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The Reporting of Associations in Genome-Wide Studies

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If you have a question about this talk, please contact Nikolaos Demiris.

In the context of genome-wide association studies we critique a number of methods that have been suggested for flagging associations for further investigation. The p-value is by far the most commonly used measure, but requires careful calibration when the a priori probability of an association is small, and discards information by not considering the power associated with each test. The q-value is a frequentist method by which the false discovery rate (FDR) may be controlled. We advocate the use of the Bayes factor as a summary of the information in the data with respect to the comparison on the null and alternative hypotheses, and describe a recently-proposed approach to the calculation of the Bayes factor (Wakefield, 2007) that is easily implemented. The Bayes factor and the q-value provide complementary information and may be used to reduce the number of reported findings that are subsequently not reproducible.

Wakefield (2007). A Bayesian measure of the probability of false discovery in genetic epidemiology studies. Available on-line, to appear: American Journal of Human Genetics.

This talk is part of the MRC Biostatistics Unit Seminars series.

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