Please use this identifier to cite or link to this item:
https://hdl.handle.net/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: | 1469-5073 0016-6723 |
Fields of Research (FoR) 2008: | 070201 Animal Breeding | Peer Reviewed: | Yes | HERDC Category Description: | C1 Refereed Article in a Scholarly Journal |
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Appears in Collections: | Animal Genetics and Breeding Unit (AGBU) Journal Article |
Files in This Item:
File | Description | Size | Format | |
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open/SOURCE03.pdf | Author final version | 114.4 kB | Adobe PDF Download Adobe | View/Open |
open/SOURCE04.pdf | Publisher version (open access) | 132.24 kB | Adobe PDF Download Adobe | View/Open |
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