Statistical power of model selection strategies for genome-wide association studies.

ABSTRACT: Genome-wide association studies (GWAS) aim to identify genetic variants related to diseases by examining the associations between phenotypes and hundreds of thousands of genotyped markers. Because many genes are potentially involved in common diseases and a large number of markers are analyzed, it is crucial to devise an effective strategy to identify truly associated variants that have individual and/or interactive effects, while controlling false positives at the desired level. Although a number of model selection methods have been proposed in the literature, including marginal search, exhaustive search, and forward search, their relative performance has only been evaluated through limited simulations due to the lack of an analytical approach to calculating the power of these methods. Th

SUBMITTER: Wu Z 

PROVIDER: S-EPMC2712761 | biostudies-literature | 2009 Jul

REPOSITORIES: biostudies-literature