Figure 2

ROC curves for 7 filtering methods (2 groups, 200 informative features out of 2000, 200 samples, 100 simulated data sets). For each data set the sensitivity and specificity of selecting informative features using the top ranked list (1–2000 features) are averaged over 100 replications. Figure A-C show ROC curves for 7 listed filtering methods: SD-b, Precision, SD-m, BQ-GOF, TM-GOF, TQ-GOF, and BR (best rank) under different sample ratio scenarios: A. Sample size ratio 9:1 (non-CIMP/CIMP); B. Sample size ratio 1:1; C. Sample size ratio 1:9. The bottom three panels D-F are partial ROC curves obtained from the panels A-C by restricting the axis ranges to the region relevant to the diagonal line. The solid black diagonal line in Figure D-F indicates the estimated sensitivity and specificity levels for a list of 100 genes.