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Genomic Prediction in Animals and Plants

This course is open for applications. See how to apply here.

The course focuses on the quantitative genetics and statistical background of different genomic prediction models, covering also estimation of variance components, theory on genomic heritabilities, Bayesian statistics, estimation of hyper parameters in Bayesian models, multitrait 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 can analyse data with a critical assessment of the results from different statistical approaches.

Exam info and full course description

Exam info and full course description can be found in the course catalogue.  

Admission Requirements

Course specific:

A relevant bachelor's degree within Science and Technology.

General:

Exchange Students: nomination from your home university

Freemovers: documentation for English Language proficiency

You can read more about the admission here.