Using VAAST to Identify Disease‐Associated Variants in Next‐Generation Sequencing Data. (24th April 2014)

• Record Type: Journal Article
• Authors: Kennedy, Brett; Kronenberg, Zev; Hu, Hao; Moore, Barry; Flygare, Steven; Reese, Martin G.; Jorde, Lynn B.; Yandell, Mark; Huff, Chad
• Editors: Haines, Jonathan L.; Korf, Bruce R.; Morton, Cynthia C.; Seidman, Christine E.; Seidman, J.G.; Smith, Douglas R.
• Is Part Of: Current protocols in human genetics. Volume 81(2014)
• Page Start: 6.14.1
• Page End: 6.14.25
• Publication Date: 2014-04-24
• Subjects: VAAST -- rare‐variant association test -- variant classification -- disease‐gene identification -- next‐generation sequencing -- genome‐wide association studies -- human disease -- genomics -- computational genomics -- bioinformatics; Human genetics -- Laboratory manuals; Genetic Techniques; Human genetics; Laboratory manuals; 599.935028
• DOI: 10.1002/0471142905.hg0614s81
• Languages: English
• ISSNs: 1934-8258

Abstract

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. Curr. Protoc. Hum. Genet . 81:6.14.1‐6.14.25. © 2014 by John Wiley & Sons, Inc.