approach is Fisher's method [27]. As it combines univariate p-values into one test statistic, similar to TATES, it does not suffer from a differential sign of effect. For scenarios with a negative genetic correlation, Fisher's method performed better than UV-MA and also better than TATES, except for scenarios with a residual correlation of 0.7: here it was outperformed by TATES but not by UV-MA (data not shown). The reduced performance for an opposite QTL effect was observed for UV-PCA as well, but not for scenarios with no residual trait correlation. In these scenarios, the first PC reflects the negative genetic correlation between the traits. Power is thus increased compared to UV since there is no need to multiple testing penalty.
