%0 Journal Article
%T Improved techniques for sampling complex pedigrees with the Gibbs sampler
%A Abraham K Joseph
%A Totir Liviu R
%A Fernando Rohan L
%J Genetics Selection Evolution
%D 2007
%I BioMed Central
%R 10.1186/1297-9686-39-1-27
%X Markov chain Monte Carlo (MCMC) methods have been widely used to overcome computational problems in linkage and segregation analyses. Many variants of this approach exist and are practiced; among the most popular is the Gibbs sampler. The Gibbs sampler is simple to implement but has (in its simplest form) mixing and reducibility problems; furthermore in order to initiate a Gibbs sampling chain we need a starting genotypic or allelic configuration which is consistent with the marker data in the pedigree and which has suitable weight in the joint distribution. We outline a procedure for finding such a configuration in pedigrees which have too many loci to allow for exact peeling. We also explain how this technique could be used to implement a blocking Gibbs sampler.
%K Gibbs sampler
%K Markov chain Monte Carlo
%K pedigree peeling
%K Elston Stewart algorithm
%U http://www.gse-journal.org/content/39/1/27