Jump to ContentJump to Main Navigation
Evolution and Selection of Quantitative Traits$
Users without a subscription are not able to see the full content.

Bruce Walsh and Michael Lynch

Print publication date: 2018

Print ISBN-13: 9780198830870

Published to Oxford Scholarship Online: September 2018

DOI: 10.1093/oso/9780198830870.001.0001

Show Summary Details
Page of

PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2020. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 30 November 2020

Analysis of Short-term Selection Experiments: 2. Mixed-model and Bayesian Approaches

Analysis of Short-term Selection Experiments: 2. Mixed-model and Bayesian Approaches

Chapter:
(p.631) 19 Analysis of Short-term Selection Experiments: 2. Mixed-model and Bayesian Approaches
Source:
Evolution and Selection of Quantitative Traits
Author(s):

Bruce Walsh

Michael Lynch

Publisher:
Oxford University Press
DOI:10.1093/oso/9780198830870.003.0019

When the full pedigree of individuals whose values (records) were used in the selection decisions during an experiment (or breeding program) is known, LS analysis can be replaced by mixed models and their Bayesian extensions. In this setting, REML can be used to estimate genetic variances and BLUP can be used to estimate the mean breeding value in any given generation. The latter allows for genetic trends to be separated from environmental trends without the need for a control population. Under the infinitesimal model setting (wherein selection-induced allele-frequency changes are small during the course of the experiment), the use of the relationship matrix in a BLUP analysis accounts for drift, nonrandom mating, and linkage disequilibrium.

Keywords:   animal model, Bayesian mixed-models, BLUP, BLUP selection, Gibbs sampler, Henderson's mixed-model equations, infinitesimal model, Markov chain Monte Carlo, Metropolis-Hastings algorithm, MCMC, mixed models, numerator relationship matrix, prediction error variances, relationship matrix, REML

Oxford Scholarship Online requires a subscription or purchase to access the full text of books within the service. Public users can however freely search the site and view the abstracts and keywords for each book and chapter.

Please, subscribe or login to access full text content.

If you think you should have access to this title, please contact your librarian.

To troubleshoot, please check our FAQs , and if you can't find the answer there, please contact us .