Irreducibility and efficiency of ESIP to sample marker genotypes in large pedigrees with loops

Genetics Selection Evolution. 2002;34(5):537-555 DOI 10.1186/1297-9686-34-5-537

 

Journal Homepage

Journal Title: Genetics Selection Evolution

ISSN: 0999-193X (Print); 1297-9686 (Online)

Publisher: BMC

Society/Institution: French National Institute for Agricultural Research

LCC Subject Category: Agriculture: Animal culture | Science: Biology (General): Genetics

Country of publisher: United Kingdom

Language of fulltext: German, French, English

Full-text formats available: PDF, HTML

 

AUTHORS

Schelling Matthias
Stricker Christian
Guldbrandtsen Bernt
Fernando Rohan L
Fernández Soledad A
Carriquiry Alicia L

EDITORIAL INFORMATION

Blind peer review

Editorial Board

Instructions for authors

Time From Submission to Publication: 26 weeks

 

Abstract | Full Text

<p>Abstract</p> <p>Markov chain Monte Carlo (MCMC) methods have been proposed to overcome computational problems in linkage and segregation analyses. This approach involves sampling genotypes at the marker and trait loci. Among MCMC methods, scalar-Gibbs is the easiest to implement, and it is used in genetics. However, the Markov chain that corresponds to scalar-Gibbs may not be irreducible when the marker locus has more than two alleles, and even when the chain is irreducible, mixing has been observed to be slow. Joint sampling of genotypes has been proposed as a strategy to overcome these problems. An algorithm that combines the Elston-Stewart algorithm and iterative peeling (ESIP sampler) to sample genotypes jointly from the entire pedigree is used in this study. Here, it is shown that the ESIP sampler yields an irreducible Markov chain, regardless of the number of alleles at a locus. Further, results obtained by ESIP sampler are compared with other methods in the literature. Of the methods that are guaranteed to be irreducible, ESIP was the most efficient.</p>