(Course expiry: 90 days after purchase. Trial license expiry 90 days)

In this asynchronous course we will focus on the fundamentals of Genomic Prediction by fitting several linear mixed models (LMM) using different methodologies. An array of R libraries will be used in this course including ASReml-R version 4.2, BGLR, and rrBLUP, among others.

The genomic models considered include some of the Bayesian alphabet (e.g., Bayes A, Bayes B), genomic-BLUP and SNP-BLUP. In this course, we will walk through a workflow that includes: 1) preparing the phenotypic and genotypic data, 2) obtaining relevant filtered marker and/or genomic relationship matrices, and 3) fitting and evaluating genomic prediction models. In addition, some extensions of the GBLUP model are considered, with the illustration of multi-trait and multi-environment models, calculation and incorporation of a dominance relationship matrix, and the use of single-step GBLUP (ssGBLUP) by combining pedigree-based and genomic-based relationship matrices.

This course focuses on appropriate definitions of LMMs, with required random or fixed effects, heterogeneous error structures, and modelling of correlated observations (as implemented in ASReml-R). In addition, all datasets used are real-life examples, and here we will interpret results and discuss implications of the use of genomic prediction models in the context of operational breeding programs. For this course we recommend that you have some basic understanding of linear models and be familiar with the statistical package R.

Do you have a licence for ASReml-R version 4.2? As a participant of this training, you have access to a free trial licence of ASReml-R for 90 days. Once purchased you will be sent a licence and link to download the software within 24 hours. Please note this will ONLY be sent to the email from which you signed up.