COMPUTATIONAL METHODS IN GENETIC EPIDEMIOLOGY

University Of Southern California, Los Angeles CA

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Abstract

In this grant, we propose to focus further work on computational problems in gene mapping studies, with particular emphasis on finding genes for complex traits combining linkage and linkage disequilibrium information. Combining research forces at both the University of Southern California (USC) and the Fred Hutchinson Cancer Research Center (FHCRC), we propose to explore the following approaches for joint linkage and linkage disequilibrium analysis: Maximum likelihood methods using both empirical models for disequilibrium and population genetics models for isolated and admixed populations. Efficient Estimating Equations (EEE) methods for semi-parametric analysis MCMC methods for larger pedigrees than are currently feasible.