Mary Sara McPeek : X-chromosome Genetic Association Analysis with Related Individuals

Posted by Jie Yang , part of the Statistics and Data Science Seminar.

At

Oct. 5, 2011, 4 p.m.

In

SEO 636

Abstract

Common diseases such as asthma, diabetes, and hypertension, which currently account for a large portion of the health care burden, are complex in the sense that they are influenced by many factors, both environmental and genetic. One fundamental problem of interest is to understand what the genetic risk factors are that predispose some people to get a particular complex disease. Despite the potential for complex traits to have X-linked causal genes, genetic association methods have primarily been developed for the analysis of markers on the autosomal chromosomes, and significantly less attention has been given to analyzing X-linked markers. We develop methods for case-control association testing of X-chromosome variants in samples in which some individuals are related. Our methods are applicable to association studies with completely general combinations of family and case-control designs, including large complex pedigrees. Even in the context of large complex pedigrees, the methods are computationally feasible for analysis of millions of variants. We allow for sex-specific prevalence, and we allow both unaffected controls and controls of unknown phenotype in the analysis. We discuss some of the distinct challenges posed by X-chromosome association analysis in contrast to autosomal association analysis. We discuss the performance of the methods in the context of several data sets as well as in simulations.