University of Washington - Department of Statistics
Patterns of inheritance of genes on pedigrees underlie similarities among relatives, and hence approaches to the analysis of genetic data observed on related individuals. With modern genetic technology, data are often available for large numbers of genetic loci, sometimes on large sets of interrelated individuals. The space of underlying inheritance patterns consistent with the data is then not only huge, but also tightly constrained by the laws of genetics. Monte Carlo methods, including MCMC methods, have been developed to realize inheritance patterns of latent genes conditional on observed genetic marker data. While the constraints on the system pose severe difficulties in obtaining adequate samplers, combining several alternative samplers has led to major improvements. Monte Carlo realizations of latent inheritance patterns make possible the estimation of likelihoods on pedigrees and the analysis of genome sharing among relatives, jointly over relatives and over genetic loci. Such genome sharing analyses may be used in linkage detection, the determination of segregating pedigrees, and the identification of probable gene carriers.