| Literature DB >> 23853079 |
Bingshan Li1, Dajiang J Liu, Suzanne M Leal.
Abstract
Although genome-wide association studies have been successful in detecting associations with common variants, there is currently an increasing interest in identifying low-frequency and rare variants associated with complex traits. Next-generation sequencing technologies make it feasible to survey the full spectrum of genetic variation in coding regions or the entire genome. The association analysis for rare variants is challenging, and traditional methods are ineffective, however, due to the low frequency of rare variants, coupled with allelic heterogeneity. Recently a battery of new statistical methods has been proposed for identifying rare variants associated with complex traits. These methods test for associations by aggregating multiple rare variants across a gene or a genomic region or among a group of variants in the genome. In this unit, we describe key concepts for rare variant association for complex traits, survey some of the recent methods, discuss their statistical power under various scenarios, and provide practical guidance on analyzing next-generation sequencing data for identifying rare variants associated with complex traits. 2013 by John Wiley & Sons, Inc.Entities:
Mesh:
Year: 2013 PMID: 23853079 PMCID: PMC3830981 DOI: 10.1002/0471142905.hg0126s78
Source DB: PubMed Journal: Curr Protoc Hum Genet ISSN: 1934-8258