST
High-throughput sequencing of related individuals has become an important tool for studying human disease. However, owing to technical complexity and lack of available tools, most pedigree-based sequencing studies rely on an ad hoc combination of suboptimal analyses. Pedigree-VAAST (pVAAST) is a disease-gene identification tool designed for high-throughput sequence data in pedigrees. pVAAST uses a sequence-based model to perform variant and gene-based linkage analysis. Linkage information is then combined with functional prediction and rare variant case-control association information in a unified statistical framework. The approach is robust to incomplete penetrance and locus heterogeneity and is applicable to a wide variety of genetic traits. pVAAST maintains high power across studies of monogenic, high-penetrance phenotypes in a single pedigree to highly polygenic, common phenotypes involving hundreds of pedigrees.
The VAAST package consists of four primary tools:
- VAT: The Variant Annotation Tool calculates a rich set of annotations on the effects that variants have on genomic features based on terms described and constrained by the Sequence Ontology. These effects, like synonymous and missense changes, stop-gain and loss, splice site variants and others that provide additional information about the functional effect of a variant, which VAAST 2 uses to score features.
- VST: The Variant Selection Tool performs set operations (intersection, union, complement, and difference) on a group of annotated GVF files to produce a merged representation of the group's variants in a CDR file. VST can be used to simply create a merged set of variants for the target or background genomes required as input to VAAST 2, but can also manufacture arbitrarily complex selections based on nested set operations.
- VAAST 2: A probabilistic search tool that uses the outputs of VAT and VST to identify damaged genes and their disease-causing variants in sets of unrelated personal genome sequences.
- pVAAST: Built on the VAAST 2 framework pVAAST is a disease-gene identification tool designed for high-throughput sequence data in pedigrees.
Note that another tool with the name VAT and similar functionality to VAAST's VAT was published recently by the Gerstein lab. You can access the Gerstein lab VAT on their web-site, however it's output is not compatible with VAAST 2.
- Matthew Herper - Forbes.com
- Salt Lake Tribune
- Ogden Standard Examiner
- Bio-It World 2012 Best Practices Awards
License & Downloads
VAAST/pVAAST is developed as a collaboration between the Yandell Lab at the University of Utah, the Huff Lab at MD Anderson Cancer Center and Omicia, Inc. of Oakland, CA. The University of Utah freely licenses VAAST 2 for academic research use. For commercial, clinical and all other uses please contact Martin Reese at Omicia, Inc.
- License and Download VAAST/pVAAST
- VAAST Quick Start Guide
- VAAST 2 User's Guide
- pVAAST User's Guide - Coming Soon!
- VAAST 2 Data Files
- VAAST 1 Data File (Archive)