| Study on mapping quantitative trait loci for animal complex binary traits using Bayesian-Markov chain Monte Carlo approach. | |
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MedLine Citation:
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PMID: 17312993 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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It is a challenging issue to map Quantitative Trait Loci (QTL) underlying complex discrete traits, which usually show discontinuous distribution and less information, using conventional statistical methods. Bayesian-Markov chain Monte Carlo (Bayesian-MCMC) approach is the key procedure in mapping QTL for complex binary traits, which provides a complete posterior distribution for QTL parameters using all prior information. As a consequence, Bayesian estimates of all interested variables can be obtained straightforwardly basing on their posterior samples simulated by the MCMC algorithm. In our study, utilities of Bayesian-MCMC are demonstrated using simulated several animal outbred full-sib families with different family structures for a complex binary trait underlied by both a QTL and polygene. Under the Identity-by-Descent-Based variance component random model, three samplers basing on MCMC, including Gibbs sampling, Metropolis algorithm and reversible jump MCMC, were implemented to generate the joint posterior distribution of all unknowns so that the QTL parameters were obtained by Bayesian statistical inferring. The results showed that Bayesian-MCMC approach could work well and robust under different family structures and QTL effects. As family size increases and the number of family decreases, the accuracy of the parameter estimates will be improved. When the true QTL has a small effect, using outbred population experiment design with large family size is the optimal mapping strategy. |
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Authors:
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Jianfeng Liu; Yuan Zhang; Qin Zhang; Lixian Wang; Jigang Zhang |
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Publication Detail:
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Type: Journal Article; Research Support, Non-U.S. Gov't |
Journal Detail:
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Title: Science in China. Series C, Life sciences / Chinese Academy of Sciences Volume: 49 ISSN: 1006-9305 ISO Abbreviation: Sci. China, C, Life Sci. Publication Date: 2006 Dec |
Date Detail:
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Created Date: 2007-02-22 Completed Date: 2007-03-20 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9611809 Medline TA: Sci China C Life Sci Country: China |
Other Details:
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Languages: eng Pagination: 552-9 Citation Subset: IM |
Affiliation:
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College of Animal Science and Technology, China Agricultural University, Beijing 100094, China. |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Animals Bayes Theorem* Chromosome Mapping / methods*, statistics & numerical data* Markov Chains* Monte Carlo Method* Quantitative Trait Loci* |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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