We are a quantitative genetics lab interested the relationship between genes and complex disease. Most of our work focuses on developing statistical and computational techniques for the design and analysis of genetic experiments in animal models. This includes, for example: Bayesian hierarchical modeling of gene by drug effects in crosses of inbred mouse strains; statistical methods for identifying quantitative trait loci (QTL) in a variety of experimental mouse populations (including the Collaborative Cross); computational methods for optimal design of studies on parent of origin effects; modeling of diet by gene by parentage interactions that affecting psychiatric disease; detection and estimation of genetic effects on phenotypic variability. For more information, visit the lab website.