The DMU-package for Analyzing Multivariate Mixed Models has been developed over a
period of more than 25 years. This paper gives an overview of new features and the recent …

DMU is a package directed towards applications in quantitative genetics, and it implements
powerful tools to estimate variance components and fixed effects (BLUE) and to predict …

The BLUPF90 suite is a collection of software for mixed-model analysis with focus on
breeding and genetics applications. Solving of mixed model equations and variance …

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 …

Background Mixed models have a long and fruitful history in statistics. They are pertinent to
genomics problems because they are highly versatile, accommodating a wide variety of …

In the last decade the use of mixed models has become a pivotal part in the implementation
of genome-assisted prediction in plant and animal breeding programs. Exploiting the use …

Mixed models have been used extensively in quantitative genetics to study continuous and
discrete traits. A standard quantitative genetic model proposes that the effects of levels of …

We propose a general Bayesian approach to heteroskedastic error modeling for generalized
linear mixed models (GLMM) in which linked functions of conditional means and residual …

Background Two types of models have been used for single-step genomic prediction and
genome-wide association studies that include phenotypes from both genotyped animals and …

Implicit assumption of common (co) variance for all loci in multi-trait Genomic Best Linear
Unbiased Prediction (GBLUP) results in a genomic relationship matrix (G) that is common to …