Genetic epidemiology and genome-wide association analyses
Dates: 30 May – 3 June 2022.
Location: University of Bergen, Department of Global Public Health and Primary Care.
Organiser: Håkon K. Gjessing.
Evaluation: Take-home/written exam at the end of the course.
Course code: GENESTAT-B.
Registration: Closed. If you wish to earn credits for the course, you will need to sign up through Mitt UiB.
Registration deadline: May 20th, 2022.
Credits: 4 ECTS.
- Rolv Terje Lie (UiB)
- Anil Jugessur (UiB and FHI)
- Julia Romanowska (UiB)
- Øystein Haaland (UiB)
- Miriam Gjerdevik (FHI)
- Jon Bohlin (FHI)
- Yunsung Lee (UiB)
- Bjørn Olav Åsvold (NTNU)
- Siri Skodvin (FHI)
- Marc Vaudel (UiB)
The first part of the course will provide a broad overview of genetic epidemiology and statistical genetics, as well as an introduction to necessary software.
The second part will cover genetic association analyses in detail: Designs, including case-family trios, case-control, time-to-event etc.; Data handling and basic quality control for candidate genes and Genome-wide association analyses (GWAS); data imputation, selection of informative (tagging) SNPs; Power simulations. Analyses: Basic associations analyses, control for population structure, haplotype reconstruction, risk response models; estimation of maternal gene effects and parent-of-origin effects; X-chromosome models. Testing and measuring gene-environment interactions (GxE). Post-processing of results, regional association plots, assessing haplotype blocks, control for multiple testing, False Discovery Rate (FDR), q-values. Polygenic risk scores. EWAS, methylation data analyses. Mendelian randomization techniques. Case studies with polygenic risk scores, methylation age clocks, and genetic makeup of cleft lip palate as examples.
The course will use freely available software/resources, including numerous R packages as well as PLINK.
Day I: Monday 09:30-16:00 Introduction of lecturers and participants, and to the course. Lectures and exercises/practicals: Basic intro to necessary software such as R. First intro to genetic epidemiology.
Day II: Tuesday 0815-1600 Lectures and exercises/practicals: Second part of intro to genetic epidemiology. Quality control, imputations, GWAS, PLINK, other software.
Day III: Wednesday 0815-1600 Lectures and exercises/practicals: Haplin, analysis of family trio data, sample size calculations, postprocessing of results, polygenic risk scores.
Day IV: Thursday 0815-1600 Lectures and exercises/practicals: Special inheritance models, X-chromosome, Parent-of-origin effects, EWAS/methylation data, Case study (methylation clock).
Day V: Friday 0815-1300 Lecture and exercises/practicals: Mendelian randomization, Case Study (Orofacial clefts), Bioinformatics services and databases. 1300-1600 Wrap-up/summary, prepare take-home project.
Following (one full) week: Work on take-home project, return within two weeks.
Learning outcomes and competence
To obtain a general overview and understanding of the field of genetic epidemiology. To obtain familiarity with GWAS and EWAS data, and standard study designs, such as case-control and family designs. To acquire the tools and abilities to conduct genetic association analyses, including data quality control, analyses, interpretation of results, and post-processing/presentation of results.
Basic understanding of genetic principles. Experience with regression models, including linear and logistic regression. Experience with the R software and some previous experience with genetic association analyses will be an advantage.