BIN303 Estimation of variance components - animal and plants
Credits (ECTS):5
Course responsible:Gunnar Klemetsdal
Campus / Online:Taught campus Ås
Teaching language:Engelsk
Course frequency:BIN303 will intentionally be given every second year.
Nominal workload:125 hours of study, including colloquia and participation in study groups for 25 hours.
Teaching and exam period:The course version is given first time in 2024, in the spring paralell.
About this course
Learning outcome
Knowledge
You will get knowledge on theory for estimation of variance components in mixed linear models via REML.
Skills
You will be able to calculate REML-variance components with R, by use of matrix algebra and by use of a R-package.
General competence
In general, the course will give you competence in data handling, programming, linear algebra, and estimation theory; and some understanding of plant and animal breeding programs
- Every second week lecture with assignments in R, that will be worked through in detail the following week. Self-study of literature. Estimation of variance components on own, realistically huge datasets. Presentation for students and teacher.
- Teacher goes through all assignments and participate in all colloquia. Advice will be given for term papers and assignments.
- Primarilly BIN301, but at least good knowledge in matrix algebra and linear models.
Some animal or plant breeding to MSc level, including knowledge on pedigree and genomic based relationship.
Good knowledge about linear algebra, vector and matrix handling.
Data programming in R.
- Evalutation will be made of the term paper, showing results of calculations of variance components in real data with state of the art R-program.
- Evaluated by teacher and external sensor.
Participation in colloquia.
Presentation of calculation of variance components in an own data set, of size relevant for plant or animal breeding organizations.
Commenting/being opponent to other participants' presentations.
- Approximately 12.5 hours colloquium/lectures and 12.5 hours of exercises.
- Special requirements in Science