Effect of prior distributions on accuracy of genomic breeding values for two dairy traits

Nicolazzi, Ezequiel L., Negrini, Riccardo, Chamberlain, Amanda J., Goddard, Michael E., Marsan, Paolo Ajmone and Hayes, Ben J. (2013) Effect of prior distributions on accuracy of genomic breeding values for two dairy traits. Italian Journal of Animal Science, 12 4: 555-561. doi:10.4081/ijas.2013.e91

Author Nicolazzi, Ezequiel L.
Negrini, Riccardo
Chamberlain, Amanda J.
Goddard, Michael E.
Marsan, Paolo Ajmone
Hayes, Ben J.
Title Effect of prior distributions on accuracy of genomic breeding values for two dairy traits
Journal name Italian Journal of Animal Science   Check publisher's open access policy
ISSN 1594-4077
Publication date 2013-09-07
Sub-type Article (original research)
DOI 10.4081/ijas.2013.e91
Open Access Status DOI
Volume 12
Issue 4
Start page 555
End page 561
Total pages 7
Place of publication Bologna, Italy
Publisher Avenue Media
Language eng
Formatted abstract
The ideal method to estimate direct genomic values (DGV) would calculate the conditional mean of the breeding value given the genotype of individuals at each quantitative traits locus (QTL). In this study we compare accuracies of DGV obtained using three different prior distributions of the single-nucleotide polymorphism (SNP) effects (normal, Student's t and double-exponential) in simulated data, to understand the extent of reduction in DGV accuracy when the prior distribution does not match the true distribution of QTL effects. We then apply the methods in a real dataset of 1149 Australian Holstein-Friesian bulls, both to find the prior distribution that is most robust across traits and to make interpretations about the true distribution of QTL effects. Methods using normal and Student's t prior distributions had fixed hyper-parameters, whereas hyper-parameters for double-exponential prior distribution were conditional to the data. Using the Student's t distribution for the prior distribution of SNP effects gave the largest estimates of SNP effects in the presence of QTL with large effects in both simulated and real data, and achieved the best accuracies of DGV in both datasets. The double-exponential distribution resulted in higher shrinkage of SNP effect estimates, even when a large true effect was present. The normal distribution resulted in the greatest degree of shrinkage of estimated effects, and gave the lowest accuracies. The amount of information of the data analyzed might still be inadequate to estimate these hyper-parameters accurately. A Student's t distribution with fixed hyper-parameters was the best approximation of the QTL distribution for the two dairy traits analyzed.
Keyword Accuracy
Genomic selection
Prior distribution
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ
Additional Notes http://www.tandfonline.com/doi/full/10.4081/ijas.2013.e91

Document type: Journal Article
Sub-type: Article (original research)
Collection: Queensland Alliance for Agriculture and Food Innovation
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