This study compared the accuracy of genome-enabled prediction models using individual
single nucleotide polymorphisms (SNP) or haplotype blocks as covariates when using either …

Prediction of genomic breeding values is of major practical relevance in dairy cattle
breeding. Deterministic equations have been suggested to predict the accuracy of genomic …

Using a combined multi‐breed reference population, this study explored the influence of
model specification and the effect of including a polygenic effect on the reliability of genomic …

The impact of extent of genetic relatedness on accuracy of genome-enabled predictions was
assessed using a dairy cattle population and alternative cross-validation (CV) strategies …

This study investigated genomic predictions across Nordic Holstein and Nordic Red using
various genomic relationship matrices. Different sources of information, such as …

Background Fitting covariates representing the number of haplotype alleles rather than
single nucleotide polymorphism (SNP) alleles may increase genomic prediction accuracy if …

Background A haplotype approach to genomic prediction using high density data in dairy
cattle as an alternative to single-marker methods is presented. With the assumption that …

The basic idea of cross-validation procedures is to divide a data set into a reference and a
validation set, to omit any kind of information of the validation set and to predict this …

Bias and inflation in genomic evaluation with the single-step methods have been reported in
several studies. Incompatibility between the base-populations of the pedigree-based and …

This study investigated the possibility of increasing the reliability of direct genomic values
(DGV) by combining reference populations. The data were from 3,735 bulls from Danish …