Statistics and Data Science Seminar
Mary Sara McPeek
University of Chicago
X-chromosome Genetic Association Analysis with Related Individuals
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.
Wednesday October 5, 2011 at 4:00 PM in SEO 636