Localization of a quantitative trait locus via a Bayesian approach

A Bayesian approach to the direct mapping of a quantitative trait locus (QT L), fully utilizing information from multiple linked gene markers, is prese nted in this paper. The joint posterior distribution (a mixture distributio n modeling the linkage between a biallelic QTL and N gene markers) is compu tationally challenging and invites exploration via Markov chain Monte Carlo methods. The parameter's complete marginal posterior densities are obtaine d, allowing a diverse range of inferences. Parameters estimated include the QTL genotype probabilities for title sires and the offspring, the allele f requencies for the QTL, and the position and additive and dominance effects of the QTL. The methodology is applied through simulation to a half-sib de sign to form an outbred pedigree structure where there is an entire class o f missing information. The capacity of the technique to accurately estimate parameters is examined for a range of scenarios.