Figure 2.

Misclassification error, false discovery and false non-discovery rates for case A2 (results are averaged over 50 replicates). The upper plot shows the false discovery rate (FDR) and the false non-discovery rate (FNR) for case A2. The FDR is calculated as the ratio of the false positives to the number of genes called in common, while the FDR is calculated as the ratio of the false negatives to the number of genes not called in common. The true differences d_g are drawn from a Ga(2, 0.5) and the noise component experiment specific is 2 for the first experiment and 3 for the second. R(q_max) shows the minimum FDR. On the other hand, R(q_min) has a very large FDR and the improvement of the FNR is slight. As a compromise, the threshold q₂ is close to q_max, so guarantees a low FDR, but returns a larger list. It approximatively corresponds to the intersection point between the two curves of FDR and FNR. The lower plot shows the global error as the sum of FP and FN. The threshold associated with R(q₂) is very close to the minimum of the curve, that is, to the smallest global misclassification error.