Bayesian mixture modeling of gene-environment and gene-gene interactions.

ABSTRACT: With the advent of rapid and relatively cheap genotyping technologies there is now the opportunity to attempt to identify gene-environment and gene-gene interactions when the number of genes and environmental factors is potentially large. Unfortunately the dimensionality of the parameter space leads to a computational explosion in the number of possible interactions that may be investigated. The full model that includes all interactions and main effects can be unstable, with wide confidence intervals arising from the large number of estimated parameters. We describe a hierarchical mixture model that allows all interactions to be investigated simultaneously, but assumes the effects come from a mixture prior with two components, one that reflects small null effects and the second for epidemi

SUBMITTER: Wakefield J 

PROVIDER: S-EPMC2796715 | biostudies-literature | 2010 Jan

REPOSITORIES: biostudies-literature