5-7 and 19-21 September 2016

4 ECTS

PhD course taught by Daniel Sorensen, Peter Sørensen, Ole Christensen and Luc Janss, AU, Denmark.

Short description:

The objective of the course is to provide first year PhD students in statistical genetics, that have a biological background and little statistical expertise, with the basic tools needed to perform computer-based genetic analyses. At the end of the course, the student should be familiar with some of the computer-based methods of inference and be able to implement the techniques needed for their own research projects.

The course consists of four basic topics: Likelihood, Implementation of the likelihood, Bayesian methods, Markov chain Monte Carlo in practice.

The course is very much exercise-driven, and builds on examples and their solutions using R. There will be lectures from 9-12 and computer exercises from 13-16.

PhD course of 3 ECTS, organised by Senior Scientist Elise Norberg, Aarhus University: Science and Technology. Course dates and location: 19 - 23 Jun. 2017 in Viborg, Denmark. 

The course is taught by Christian Sørensen, Senior scientist, AU, and Theo Meuwissen, Professor, Norwegian University of Life Sciences (NMBU)

Course Description

The course is aimed at tackling problems from practical modern genetic improvement of agricultural livestock and crops. Through the course you acquire theoretical insight in designing genetic improvement programs in general and experience in some practical examples. You will be able to design genetic improvement programs for simple situations. Recently developed methods, including the use of genomic data, are considered and their role in designing genetic improvement programs is evaluated. 

The course focuses on the quantitative genetics and statistical background of different genomic prediction models, also covering estimation of variance components, theory on genomic heritabilities, Bayesian statistics, estimation of hyper parameters in Bayesian models, multi-trait models and simple genomic feature models. Use of all models will be trained in computer practicals with the objective that students obtain an understanding of the statistical principles of the different models, and will be able to analyze data and critically assess the results from different statistical approaches.

Teachers: Luc Janss (AU), Theo Meuwissen (NMBU)

ECTS:  MSc course 5 , PhD course 3