We benchmarked the performance of our method against 7 previously published methods for cancer gene identification based on the sequencing data of 11,873 samples spanning 28 different cancer types. To benchmark the performance of a method, we sorted genes according to the significance values (adjusted for multiple testing) returned by the method. As a conservative approximation of the true-positive rate we used Cancer Gene Census (CGC) genes and OncoKB genes to derive ROC and precision-recall curves. We quantified the performance of each method as the area under the ROC curve (AUC) for the top 150 (a) or 1000 (b) non-CGC/OncoKB genes, respectively. Further, we determined the precision at 5% recall for each method (c). This figure compares the performance measures derived from the CGC (x-axis) and OncoKB (y-axis) databases. Each dot represents the AUC/precision of a different method (dot color) for an individual cancer type. The concordance between CGC and OncoKB measures suggests that our measure of performance does not entirely depend on the dataset used to approximate the true-positive rate.