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

Genetics Selection Evolution

Alicia L Carriquiry³  Matthias Schelling²  Christian Stricker³  Bernt Guldbrandtsen¹  Rohan L Fernando⁵  Soledad A Fernández⁴ 

[1] Danish Institute of Animal Science, Foulum, Denmark;Institute of Animal Sciences, Swiss Federal Institute of Technology, ETH-Zentrum CLU, 8092 Zürich, Switzerland;Department of Statistics, 219 Snedecor Hall, Iowa State University, Ames, IA 50011, USA;Department of Statistics, 317 Cockins Hall, Ohio State University, Columbus, OH 43210, USA;Department of Animal Science, 225 Kildee Hall, Iowa State University, Ames, IA 50011, USA

关键词: iterative peeling;    Elston-Stewart algorithm;    irreducibility;    Metropolis-Hastings;   

Others  :  1094522
DOI  :  10.1186/1297-9686-34-5-537

 received in 2001-08-21, accepted in 2002-05-06,  发布年份 2002

【 摘 要 】

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.

【 授权许可】

   
2002 INRA, EDP Sciences