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In genome-wide association (GWA) studies the goal is to detect associationbetween one or more genetic markers and a given phenotype. The number ofgenetic markers in a GWA study can be in the order hundreds of thousands andtherefore multiple testing methods are needed. This paper presents a set ofpopular methods to be used to correct for multiple testing in GWA studies. Allare based on the concept of estimating an effective number of independenttests. We compare these methods using simulated data and data from the TOPstudy, and show that the effective number of independent tests is not additiveover blocks of independent genetic markers unless we assume a common value forthe local significance level. We also show that the reviewed methods based onestimating the effective number of independent tests in general do not controlthe familywise error rate.

Is the familywise error rate in genomics controlled by methods based on the effective number of independent tests?