| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 10: Performance metrics of 17 algorithms, default categories, benchmark 2 (OncoKB) | FATHMM-XF (Chen et al. 2020) | OncoKB benchmark (positive set not stated), default categorical calls (Chen et al. 2020 Additional file 10) | Negative predictive value (OncoKB benchmark (positive set not stated), default categorical calls) | 0.85 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 10: Performance metrics of 17 algorithms, default categories, benchmark 2 (OncoKB) | FATHMM-XF (Chen et al. 2020) | OncoKB benchmark (positive set not stated), default categorical calls (Chen et al. 2020 Additional file 10) | Precision (OncoKB benchmark (positive set not stated), default categorical calls) | 0.6 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 10: Performance metrics of 17 algorithms, default categories, benchmark 2 (OncoKB) | FATHMM-XF (Chen et al. 2020) | OncoKB benchmark (positive set not stated), default categorical calls (Chen et al. 2020 Additional file 10) | Recall (OncoKB benchmark (positive set not stated), default categorical calls) | 0.93 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 10: Performance metrics of 17 algorithms, default categories, benchmark 2 (OncoKB) | FATHMM-XF (Chen et al. 2020) | OncoKB benchmark (positive set not stated), default categorical calls (Chen et al. 2020 Additional file 10) | Specificity (OncoKB benchmark (positive set not stated), default categorical calls) | 0.39 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 9: Performance metrics of 33 algorithms, median-score threshold, benchmark 2 (OncoKB) | FATHMM-XF (Chen et al. 2020) | OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) | Accuracy (OncoKB benchmark (positive set not stated), median-score threshold) | 0.65 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 9: Performance metrics of 33 algorithms, median-score threshold, benchmark 2 (OncoKB) | FATHMM-XF (Chen et al. 2020) | OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) | Negative predictive value (OncoKB benchmark (positive set not stated), median-score threshold) | 0.65 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 9: Performance metrics of 33 algorithms, median-score threshold, benchmark 2 (OncoKB) | FATHMM-XF (Chen et al. 2020) | OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) | Precision (OncoKB benchmark (positive set not stated), median-score threshold) | 0.65 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 9: Performance metrics of 33 algorithms, median-score threshold, benchmark 2 (OncoKB) | FATHMM-XF (Chen et al. 2020) | OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) | Recall (OncoKB benchmark (positive set not stated), median-score threshold) | 0.65 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 9: Performance metrics of 33 algorithms, median-score threshold, benchmark 2 (OncoKB) | FATHMM-XF (Chen et al. 2020) | OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) | Specificity (OncoKB benchmark (positive set not stated), median-score threshold) | 0.65 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 22: Performance metrics of 17 algorithms, default categories, benchmark 5 (cell viability) | FATHMM-XF (Chen et al. 2020) | Cell viability drivers versus neutral, default categorical calls (Chen et al. 2020 Additional file 22) | Accuracy (cell viability drivers versus neutral, default categorical calls) | 0.59 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 22: Performance metrics of 17 algorithms, default categories, benchmark 5 (cell viability) | FATHMM-XF (Chen et al. 2020) | Cell viability drivers versus neutral, default categorical calls (Chen et al. 2020 Additional file 22) | Negative predictive value (cell viability drivers versus neutral, default categorical calls) | 0.72 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 22: Performance metrics of 17 algorithms, default categories, benchmark 5 (cell viability) | FATHMM-XF (Chen et al. 2020) | Cell viability drivers versus neutral, default categorical calls (Chen et al. 2020 Additional file 22) | Precision (cell viability drivers versus neutral, default categorical calls) | 0.56 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 22: Performance metrics of 17 algorithms, default categories, benchmark 5 (cell viability) | FATHMM-XF (Chen et al. 2020) | Cell viability drivers versus neutral, default categorical calls (Chen et al. 2020 Additional file 22) | Recall (cell viability drivers versus neutral, default categorical calls) | 0.89 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 22: Performance metrics of 17 algorithms, default categories, benchmark 5 (cell viability) | FATHMM-XF (Chen et al. 2020) | Cell viability drivers versus neutral, default categorical calls (Chen et al. 2020 Additional file 22) | Specificity (cell viability drivers versus neutral, default categorical calls) | 0.28 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 21: Performance metrics of 33 algorithms, median-score threshold, benchmark 5 (cell viability) | FATHMM-XF (Chen et al. 2020) | Cell viability drivers versus neutral, median-score threshold (Chen et al. 2020 Additional file 21) | Accuracy (cell viability drivers versus neutral, median-score threshold) | 0.63 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 21: Performance metrics of 33 algorithms, median-score threshold, benchmark 5 (cell viability) | FATHMM-XF (Chen et al. 2020) | Cell viability drivers versus neutral, median-score threshold (Chen et al. 2020 Additional file 21) | Negative predictive value (cell viability drivers versus neutral, median-score threshold) | 0.63 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 21: Performance metrics of 33 algorithms, median-score threshold, benchmark 5 (cell viability) | FATHMM-XF (Chen et al. 2020) | Cell viability drivers versus neutral, median-score threshold (Chen et al. 2020 Additional file 21) | Precision (cell viability drivers versus neutral, median-score threshold) | 0.63 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 21: Performance metrics of 33 algorithms, median-score threshold, benchmark 5 (cell viability) | FATHMM-XF (Chen et al. 2020) | Cell viability drivers versus neutral, median-score threshold (Chen et al. 2020 Additional file 21) | Recall (cell viability drivers versus neutral, median-score threshold) | 0.63 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 21: Performance metrics of 33 algorithms, median-score threshold, benchmark 5 (cell viability) | FATHMM-XF (Chen et al. 2020) | Cell viability drivers versus neutral, median-score threshold (Chen et al. 2020 Additional file 21) | Specificity (cell viability drivers versus neutral, median-score threshold) | 0.63 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 10: Performance metrics of 17 algorithms, default categories, benchmark 2 (OncoKB) | PrimateAI (Chen et al. 2020) | OncoKB benchmark (positive set not stated), default categorical calls (Chen et al. 2020 Additional file 10) | Negative predictive value (OncoKB benchmark (positive set not stated), default categorical calls) | 0.71 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 10: Performance metrics of 17 algorithms, default categories, benchmark 2 (OncoKB) | PrimateAI (Chen et al. 2020) | OncoKB benchmark (positive set not stated), default categorical calls (Chen et al. 2020 Additional file 10) | Precision (OncoKB benchmark (positive set not stated), default categorical calls) | 0.63 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 10: Performance metrics of 17 algorithms, default categories, benchmark 2 (OncoKB) | PrimateAI (Chen et al. 2020) | OncoKB benchmark (positive set not stated), default categorical calls (Chen et al. 2020 Additional file 10) | Recall (OncoKB benchmark (positive set not stated), default categorical calls) | 0.77 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 10: Performance metrics of 17 algorithms, default categories, benchmark 2 (OncoKB) | PrimateAI (Chen et al. 2020) | OncoKB benchmark (positive set not stated), default categorical calls (Chen et al. 2020 Additional file 10) | Specificity (OncoKB benchmark (positive set not stated), default categorical calls) | 0.55 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 9: Performance metrics of 33 algorithms, median-score threshold, benchmark 2 (OncoKB) | PrimateAI (Chen et al. 2020) | OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) | Accuracy (OncoKB benchmark (positive set not stated), median-score threshold) | 0.66 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 9: Performance metrics of 33 algorithms, median-score threshold, benchmark 2 (OncoKB) | PrimateAI (Chen et al. 2020) | OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) | Negative predictive value (OncoKB benchmark (positive set not stated), median-score threshold) | 0.66 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 9: Performance metrics of 33 algorithms, median-score threshold, benchmark 2 (OncoKB) | PrimateAI (Chen et al. 2020) | OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) | Precision (OncoKB benchmark (positive set not stated), median-score threshold) | 0.66 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 9: Performance metrics of 33 algorithms, median-score threshold, benchmark 2 (OncoKB) | PrimateAI (Chen et al. 2020) | OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) | Recall (OncoKB benchmark (positive set not stated), median-score threshold) | 0.66 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 9: Performance metrics of 33 algorithms, median-score threshold, benchmark 2 (OncoKB) | PrimateAI (Chen et al. 2020) | OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) | Specificity (OncoKB benchmark (positive set not stated), median-score threshold) | 0.66 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 22: Performance metrics of 17 algorithms, default categories, benchmark 5 (cell viability) | PrimateAI (Chen et al. 2020) | Cell viability drivers versus neutral, default categorical calls (Chen et al. 2020 Additional file 22) | Accuracy (cell viability drivers versus neutral, default categorical calls) | 0.65 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 22: Performance metrics of 17 algorithms, default categories, benchmark 5 (cell viability) | PrimateAI (Chen et al. 2020) | Cell viability drivers versus neutral, default categorical calls (Chen et al. 2020 Additional file 22) | Negative predictive value (cell viability drivers versus neutral, default categorical calls) | 0.7 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 22: Performance metrics of 17 algorithms, default categories, benchmark 5 (cell viability) | PrimateAI (Chen et al. 2020) | Cell viability drivers versus neutral, default categorical calls (Chen et al. 2020 Additional file 22) | Precision (cell viability drivers versus neutral, default categorical calls) | 0.63 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 22: Performance metrics of 17 algorithms, default categories, benchmark 5 (cell viability) | PrimateAI (Chen et al. 2020) | Cell viability drivers versus neutral, default categorical calls (Chen et al. 2020 Additional file 22) | Recall (cell viability drivers versus neutral, default categorical calls) | 0.79 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 22: Performance metrics of 17 algorithms, default categories, benchmark 5 (cell viability) | PrimateAI (Chen et al. 2020) | Cell viability drivers versus neutral, default categorical calls (Chen et al. 2020 Additional file 22) | Specificity (cell viability drivers versus neutral, default categorical calls) | 0.52 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 21: Performance metrics of 33 algorithms, median-score threshold, benchmark 5 (cell viability) | PrimateAI (Chen et al. 2020) | Cell viability drivers versus neutral, median-score threshold (Chen et al. 2020 Additional file 21) | Accuracy (cell viability drivers versus neutral, median-score threshold) | 0.7 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 21: Performance metrics of 33 algorithms, median-score threshold, benchmark 5 (cell viability) | PrimateAI (Chen et al. 2020) | Cell viability drivers versus neutral, median-score threshold (Chen et al. 2020 Additional file 21) | Negative predictive value (cell viability drivers versus neutral, median-score threshold) | 0.7 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 21: Performance metrics of 33 algorithms, median-score threshold, benchmark 5 (cell viability) | PrimateAI (Chen et al. 2020) | Cell viability drivers versus neutral, median-score threshold (Chen et al. 2020 Additional file 21) | Precision (cell viability drivers versus neutral, median-score threshold) | 0.7 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 21: Performance metrics of 33 algorithms, median-score threshold, benchmark 5 (cell viability) | PrimateAI (Chen et al. 2020) | Cell viability drivers versus neutral, median-score threshold (Chen et al. 2020 Additional file 21) | Recall (cell viability drivers versus neutral, median-score threshold) | 0.7 |
|---|
| Comprehensive assessment of computational algorithms in predicting cancer driver mutations; Chen et al. 2020, Additional file 21: Performance metrics of 33 algorithms, median-score threshold, benchmark 5 (cell viability) | PrimateAI (Chen et al. 2020) | Cell viability drivers versus neutral, median-score threshold (Chen et al. 2020 Additional file 21) | Specificity (cell viability drivers versus neutral, median-score threshold) | 0.7 |
|---|