title: 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.
authors.affiliation: Biostatistics Branch, Graduate Institute of Statistics, National Central University, Jhongli, Taiwan, ROC. kfcheng@cc.ncu.edu.tw
authors.forename: K F
authors.initials: KF
authors.lastname: Cheng
authors.forename: J H
authors.initials: JH
authors.lastname: Chen
mesh_terms: D001499:Bayes Theorem; D016022:Case-Control Studies; D003327:Coronary Disease / Q000235:genetics; D004781:Environmental Exposure; D020022:Genetic Predisposition to Disease; D005828:Genetics, Population; D005838:Genotype; D006801:Humans; D016013:Likelihood Functions; D008957:Models, Genetic; D012107:Research Design