title: Measuring gametic disequilibrium from multilocus data.
abstract: We describe a Bayesian approach to analyzing multilocus genotype or haplotype data to assess departures from gametic (linkage) equilibrium. Our approach employs a Markov chain Monte Carlo (MCMC) algorithm to approximate the posterior probability distributions of disequilibrium parameters. The distributions are computed exactly in some simple settings. Among other advantages, posterior distributions can be presented visually, which allows the uncertainties in parameter estimates to be readily assessed. In addition, background knowledge can be incorporated, where available, to improve the precision of inferences. The method is illustrated by application to previously published datasets; implications for multilocus forensic match probabilities and for simple association-based gene mapping are also discussed.
authors.affiliation: Department of Applied Statistics, University of Reading, Reading RG6 6FN, United Kingdom.
authors.forename: K L
authors.initials: KL
authors.lastname: Ayres
authors.forename: D J
authors.initials: DJ
authors.lastname: Balding
mesh_terms: D000465:Algorithms; D000483:Alleles; D001499:Bayes Theorem; D003627:Data Interpretation, Statistical; D005554:Forensic Medicine; D005838:Genotype; D006239:Haplotypes; D006801:Humans; D015810:Linkage Disequilibrium; D008390:Markov Chains; D008957:Models, Genetic; D009010:Monte Carlo Method