Human diseases and agricultural traits can be predicted by modeling a genetic random
polygenic effect in linear mixed models. To estimate variance components and predict …

Single-step genomic evaluation became a standard procedure in livestock breeding, and
the main reason is the ability to combine all pedigree, phenotypes, and genotypes available …

Genomic prediction is a statistical method to predict phenotypes of polygenic traits using
high-throughput genomic data. Most diseases and behaviors in humans and animals are …

We examined whether or not the predictive ability of genomic best linear unbiased
prediction (GBLUP) could be improved via a resampling method used in machine learning …

Background Genomic selection is an effective tool for animal and plant breeding, allowing
effective individual selection without phenotypic records through the prediction of genomic …

Improvement of statistical methods is crucial for realizing the potential of increasingly dense
genetic markers. Bayesian methods treat all markers as random effects, exhibit an …

Genomic best linear unbiased prediction (BLUP) is a statistical method that uses
relationships between individuals calculated from single-nucleotide polymorphisms (SNPs) …

The rapid increase in high-throughput single-nucleotide polymorphism data has led to a
great interest in applying genome-wide evaluation methods to identify an individual's …

Most human diseases and agriculturally important traits are complex. Dissecting their
genetic architecture requires continued development of innovative and powerful statistical …

Genomic data provide a valuable source of information for modeling covariance structures,
allowing a more accurate prediction of total genetic values (GVs). We apply the kriging …