Epigenomics and Sequencing in Behaviour and Health


Course Objective

Course objective
To 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.

Learning objectives
Upon successful completion of the course, students are expected to be
able to:
1. describe the epigenetic mechanisms employed in human cells and their
role in development and cell identity
2. relate these mechanisms to the effects of DNA polymorphisms and
social and environmental factors that elicit individual differences in
behaviour and health
3. explain array-based and sequencing techniques to measure genome-wide
DNA methylation and RNA
4. interpret and cite research described in key scientific publications
in expert journals such as Genome Biology, Epigenetics, and Nature
5. perform quality control and normalization of genome-wide DNA
methylation datasets
6. perform an epigenome-wide association study and interpret results
7. compare research designs and summarize challenges in epigenetics

Course Content

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.

Teaching Methods

Tuition consists of lectures, self-study (literature), computer
practicals, and a work group.

Method of Assessment

Method of assessment

Formative assessment
• Computer assignment 1 (mandatory, week 1)
• ELSI assignment (mandatory, week 3)

Summative assessment
• Computer assignments 2-5 (week 1, 2, 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%).

Offered for the written exam and data analysis assignments

Entry Requirements

entry only for students with an interest in the application of genetics
in the behavioural or health sciences, with sufficient background in
statistics, biology and psychology.


• 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)
• Lecture notes
• Scientific articles (announced in class)

Additional Information

Additional information about assessment

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. Each assignment is graded
and the final grade constitutes the average of all assignments. The
grade for the first practical does not contribute to the final grade,
but a grade is given as feedback to the student so that he/she knows
what is expected from him/her (along with the answers that are posted on
canvas). Assignments will be posted on canvas on the day of the

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.

General Information

Course Code P_MEPISEQ
Credits 6 EC
Period P3
Course Level 400
Language of Tuition English
Faculty Fac. of Behavioural and Movement Science
Course Coordinator J. van Dongen
Examiner J. van Dongen
Teaching Staff J. van Dongen
prof. dr. D.I. Boomsma

Practical Information

You need to register for this course yourself

Teaching Methods Lecture, Study Group, Practical