Methods for the Analysis and Interpretation for Rare Variants Associated with Complex Traits. (8th March 2019)

• Record Type: Journal Article
• Authors: Weissenkampen, J. Dylan; Jiang, Yu; Eckert, Scott; Jiang, Bibo; Li, Bingshan; Liu, Dajiang J.
• Editors: Dracopoli, Nicholas C.; 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 101(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-03-08
• Subjects: genetic association -- genome sequencing -- GWAS -- PheWAS -- rare variant -- complex traits; Human genetics -- Laboratory manuals; Genetic Techniques; Human genetics; Laboratory manuals; 599.935028
• DOI: 10.1002/cphg.83
• Languages: English
• ISSNs: 1934-8258

Abstract

Abstract: With the advent of Next Generation Sequencing (NGS) technologies, whole genome and whole exome DNA sequencing has become affordable for routine genetic studies. Coupled with improved genotyping arrays and genotype imputation methodologies, it is increasingly feasible to obtain rare genetic variant information in large datasets. Such datasets allow researchers to gain a more complete understanding of the genetic architecture of complex traits caused by rare variants. State‐of‐the‐art statistical methods for the statistical genetics analysis of sequence‐based association, including efficient algorithms for association analysis in biobank‐scale datasets, gene‐association tests, meta‐analysis, fine mapping methods that integrate functional genomic dataset, and phenome‐wide association studies (PheWAS), are reviewed here. These methods are expected to be highly useful for next generation statistical genetics analysis in the era of precision medicine. © 2019 by John Wiley & Sons, Inc.