Genet. Sel. Evol.
Volume 39, Number 1, January-February 2007
|Page(s)||27 - 38|
Improved techniques for sampling complex pedigrees with the Gibbs samplerK. Joseph Abrahama, Liviu R. Totirb and Rohan L. Fernandob, c
a 1301 Agronomy Hall, Iowa State University, Ames, IA 50011, USA
b Department of Animal Science, Iowa State University, Ames, IA 50011, USA
c Lawrence H. Baker Center for Bioinformatics and Biological Statistics, Iowa State University, Ames, IA 50011, USA
(Received 5 January 2006; accepted 3 September 2006; published online 11 January 2007)
Abstract - 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.
Key words: Gibbs sampler / Markov chain Monte Carlo / pedigree peeling / Elston Stewart algorithm
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