Figure 2.

Limitation of existing methods. We assessed the calibration under the null of four approaches representing the state of the art for covariance matrix comparison: the Fisher method (A, B), the Jenrich test (C, D), BoxM (E, F) and Mantel test (G,H), against the proposed MANOCCA approach (I, J). Note that we applied MANOCCA directly on the product matrix thanks to the high sample size compared to the number of products. We simulated a series of 10 000 replicates, with a sample size of 1000 each, under two different null models. In the first model (A, C, E, G, I), replicates included five outcomes drawn from a multivariate normal with modest pairwise correlation. In the second model (B, D, F, H, J), closer to the expected distribution of omics data, replicates included 30 non-normal outcomes with high correlation. Calibration was derived by splitting each replicate in two random sets according to a random binary variable and testing for association between and the correlation between variables. The panels present the distribution of the P-values, expected to be uniformly distributed under this null model, for the five approaches and the two models.