title: MCMC multilocus lod scores: application of a new approach.
abstract: On extended pedigrees with extensive missing data, the calculation of multilocus likelihoods for linkage analysis is often beyond the computational bounds of exact methods. Growing interest therefore surrounds the implementation of Monte Carlo estimation methods. In this paper, we demonstrate the speed and accuracy of a new Markov chain Monte Carlo method for the estimation of linkage likelihoods through an analysis of real data from a study of early-onset Alzheimer's disease. For those data sets where comparison with exact analysis is possible, we achieved up to a 100-fold increase in speed. Our approach is implemented in the program lm_bayes within the framework of the freely available MORGAN 2.6 package for Monte Carlo genetic analysis (http://www.stat.washington.edu/thompson/Genepi/MORGAN/Morgan.shtml).
authors.affiliation: Department of Statistics, University of Washington, Seattle, WA 98195, USA.
authors.forename: Andrew W
authors.initials: AW
authors.lastname: George
authors.forename: Ellen M
authors.initials: EM
authors.lastname: Wijsman
authors.forename: Elizabeth A
authors.initials: EA
authors.lastname: Thompson
mesh_terms: D000544:Alzheimer Disease / Q000235:genetics*; D008040:Genetic Linkage; D005819:Genetic Markers / Q000235:genetics; D006801:Humans; D008126:Lod Score; D008390:Markov Chains; D009010:Monte Carlo Method; D010375:Pedigree; D012984:Software
chemical_list: D005819:Genetic Markers