Bayes factor for testing between different structures of random genetic groups: A case study using weaning weight in Bruna dels Pirineus beef cattle

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2007Author
Casellas, Joaquim
Piedrafita, Jesús
Varona Aguado, Luís
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Casellas, Joaquim;
Piedrafita, Jesús;
Varona Aguado, Luís;
.
(2007)
.
Bayes factor for testing between different structures of random genetic groups: A case study using weaning weight in Bruna dels Pirineus beef cattle.
Genetics Selection Evolution, 2007, vol. 39, núm. 1, p. 39-53.
https://doi.org/10.1051/gse:2006030.
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Show full item recordAbstract
The implementation of genetic groups in BLUP evaluations accounts for different
expectations of breeding values in base animals. Notwithstanding, many feasible structures of
genetic groups exist and there are no analytical tools described to compare them easily. In
this sense, the recent development of a simple and stable procedure to calculate the Bayes
factor between nested competing models allowed us to develop a new approach of that method
focused on compared models with different structures of random genetic groups. The procedure
is based on a reparameterization of the model in terms of intraclass correlation of genetic groups.
The Bayes factor can be easily calculated from the output of a Markov chain Monte Carlo
sampling by averaging conditional densities at the null intraclass correlation. It compares two
nested models, a model with a given structure of genetic groups against a model without genetic
groups. The calculation of the Bayes factor between different structures of genetic groups can
be quickly and easily obtained from the Bayes factor between the nested models. We applied
this approach to a weaning weight data set of the Bruna dels Pirineus beef cattle, comparing
several structures of genetic groups, and the final results showed that the preferable structure
was an only group for unknown dams and different groups for unknown sires for each year of
calving.
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Genetics Selection Evolution, 2007, vol. 39, núm. 1, p. 39-53European research projects
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