To control type I error for continuous phenotypes, a statistic must have a pdf <=1 around values close to 0. We accordingly expected the TATES p-values to have a uniform distribution around 0. However, our examples using simulated data showed that it is possible to get inflated results when calculating TATES combined p-values. This concern was further evidenced in a mathematical proof for the simplest two phenotype scenario. These results call into question the use of TATES to test for association across correlated phenotypes, since the TATES test does not satisfy the theoretical assumption that the statistic must be distributed such that the pdf <=1 around 0. The implication of this finding is that TATES may not successfully summarize GWAS results across correlated phenotypes because it can produce results that are inflated (increasing the risk of erroneously rejecting the null hypothesis; Type I error).
