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Curr Protoc Hum Genet. 2014 Apr 24;81:6.14.1-25. doi: 10.1002/0471142905.hg0614s81.

Using VAAST to Identify Disease-Associated Variants in Next-Generation Sequencing Data.

Author information

1
Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, Utah; These authors collectively are the first authors of the unit.

Abstract

The VAAST pipeline is specifically designed to identify disease-associated alleles in next-generation sequencing data. In the protocols presented in this paper, we outline the best practices for variant prioritization using VAAST. Examples and test data are provided for case-control, small pedigree, and large pedigree analyses. These protocols will teach users the fundamentals of VAAST, VAAST 2.0, and pVAAST analyses.

KEYWORDS:

VAAST; bioinformatics; computational genomics; disease-gene identification; genome-wide association studies; genomics; human disease; next-generation sequencing; rare-variant association test; variant classification

PMID:
24763993
PMCID:
PMC4137768
DOI:
10.1002/0471142905.hg0614s81
[Indexed for MEDLINE]
Free PMC Article
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