Case-Control Genome-wide Joint Association Study Using Semiparametric Empirical Model and Approximate Bayes Factor.

ABSTRACT: We propose a semiparametric approach for the analysis of case-control genome-wide association study. Parametric components are used to model both the conditional distribution of the case status given the covariates and the distribution of genotype counts, whereas the distribution of the covariates are modeled nonparametrically. This yields a direct and joint modeling of the case status, covariates and genotype counts, and gives better understanding of the disease mechanism and results in more reliable conclusions. Side information, such as the disease prevalence, can be conveniently incorporated into the model by empirical likelihood approach and leads to more efficient estimates and powerful test in the detection of disease-associated SNPs. Profiling is used to eliminate a nuisance nonpar

SUBMITTER: Xu J 

PROVIDER: S-EPMC3921884 | biostudies-literature | 2013 Jan

REPOSITORIES: biostudies-literature