Open Access

Hypothesis testing for the genetic background of quantitative traits

  • Luis Alberto García-Cortés1Email author,
  • Carlos Cabrillo2,
  • Carlos Moreno1 and
  • Luis Varona3
Genetics Selection Evolution200133:3

https://doi.org/10.1186/1297-9686-33-1-3

Received: 8 November 1999

Accepted: 29 September 2000

Published: 15 January 2001

Abstract

The testing of Bayesian point null hypotheses on variance component models have resulted in a tough assignment for which no clear and generally accepted method exists. In this work we present what we believe is a succeeding approach to such a task. It is based on a simple reparameterization of the model in terms of the total variance and the proportion of the additive genetic variance with respect to it, as well as on the explicit inclusion on the prior probability of a discrete component at origin. The reparameterization was used to bypass an arbitrariness related to the impropriety of uninformative priors onto unbounded variables while the discrete component was necessary to overcome the zero probability assigned to sets of null measure by the usual continuous variable models. The method was tested against computer simulations with appealing results.

Keywords

animal breedingprior distributionBayes factorhypothesis testingheritability

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Authors’ Affiliations

(1)
Departamento de Genética, Facultad de Veterinaria
(2)
Instituto de Óptica "Daza de Valdés", CSIC
(3)
Área de Producción Animal, Centro UdL-IRTA

Copyright

© INRA, EDP Sciences 2001

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