Epistatic module detection for case-control studies: a Bayesian model with a Gibbs sampling strategy.

ABSTRACT: The detection of epistatic interactive effects of multiple genetic variants on the susceptibility of human complex diseases is a great challenge in genome-wide association studies (GWAS). Although methods have been proposed to identify such interactions, the lack of an explicit definition of epistatic effects, together with computational difficulties, makes the development of new methods indispensable. In this paper, we introduce epistatic modules to describe epistatic interactive effects of multiple loci on diseases. On the basis of this notion, we put forward a Bayesian marker partition model to explain observed case-control data, and we develop a Gibbs sampling strategy to facilitate the detection of epistatic modules. Comparisons of the proposed approach with three existing methods on

SUBMITTER: Tang W 

PROVIDER: S-EPMC2669883 | biostudies-literature | 2009 May

REPOSITORIES: biostudies-literature