? The genetic analysis of complex traits is one of the major challenges facing biomedical researchers today. These traits are often common in the population and, hence, account for a large portion of the health care burden. Their manifestation is the result of numerous factors, both genetic and environmental, that often interact in complex ways, making the identification of risk factors extremely difficult. Novel genetic mapping techniques that take advantage of the study design and use the maximal amount of available data may prove instrumental in identifying and characterizing the genetic components of the traits. ? ? The long-term objective of the proposed research is to develop statistical methods for genetic mapping and analysis of complex traits in humans. We focus primarily on methods that can be applied to large, complex pedigrees and isolated, founder populations. While such pedigrees and populations may be efficacious for the identification of genes that influence complex traits, their analysis poses significant statistical and computational challenges. While the methods we propose are designed with large, complex pedigrees in mind, they are also applicable to the smaller family studies that are also common. In this proposal we outline four closely related aims for gene mapping in large pedigrees: (1) Develop a model for qualitative trait mapping that includes covariate adjustment and properly accounts for relatedness among the individuals in the study sample and apply this model as an extension to our quantitative trait homozygosity mapping study; (2) Develop an algorithm for the computation of bilocus identity coefficients for arbitrary relative pairs unconditional on genotype data and extensions to the algorithm that will allow efficient computation of conditional identity by descent probabilities given multipoint genotype data; (3) Extend our homozygosity mapping method for quantitative traits to include the identification of genes that follow general genetic models and account for such effects as epistasis and gene by environment interaction; and (4) Develop extensions to our QTL mapping method to (a) include greater use of available genotype data and (b) allow our novel permutation based test to be applicable under a wider range of phenotype distributions. ? ?
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