Accuracy of genomic evaluation in pure line layers

Cite this article as: Denis and Bouvet: Genomic selection in tree breeding: testing accuracy of prediction models including

The objectives of our study were to: (1) compare these two grouping methods based on genotyping infor- mation to improve accuracy of selection with group records, when using

The data provided represent the mean progeny phenotype (MPP) and predictions (EBV and GEBV) for BCWD resistance (DAYS and STATUS) using pedigree-based BLUP (P-BLUP) and

The across-breed-prediction approach was followed by the Australian Beef Coop- erative Research Center (www.beefcrc.com, Beef CRC), which derived PE on a pooled training population

Average accuracies of genomic prediction (± standard errors) for Holstein-Friesian (HF, solid fill) and Jersey (J, diagonal fill) animals using a model that included a

The objec- tives of this study were: (1) to describe genomic prediction models that involve separate steps to estimate SNP variances and to estimate GEBV (genome-enhanced

Table 3 shows the raw correlations, ρ, between the masked records and their predicted values using the al- ternative relationship matrices.. Generally, there is a sub-

Extending the reference set by adding a large number of cows with genotypes and phenotypes increases the reli- ability of breeding values of young selection candidates and