Gene Finding: Genome-Wide Association Studies and beyond

2019-2020

Course Objective

Learn how to find causal genetic variants using the Genome-Wide
Association Study (GWAS) approach, and subsequently being able to
integrate these results in follow-up studies, which examine the gene
contributions in relation to the psychological traits studied.

Course Content

The Genome-Wide Association Study (GWAS) design is the most successful
study design to date with respect to identifying genetic variants that
influence heritable and complex human traits. Students will learn the
theoretical background, statistical methods, and the basic computational
skills needed to conduct such gene-finding studies using the latest
techniques on directly measured and imputed single nucleotide
polymorphism (SNP) data. They will gain hands-on experience cleaning and
analyzing genetic data in order to find causal genes for complex traits
related to cognition (e.g., intelligence), personality (e.g.,
neuroticism), behaviour (e.g., smoking, sport participation) and health
(e.g., depression, diabetes). Also they will learn how to evaluate the
importance of their genetic findings in post-analyses which include
meta-analysis, gene annotation, gene - and gene network based
statistics, SNP heritability and genetic overlap between traits.

Teaching Methods

Tuition consists of lectures and computer practicals.

Method of Assessment

The students have to successfully finish all practical assignments in
order to receive a grade. The grade will be based on a homework
assignment (25%) and a written exam (75%).

Literature

Background book for molecular genetics and basic principles of GWAS:
Human Molecular Genetics, Strachan & Read, 4th edition.

Several research papers on methods will be discussed:
LD-score regression (B. Sullivan et al.)
Genetic data cleaning (Laurie et al.)
GWAS meta-analysis (Abecasis et al.).

Students are expected to read the documentation available for web based
tools when needed.

Metal (http://genome.sph.umich.edu/wiki/METAL_Documentation),
Plink (http://zzz.bwh.harvard.edu/plink/),
LD-score-regression
(https://github.com/bulik/ldsc/wiki/LD-Score-Estimation-Tutorial),
Fuma & Magma (https://ctg.cncr.nl/software/)

During the course, additional reading material based on the latest
developments in the field may be distributed in class.

Target Audience

Master and PHD students interested in Genome Wide Association Studies.

Recommended background knowledge

Basic knowledge about statistics and molecular biology.

General Information

Course Code P_MGENFIND
Credits 6 EC
Period P1
Course Level 400
Language of Tuition English
Faculty Fac. of Behavioural and Movement Science
Course Coordinator dr. J.J. Hottenga
Examiner dr. J.J. Hottenga
Teaching Staff

Practical Information

You need to register for this course yourself

Teaching Methods Lecture, Practical
Target audiences

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