https://studiegids.vu.nl/en/courses/2025-2026/P_MEPISEQTo provide an understanding of epigenetic mechanisms, and the skills to analyse and interpret human genome-wide epigenomic datasets, as applied in human epigenetic epidemiology research.Though our genetic material (DNA sequence) may be relatively fixed, the epigenetic mechanisms that regulate the expression of our genes vary across cell types and are subject to changes during development and in response to external influences. Epigenomics is concerned with the study of epigenetic mechanisms on a genome-wide scale. Sequencing is a technique that is applied for typing DNA, RNA, or DNA methylation on a genome-wide scale at the maximum resolution. This course aims to provide students with the theoretical background and with the analytical skills required to analyse and interpret genome-wide epigenomic data in the context of human epigenetic epidemiology research. Students will understand how life circumstances may alter gene expression and lead to individual differences in behaviour and health. The theoretical part, covered by lectures and a textbook, provides an understanding of the various epigenetic mechanisms employed in human cells, our current understanding of their role in behaviour and health, the techniques to measure whole genome DNA methylation and RNA including array-based methods and sequencing, and the research designs, quality control of data, statistical analysis, and challenges in human epigenetic epidemiology. A significant part of this course will be devoted to hands-on computer practical work in which the student will analyse epigenomic data (mostly DNA methylation arrays) from the Netherlands Twin Register in combination with survey data (e.g. environmental indicators). These practical assignments are intended to familiarize students with all aspects of the analysis of epigenomic data: from the initial data quality control and normalization to performing an epigenome-wide association study. The course duration is 4 weeks. The first 3 weeks consist of lectures and practicals. The course will end with a final integrative data analysis assignment, and with a written exam in week 4.Tuition consists of live lectures, self-study (literature and web lectures), computer practicals, work group.Formative assessmentComputer assignment 1,4,5 ELSI assignment (mandatory, week 3)Summative assessmentComputer assignments 2 and 3 Final data analysis assignment (week 3/4) Written exam (week 4)The final grade is based on the average grade of 3 separate assessments: Computer assignments (40%), final data analysis assignment (20%), final written exam (40%). To pass this course, students need to have a grade of 5.5 or higher on all 3 elements (computer assignments, final data analysis assignment, and exam). Resit Offered for the written exam and data analysis assignments Computer assignments The computer assignments (practicals) contribute to 40% of the final grade. In each practical, students will be given an assignment to analyse an empirical dataset. The assignment includes questions about the outcome of the analyses, motivation of decisions (e.g. on the treatment of covariates or corrections for familial clustering). The answers to these questions comprise of a description of the data and the results obtained, including numbers, tables, and figures and will be handed in by students after each practical. In total, there are 5 computer assignments (+ 1 final data analysis assignment). It is mandatory to hand in all assignments, but a grade is only given for practical 2 and 3. The overall grade of practical 2 and 3 contributes to 40% of the final grade for this course. For the other assignments, answers will provided after the student has handed in the assignment so that the student can check his/her own answers. Assignments will be posted on canvas on the day of the assignment. Final data-analysis assignment A separate grade is given for the final data analysis assignment in week 3, which contributes to 20% of the final grade. In this assignment, all skills that have been practiced by the student in previous practicals will be assessed. Written exam The final exam represents 40% of the final grade. It consists of multiple open questions.Selected chapters (announced in class) from Karin B. Michels, Epigenetic Epidemiology (pdf freely available in VU library) Selected chapters (announced in class) from Carsten Carlsberg, Human Epigenomics (pdf freely available in VU library) Van Dongen & Boomsma Chapter 4 Epigenetics and twin studies. A review and applications in human aggressive behavior Genes, brain, and emotions: Interdisciplinary and Translational Perspectives. Oxford Scholarship. Editors: Andrei C. Miu, Judith R. Homberg, and Klaus-Peter Lesch. Lecture notes Scientific articles (announced in class)Entry only for students with an interest in the application of genetics in the behavioural or health sciences, with sufficient background in statistics and biology. Students should check if the course program including exam does not overlap with other courses that they follow.Introduction to Omics, Behavioural GeneticsSome prior experience with programming in R, knowledge of statistics and genetics.