Sensitivity of genomic selection to using different prior distributions.
BMC Proc
; 4(Suppl 1 Proceedings of the 13th European workshop on QTL map): S5, 2010.
Article
em En
| MEDLINE
| ID: mdl-20380759
ABSTRACT
UNLABELLED Genomic selection describes a selection strategy based on genomic estimated breeding values (GEBV) predicted from dense genetic markers such as single nucleotide polymorphism (SNP) data. Different Bayesian models have been suggested to derive the prediction equation, with the main difference centred around the specification of the prior distributions. METHODS:
The simulated dataset of the 13(th) QTL-MAS workshop was analysed using four Bayesian approaches to predict GEBV for animals without phenotypic information. Different prior distributions were assumed to assess their affect on the accuracy of the predicted GEBV.CONCLUSION:
All methods produced GEBV that were highly correlated with the true breeding values. The models appear relatively insensitive to the choice of prior distributions for QTL-MAS data set and this is consistent with uniformity of performance of different methods found in real data.
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1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Idioma:
En
Revista:
BMC Proc
Ano de publicação:
2010
Tipo de documento:
Article