A MONTE-CARLO METHOD FOR BAYESIAN-ANALYSIS OF LINKAGE BETWEEN SINGLE MARKERS AND QUANTITATIVE TRAIT LOCI .1. METHODOLOGY

A Bayesian approach to the statistical mapping of Quantitative Trait L oci (QTLs) using single markers was implemented via Markov Chain Monte Carlo (MCMC) algorithms for parameter estimation and hypothesis testi ng. Parameter estimators were marginal posterior means computed using a Gibbs sampler with data augmentation. Variables sampled included the augmented data (marker-QTL genotypes, polygenic effects), an indicato r variable for linkage, and the parameters (allele frequency, QTL subs titution effect, recombination rate, polygenic and residual variances) . Several MCMC algorithms were derived for computing Bayesian tests of linkage, which consisted of the marginal posterior probability of lin kage and the marginal likelihood of the QTL variance associated with t he marker.