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Estimating genotypes with independently sampled descent graphs

Published online by Cambridge University Press:  01 February 2002

JOHN M. HENSHALL
Affiliation:
Animal Genetics and Breeding Unit, University of New England, Armidale, NSW 2351, Australia
BRUCE TIER
Affiliation:
Animal Genetics and Breeding Unit, University of New England, Armidale, NSW 2351, Australia
RICHARD J. KERR
Affiliation:
Animal Genetics and Breeding Unit, University of New England, Armidale, NSW 2351, Australia

Abstract

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A method for estimating genotypic and identity-by-descent probabilities in complex pedigrees is described. The method consists of an algorithm for drawing independent genotype samples which are consistent with the pedigree and observed genotype. The probability distribution function for samples obtained using the algorithm can be evaluated up to a normalizing constant, and combined with the likelihood to produce a weight for each sample. Importance sampling is then used to estimate genotypic and identity-by-descent probabilities. On small but complex pedigrees, the genotypic probability estimates are demonstrated to be empirically unbiased. On large complex pedigrees, while the algorithm for obtaining genotype samples is feasible, importance sampling may require an infeasible number of samples to estimate genotypic probabilities with accuracy.

Type
Research Article
Copyright
© 2001 Cambridge University Press