Erasmus Summer Programme Courses
Take a look at all the courses in the Erasmus Summer Programme, and find the course right for you.View all ESP courses
Genome-wide association studies [ESP74]
20 August 2018
24 August 2018
Monday to Friday (5 mornings)
From 8:45 till 11:45
Prof. Cornelia van Duijn, Dr. Fernando Rivadeneira
Erasmus MC, Rotterdam NL
Basic understanding of genetic epidemiology (as covered by ESP43), the principles of linkage disequilibrium and the HapMap & 1000 Genomes project (as covered by ESP57) is advised.
- Genetic Epidemiology
Online, download instructions will be sent in August by e-mail.
Apply for this course?
Design your programme
Try using our Programme Configurator to design and plan your own programme.Configurator
It gave me a competitive advantage in my research careerRead the full story
Detailed information about this course:
Faculty: Prof. Cornelia van Duijn, Ir. PhD & Fernando Rivadeneira, MD PhD
Genome-wide association studies (GWAS) constitute a powerful approach to investigate the genetic basis of multifactorial disorders. In the last decade, GWAS have yielded spectacular successes in the discovery of genes involved in complex traits and disorders (e.g. body height, BMI, cardiovascular disease, cancer and neurological disorders). This was made possible by the advent of high-throughput genotyping technology and the knowledge on genome structure and organization derived from the HapMap and 1000 Genomes Projects. Applying the GWAS approach has facilitated researchers to incorporate these analyses into large genetic, clinical and epidemiological studies.
This course aims to introduce epidemiologists, molecular biologists and clinicians into the basic principles of GWAS, addressing aspects of study design, data collection and analysis, extending to the interpretation and follow-up of results. The course consists of lectures providing a conceptual framework on crucial aspects of quality control, imputation of missing genotypes, statistical tools, methods to detect and correct for stratification, meta-analysis and genomic annotation of GWAS signals; accompanied by instructive hands-on computer exercises on the principles of analysis of quantitative traits and disease outcomes using software packages that are available in the public domain.
The course format will allow interactive break-out discussion sessions on theoretical and practical aspects of running GWAS, together with expert-advice procurement on diverse components of collaborative research within networks and consortia.
After completing the course, participants will be able to understand the principles of GWAS, perform a basic genome-wide association analysis, interpret results and integrate them in a genomic context by means of web-based bioinformatics resources.