Document Detail

Bayesian methods for estimating GEBVs of threshold traits.
MedLine Citation:
PMID:  23149458     Owner:  NLM     Status:  MEDLINE    
Estimation of genomic breeding values is the key step in genomic selection (GS). Many methods have been proposed for continuous traits, but methods for threshold traits are still scarce. Here we introduced threshold model to the framework of GS, and specifically, we extended the three Bayesian methods BayesA, BayesB and BayesCπ on the basis of threshold model for estimating genomic breeding values of threshold traits, and the extended methods are correspondingly termed BayesTA, BayesTB and BayesTCπ. Computing procedures of the three BayesT methods using Markov Chain Monte Carlo algorithm were derived. A simulation study was performed to investigate the benefit of the presented methods in accuracy with the genomic estimated breeding values (GEBVs) for threshold traits. Factors affecting the performance of the three BayesT methods were addressed. As expected, the three BayesT methods generally performed better than the corresponding normal Bayesian methods, in particular when the number of phenotypic categories was small. In the standard scenario (number of categories=2, incidence=30%, number of quantitative trait loci=50, h² = 0.3), the accuracies were improved by 30.4%, 2.4%, and 5.7% points, respectively. In most scenarios, BayesTB and BayesTCπ generated similar accuracies and both performed better than BayesTA. In conclusion, our work proved that threshold model fits well for predicting GEBVs of threshold traits, and BayesTCπ is supposed to be the method of choice for GS of threshold traits.
C-L Wang; X-D Ding; J-Y Wang; J-F Liu; W-X Fu; Z Zhang; Z-J Yin; Q Zhang
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2012-10-31
Journal Detail:
Title:  Heredity     Volume:  110     ISSN:  1365-2540     ISO Abbreviation:  Heredity (Edinb)     Publication Date:  2013 Mar 
Date Detail:
Created Date:  2013-02-14     Completed Date:  2013-07-22     Revised Date:  2014-03-07    
Medline Journal Info:
Nlm Unique ID:  0373007     Medline TA:  Heredity (Edinb)     Country:  England    
Other Details:
Languages:  eng     Pagination:  213-9     Citation Subset:  IM    
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MeSH Terms
Bayes Theorem
Breeding / statistics & numerical data*
Computer Simulation
Markov Chains
Models, Genetic*
Monte Carlo Method
Quantitative Trait, Heritable*
Selection, Genetic*

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