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Course content
The course focuses on the understanding of genetic epidemiology concepts and understanding of genetic variation in the population. Topics to be taught are study design, analysis methods (whole genome, mendelian randomization and functional follow-up), bias and confounding in analyses, implication of functional findings, the use of registry data and ethical considerations.
Learning outcome
After completing the course, the student should understand the concepts of genetic epidemiology, understand how genetic variation manifests itself in the population and how it can be studied. Know important tools and analysis methods for genome-wide analyses. Be able to assess and discuss results from such analyses, understand implications of functional findings and suggest follow-up analyses. Know analysis methods for MR-analyses. Be able to describe the construction of an instrument variable and assess the validity of such. Be able to assess and discuss results from MR-analyses.
Learning methods and activities
Lectures and problem solving. All lectures and problem solving activities are mandatory. The course coordinator may approve up to 20% absence from mandatory lectures/activities. Absence may not be approved if the activity is considered to be critical to the learning outcomes of the course.
Compulsory assignments
- Presence at lectures
Recommended previous knowledge
Recommended background knowledge: KLMED8004 Medical statistics I, Introductory course in epidemiology (eg. Master course in epidemiology), basic knowledge in genetics, basic skills using R and/or basic skills and abilities to work in a Linux system (recommended online courses can be completed prior to the course. Please contact the course coordinator for more information).
The course is supported by the Digital Life Norway Research School and there are a limited number of travel grants available for our members.
Contact course coordinator: