Please use this identifier to cite or link to this item: https://une.intersearch.com.au/unejspui/handle/1959.11/390
Title: An Algorithm for Sampling Descent Graphs in Large Complex Pedigrees Efficiently
Contributor(s): Henshall, John M (author); Tier, B  (author)
Publication Date: 2003
Open Access: Yes
DOI: 10.1017/S0016672303006232
Handle Link: https://hdl.handle.net/1959.11/390
Abstract: No exact method for determining genotypic and identity-by-descent probabilities is available for large, complex pedigrees. Approximate methods for such pedigrees cannot be guaranteed to be unbiased. Anew method is proposed that uses the Metropolis-Hastings algorithm to sample a Markov Chain of descent graphs which fit the pedigree and known genotypes. Unknown genotypes are determined from each descent graph. Genotypic probabilities are estimated as their means. The algorithm is shown to be unbiased for small, complex pedigrees and feasible and consistent for large complex pedigrees.
Publication Type: Journal Article
Source of Publication: Genetical Research, 81(3), p. 205-212
Publisher: Cambridge University Press
Place of Publication: United Kingdom
ISSN: 0016-6723
Field of Research (FOR): 070201 Animal Breeding
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
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Appears in Collections:Journal Article

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