A Bayesian approach to multipoint mapping in nuclear families.

We describe the application of a Markov Chain Monte Carlo approach for multipoint mapping of a quantitative trait locus to the Nuclear Families simulated data. The method involves repeated sampling of genotype vectors for each nuclear family from their conditional distributions, given phenotypes, markers, and model parameters, using peeling and gene dropping, followed by random sampling of each model parameter given genotypes and the other parameters. Reversible jump methods are used to sample the number of trait loci.