Fig. 3
From: Comprehensive assessment of computational algorithms in predicting cancer driver mutations
Assessment using a benchmark dataset based on OncoKB annotation. a Overview of the assessment process. The OncoKB database classifies mutations into four categories: oncogenic, likely oncogenic, likely neutral, and inconclusive. We considered “likely neutral” as negative cases, and we considered “oncogenic” mutations only or both “oncogenic” and “likely oncogenic” mutations as positive cases. b Bar plots showing the AUC scores of the 33 algorithms in the two comparisons. The red color is for oncogenic plus likely oncogenic vs. likely neutral, and green is for oncogenic vs. likely neutral. c Sensitivity and specificity of 33 algorithms. Error bars, mean ± 2SD