Figure 2.

ROC analysis was used to compare the detection sensitivity of five metrics of gene set activation and individual genes to discriminate between two different subgroups in nine different data sets (Table 1). A Wilcoxon rank sum test was used to test the null hypothesis for each gene set and individual gene that the two different subgroups groups were drawn from the same distribution. (a-d) The four graphs show results using four different p value thresholds for pathway coherence. Shown on the y-axis is the positive rate: the percentage of the gene sets or genes declared different between the two subgroups as a function of the FDR (the x-axis). The results are averaged over all nine data sets. The operating range of the X axis, [0.0, 0.3] was chosen to correspond to the range of FDRs that might be acceptable in practice. ROC curves were also calculated for each of the nine data sets individually (Supplemental Figures F1 to F9 in 1). HG, hypergeometric; WC, Wilcoxon Z score; Z, Z score.