Genetic epidemiology holds great potential for personalised medicine and improved biological knowledge of disease processes. This course provides an introduction to the design, analysis and interpretation of genetic studies of disease, with a focus on state of the art analysis of genomewide association scans. The course is 4 days long. On days 1 and 2, basic genetics will be introduced and relevant statistical methods for linkage and association analysis will be described. Days 3 and 4 will cover the design and analysis of genomewide association scans, including emerging applications to risk prediction and biological pathway analysis. Throughout the course participants will gain practical experience of analysing genetic data in population and family studies. By the end of the course participants will have an understanding of the fundamental concepts of genetic epidemiology, will have a working knowledge of the terminology and current status of the field, and will be able to perform many basic analyses of genetic data. This course is followed by the companion course “High throughput sequencing in disease studies”.
The course consists of alternating lectures and computer practical sessions. Comprehensive course notes will be provided at the start of the course. Participants are expected to be epidemiologists, clinicians, applied statisticians or biologists with an interest in becoming familiar with, or working in, genetic epidemiology. A basic knowledge of statistics is required, including familiarity with hypothesis testing and estimation. Experience with a statistical computing package such as R is required for this course; students without experience with R, will be provided an introductory class to complete online prior to the start of the course, which should be sufficient for the purpose of the class.
Introduction to Genetic Epidemiology
Genomewide association scans (GWAS)
Methods of Assessment
There is no formal assessment but a certificate of attendance will be provided.
Participants are expected to be epidemiologists, clinicians, applied statisticians or biologists with an interest in becoming familiar with, or working in, genetic epidemiology. A basic knowledge of statistics is required, including familiarity with hypothesis testing and estimation. Experience with a statistical computing package such as R is required for this course: a basic introduction to R will be provided on day 1, but this will not be adequate for those with no experience of R or of programming in a statistical package such as Stata or a programming language such as C.
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