For topics we will follow the textbook RA Mrode: Linear Models for the Prediction of Animal Breeding Values, CAB Int. Extra emphasis will be on Multitrait Mixed Models, and Random Regression etc. Relations to machine learning will be sketched. Some original articles on variance component estimation will also be covered. At least the two last chapters of Lynch and Walsh: Genetics and Analysis of Quantitative Traits, are relevant as a supplementary text. Another requirement is to be capable of using the software vce/pest, asreml, dmu, R, or another variance component estimation program on a data set, and predict blup breeding values.

Successful candidates will be able to calculate breeding values for breeding companies, understand the underlying theory and be able to work with and publish papers using special mixed models (e.g. maternal effect, dominance).

Colloquium in full group, and possibly in subgroups, depending on number of participants and where they live/work.

Teacher participation in colloquia if enough students.

See Course contents

Animal breeding up to PhD level. Linear algebra. Matrix handling.

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Participation in colloquia.

Semester assignment: 60 %. Written 3-hour examination: 40%. The term paper shall present the result of calculating breeding values on real data.

300 hours of study, including colloquia and participation in study groups.

Special requirements in Science

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Approximately 30 hours colloquium and 30 hours of exercises.

The course is given when there are enough interested participants. Colloquia initiated by the teacher will be held for more than 4 participants. If fewer students, some teacher supervision may be provided.

An external examiner will assess the written exam and term paper.