Improved techniques for sampling complex pedigrees with the Gibbs sampler

  • K. Joseph Abraham
  • Liviu R. Totir
  • Rohan L. Fernando
Open Access
Research

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.

Keywords

Gibbs sampler Markov chain Monte Carlo pedigree peeling Elston Stewart algorithm 

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Copyright information

© INRA, EDP Sciences 2006

Authors and Affiliations

  • K. Joseph Abraham
    • 1
  • Liviu R. Totir
    • 2
  • Rohan L. Fernando
    • 2
    • 3
  1. 1.1301 Agronomy HallIowa State UniversityAmesUSA
  2. 2.Department of Animal ScienceIowa State UniversityAmesUSA
  3. 3.Lawrence H. Baker Center for Bioinformatics and Biological StatisticsIowa State UniversityAmesUSA

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