Genomic Epidemiology in Africa

21-26 June 2015

Africa Centre for Health and Population Studies, University of KwaZulu-Natal, Durban, South Africa

Deadline for Applications: 13 March 2015

Course overview

Large-scale genetic studies of human populations have become a powerful tool for understanding resistance and susceptibility to disease. There is growing interest among medical researchers in Africa in applying these new methodologies to gain a better understanding of common diseases that affect African populations. This computational course aims to describe the key aspects of human population genetics and genome-wide association studies (GWAS) so that participants will be able to perform analyses of their own research. The programme will cover both theoretical and practical issues of genetic epidemiology via association analysis, illustrating particular concepts with examples from recent studies in type 2 diabetes, sickle cell disease and malaria.

The outline of the course will follow the experimental process: an introduction to human population genetics and its relevance to study design, through data collection and analysis, and on to interpreting and following up results. Particular emphasis will be placed on the use of publically available software and resources (such as PLINK, HapMap, and 1000 genomes) and the benefits of collaborative research. Material will be covered by lectures, computational practicals and break-out discussion sessions.

Course Programme

Population genetics and association studies
Patterns of diversity in natural populations and underlying molecular processes. Linkage disequilibrium and ancestry. Differences between populations and its consequences for GWAS.

Study design and exploiting population cohorts
The GWAS approach and its power to detect genetic effects. Choice of commercially available genotyping products and study individuals. Choice of control individuals. Integrating GWAS into epidemiological and cohort studies.

Data quality and basic association analysis
Genotype calling and quality control. Simple tests for association and performing a genome-wide scan. Interpreting evidence for association and identification of regions of interest.

Controlling for confounding effects
Tools for investigating possible population structure and relatedness within study individuals. Methods for correcting for confounding effects. Comparing data to existing collections.

Follow up analysis 
Replicating signals of association. Options for functional studies. Trans-ethnic fine-mapping. Exploiting whole genome sequence information. Imputation, meta-analysis and data sharing.

Course Instructors

Kirk Rockett (Wellcome Trust Centre for Human Genetics, Oxford, UK)
Manj Sandhu (Wellcome Trust Sanger Institute, UK)
Gavin Band (Wellcome Trust Centre for Human Genetics, Oxford, UK)
Luke Jostins (Wellcome Trust Centre for Human Genetics, Oxford, UK)
Geraldine Clark (Wellcome Trust Centre for Human Genetics, Oxford, UK)
Tommy Carstensen (Wellcome Trust Sanger Institute, UK)

Guest Speaker

Professor Deenan Pillay (Director, Africa Centre for Health and Population Studies, Durban, South Africa)

How to apply

Applicants should be researchers or clinicians engaged in relevant research in Africa. Experience of data analysis, including the use of software such as Excel, Stata or R is required. Preference will be given to applicants familiar with genetic epidemiological analysis.

There is no course fee for academics/clinicians as all course costs will be met by The Wellcome Trust. Commercial applicants should contact us for the commercial course fee.

Bursaries are available for academic and clinical applicants to cover travel, accommodation and sustenance costs and are subject to open competition. If you would like to apply for a bursary, please complete the bursary section of the online application form (see below for application process).

Application forms for this course can now be completed online. If you have any problems with the online application process, please email us.

Deadline for Applications: 13 March 2015

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