Identifying true positive associations in genome-wide association studies
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One of the main strategies in the search for genes that influence the risk of disease has been to compare the distribution of specific genetic variants in cases and population-based controls. It is now feasible to do this for hundreds of thousands of variants across the whole genome, instead of targeting biologically promising genes, in genome-wide association (GWA) studies. Falsely positive associations can arise due to genotyping problems, type 1 error (compounded by the large number of (correlated) statistical tests being carried out) and confounding (as a result of population stratification). Strategies for dealing with these issues will be presented and discussed with reference to a GWA study of cardiovascular disease.
This talk is part of the MRC Biostatistics Unit Seminars series.
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