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In this course the participants will learn about advanced principles of genetic and epigenetic (epidemiological) research. The first three days will focus on statistical and bioinformatical follow-up of genetic variants identified from genome-wide association studies (GWAS), so-called post-GWAS analyses, in order to prioritize variants and genes that are most likely causally involved in the complex trait or disease of interest. The last day will discuss epigenome-wide association studies (EWAS). The relevant background will be explained during interactive theoretical lectures taught by experts.
The theoretically acquired knowledge will be applied in practical classes. The participant will get familiar with study design issues and the advanced statistical techniques that build on GWAS data and results such as Genetic Risk Score analyses and Mendelian Randomization designs and bioinformatic tools for functional annotation. Common (freely available) statistical programs and online databases and tools to perform genetic data analysis will be used, such as PLINK, GCTA, R, LocusZoom, Ensembl, LDLink, GTeX, etc.
At the end of the course the participant will be able to interpret the findings of a wide range of genetic epidemiological study designs, and apply several advanced forms of genetic data analysis.
4 full days.
Students are assumed to be familiar with concepts taught in the introductory course on genetic epidemiological research and data analysis
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COURSE FULL? |