Many important traits in plant breeding are polygenic and therefore recalcitrant to traditional
marker‐assisted selection. Genomic selection addresses this complexity by including all …

Certain agronomic crop traits are complex and thus governed by many small‐effect loci.
Statistical models typically used in a genome‐wide association study (GWAS) and genomic …

The availability of dense molecular markers has made possible the use of genomic selection
in plant and animal breeding. However, models for genomic selection pose several …

Using different populations in genomic selection raises the possibility of marker effects
varying across populations. However, common models for genomic selection only account …

Background Genomic selection (GS) is emerging as an efficient and cost-effective method
for estimating breeding values using molecular markers distributed over the entire genome …

We developed an integrated R library called BWGS to enable easy computation of Genomic
Estimates of Breeding values (GEBV) for genomic selection. BWGS, for BreedWheat …

In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression
models have been used. This study assessed the predictive ability of linear and non-linear …

This paper reviews properties of ridge regression for genomewide (genomic) selection and
establishes close relationships with other methods to model genetic correlation among …

Perennial ryegrass (Lolium perenne L.) is one of the most widely grown forage grasses in
temperate agriculture. In order to maintain and increase its usage as forage in livestock …

As the molecular marker density grows, there is a strong need in both genome-wide
association studies and genomic selection to fit models with a large number of parameters …