only one of many highly correlated phenotypes (Figure 1g: D1,E1). The power of MANOVA drops if the phenotypic correlations are lower, or if multiple phenotypes are subject to the GV effect. In contrast, TATES is only slightly less powerful than the sum score procedure if the phenotypes correlate substantially (Figure 1g: A1,A2), and clearly more powerful than MANOVA in this condition. TATES outperforms both other procedures if the GV affects multiple, but not all correlated phenotypes (power TATES is 1.5–2 times higher, Figure 1g: B1,C1), and is approximately as good as, or better than, MANOVA, if the GV effect is specific to one of multiple phenotypes that correlate .30 or lower (Figure 1g: E2,E3,F1–3). In 7 of our 12 scenarios, the power of TATES was 1.5 to 2 times higher than the power of MANOVA.
