Materials on Linear Models in Animal Breeding

Julius van der Werf, University of New England, Australia

JvdW acknowledges contributions from former AGBU students having prepared some part of these notes, and further Larry Schaeffer and the late Brian Kennedy (both Univ. of Guelph) whose various courses have often been used as the basis of these notes, as well as Brian Kinghorn, whose original course notes were used for many animal model examples. Sang Hong Lee is acknowledged for his summary of the AI REML algorithm and Mike Goddard for allowing to use his notes of the 2003 Armidale Animal Breeding Summer Course on Bayesian estimation.

Content:

Linear models in animal breeding: Introduction

An introduction to matrix algebra and regression

Introduction to linear models

Estimation theory

Hypothesis testing in linear models

Introduction to mixed models

Hypothesis testing in mixed models

Modeling variance structures

Principles of breeding value estimation

Best linear unbiased prediction: animal models

The numerator relationship matrix

The animal model and selection

Genetic grouping

Non-additive effects and finite locus models

Estimating genetic parameters

Mixed models for genetic analysis (with ASReml examples)

Multiple trait models (with ASReml examples)

Analysis of longitudinal data – Random regression

Introduction to Bayesian statistics – Gibbs sampling (by Mike Goddard)

Inquiries                      Julius van der Werf, Animal Genetics, UNE , Armidale (AU)

em:    jvanderw  (at)  une.edu.au https://jvanderw.une.edu.au