BAYESIAN METHODS FOR GENETIC ASSOCIATION ANALYSIS WITH HETEROGENEOUS SUBGROUPS: FROM META-ANALYSES TO GENE-ENVIRONMENT INTERACTIONS.

ABSTRACT: Genetic association analyses often involve data from multiple potentially-heterogeneous subgroups. The expected amount of heterogeneity can vary from modest (e.g. a typical meta-analysis), to large (e.g. a strong gene-environment interaction). However, existing statistical tools are limited in their ability to address such heterogeneity. Indeed, most genetic association meta-analyses use a "fixed effects" analysis, which assumes no heterogeneity. Here we develop and apply Bayesian association methods to address this problem. These methods are easy to apply (in the simplest case, requiring only a point estimate for the genetic effect, and its standard error, from each subgroup), and effectively include standard frequentist meta-analysis methods, including the usual "fixed effects" analysis,

SUBMITTER: Wen X 

PROVIDER: S-EPMC4583155 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature