%0 Journal Article
%T Rotation-based multiple testing in the multivariate linear model.
%A Solari A
%A Finos L
%A Goeman JJ
%J Biometrics
%V 70
%N 4
%D Dec 2014
%M 25269416
%F 1.701
%R 10.1111/biom.12238
%X In observational microarray studies, issues of confounding invariably arise. One approach to account for measured confounders is to include them as covariates in a multivariate linear model. For this model, however, the application of permutation-based multiple testing procedures is problematic because exchangeability of responses, in general, does not hold. Nevertheless, it is possible to achieve rotatability of transformed responses at the cost of a distributional assumption. We argue that rotation-based multiple testing, by allowing for adjustments for confounding, represents an important extension of permutation-based multiple testing procedures. The proposed methodology is illustrated with a microarray observational study on breast cancer tumors. Software to perform the procedure described in this article is available in the flip R package.