Bayesian models for population-based case-control studies when the population is in Hardy-Weinberg equilibrium.

Abstract

Association analysis of genetic polymorphisms has been mostly performed in a case-control setting with unrelated affected subjects compared with unrelated unaffected subjects. In this paper, we present a Bayesian method for analyzing such case-control data when the population is in Hardy-Weinberg equilibrium. Our Bayesian method depends on the informative prior which is the retrospective likelihood based on historical data, raised to a power a. By modeling the retrospective likelihood properly, different prior information about the studied population can be incorporated into the specification of the prior. The scalar a is a precision parameter quantifying the heterogeneity between current and historical data. A guide value for a is discussed in this paper. The informative prior and posterior distributions are proper under very general conditions. Therefore, our method can be applied in most case-control studies. Further, for assessing gene-environment interactions, our approach will naturally lead to a Bayesian model depending only on the case data, when genotype and environmental factors are independent in the population. Thus our approach can be applied to case-only studies. A real example is used to show the applications of our method.