Issue |
Genet. Sel. Evol.
Volume 39, Number 1, January-February 2007
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Page(s) | 27 - 38 | |
DOI | https://doi.org/10.1051/gse:2006032 |
DOI: 10.1051/gse:2006032
Improved techniques for sampling complex pedigrees with the Gibbs sampler
K. Joseph Abrahama, Liviu R. Totirb and Rohan L. Fernandob, ca 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
Correspondence and reprints: abraham@iastate.edu
© INRA, EDP Sciences 2006