Data/hora: 04/06/2024 02:11:25

Provedor de dados: 	Revista Brasileira de Zootecnia	
País: 	Brazil	
Título: 	Mixture models in quantitative genetics and applications to animal breeding	
Autores: 	Gianola,Daniel; Boettcher,Paul J.; Ødegård,Jørgen; Heringstad,Bjørg.	
Data: 	2007-07-01	
Ano: 	2007	
Palavras-chave: 	Bayesian methods; Dairy cattle; Maximum likelihood; Mixture distributions; Quantitative genetics; Somatic cell scores.	
Resumo: 	Finite mixture models are helpful for uncovering heterogeneity due to hidden structure; for example, unknown major genes. The first part of this article gives examples and reviews quantitative genetics issues of continuous characters having a finite mixture of Gaussian components. The partition of variance in a mixture, the covariance between relatives under the supposition of an additive genetic model and the offspring-parent regression are derived. Formulae for assessing the effect of mass selection operating on a mixture are given. Expressions for the genetic correlation between a mixture and a Gaussian trait are presented. If there is heterogeneity in a population at the genetic or environmental levels, then genetic parameters based on theory treating distributions as homogeneous can lead to misleading interpretations. Subsequently, methods for parameter estimation (e.g., maximum likelihood) are reviewed, and the Bayesian approach is illustrated via an application to somatic cell scores in dairy cattle.	
Tipo: 	Info:eu-repo/semantics/article	
Idioma: 	Inglês	
Identificador: 	http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982007001000017	
Editor: 	Sociedade Brasileira de Zootecnia	
Relação: 	10.1590/S1516-35982007001000017	
Formato: 	text/html	
Fonte: 	Revista Brasileira de Zootecnia  v.36 suppl.0 2007	
Fonte: 	info:eu-repo/semantics/openAccess