(A) Prediction quality. Comparison of the sensitivity of MC EMiNEM and four alternative methods for four different noise levels (top) and four different signals graph sizes (bottom). The sensitivity is depicted on the y-axis, each frame corresponds to one parameter setting. Top: For a signals graph of 11 nodes, noisy data was generated such that for an optimal test with a type-I error (

-level) of 5%, a type II error (

-level) of

, and

would be achieved, respectively. Bottom: For a noise level corresponding to an error level of (

,

), signals graph sizes of

are investigated. We expect our application to range within the four central scenarios. The comparisons of sensitivities is a fair comparison of the prediction qualities since the specificities for all methods and parameter settings are located

(see also Fig. S3.7 in Text S1). (B) Influence of the Empirical Bayes procedure. Here, for the standard setting

and (

,

). The x-axis shows the calculated marginal posterior values

centered at

(indicated by the dashed vertical line), on the y-axis the frequency is displayed. In the table, the percentages of signals graphs scoring higher than

are provided, as well as the

-distances (relative to the maximum).