Benchmark 2 truth set in Chen et al. 2020.
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Release 2026-10-10-7fcc3e48a123 · Evidence verified: Not verified
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50 evaluations · 250 results. Different protocols are not a single leaderboard.
Applied filters: All linked evaluations
| Tested configuration | Protocol and dataset | Finding | Evidence and details |
|---|---|---|---|
| Configuration: CADD (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.64 accuracy fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCADD on OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-median Aggregation: Not reported 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) · Additional file 9 (sheet 'Additional_file_9'), B16; Algorithm 'CADD'; column 'Accuracy (±2σ)' |
| Configuration: CADD (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.64 negative-predictive-value fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCADD on OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-median Aggregation: Not reported 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) · Additional file 9 (sheet 'Additional_file_9'), F16; Algorithm 'CADD'; column 'NPV (±2σ)' |
| Configuration: CADD (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.64 precision fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCADD on OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-median Aggregation: Not reported 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) · Additional file 9 (sheet 'Additional_file_9'), E16; Algorithm 'CADD'; column 'PPV (±2σ)' |
| Configuration: CADD (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.64 recall fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCADD on OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-median Aggregation: Not reported 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) · Additional file 9 (sheet 'Additional_file_9'), C16; Algorithm 'CADD'; column 'Sensitivity (±2σ)' |
| Configuration: CADD (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.64 specificity fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCADD on OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-median Aggregation: Not reported 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) · Additional file 9 (sheet 'Additional_file_9'), D16; Algorithm 'CADD'; column 'Specificity (±2σ)' |
| Configuration: CanDrA (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), default categorical calls (Chen et al. 2020 Additional file 10) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.49 accuracy fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceCanDrA on OncoKB benchmark (positive set not stated), default categorical calls (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-default Aggregation: Not reported 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) · Additional file 10 (sheet 'Additional_file_10'), B18; Algorithm 'CanDrA'; column 'Accuracy (±2σ)' |
| Configuration: CanDrA (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), default categorical calls (Chen et al. 2020 Additional file 10) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.46 negative-predictive-value fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceCanDrA on OncoKB benchmark (positive set not stated), default categorical calls (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-default Aggregation: Not reported 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) · Additional file 10 (sheet 'Additional_file_10'), F18; Algorithm 'CanDrA'; column 'NPV (±2σ)' |
| Configuration: CanDrA (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), default categorical calls (Chen et al. 2020 Additional file 10) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.49 precision fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceCanDrA on OncoKB benchmark (positive set not stated), default categorical calls (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-default Aggregation: Not reported 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) · Additional file 10 (sheet 'Additional_file_10'), E18; Algorithm 'CanDrA'; column 'PPV (±2σ)' |
| Configuration: CanDrA (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), default categorical calls (Chen et al. 2020 Additional file 10) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.8 recall fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceCanDrA on OncoKB benchmark (positive set not stated), default categorical calls (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-default Aggregation: Not reported 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) · Additional file 10 (sheet 'Additional_file_10'), C18; Algorithm 'CanDrA'; column 'Sensitivity (±2σ)' |
| Configuration: CanDrA (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), default categorical calls (Chen et al. 2020 Additional file 10) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.17 specificity fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceCanDrA on OncoKB benchmark (positive set not stated), default categorical calls (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-default Aggregation: Not reported 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) · Additional file 10 (sheet 'Additional_file_10'), D18; Algorithm 'CanDrA'; column 'Specificity (±2σ)' |
| Configuration: CanDrA (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.59 accuracy fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceCanDrA on OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-median Aggregation: Not reported 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) · Additional file 9 (sheet 'Additional_file_9'), B26; Algorithm 'CanDrA'; column 'Accuracy (±2σ)' |
| Configuration: CanDrA (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.59 negative-predictive-value fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceCanDrA on OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-median Aggregation: Not reported 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) · Additional file 9 (sheet 'Additional_file_9'), F26; Algorithm 'CanDrA'; column 'NPV (±2σ)' |
| Configuration: CanDrA (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.59 precision fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceCanDrA on OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-median Aggregation: Not reported 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) · Additional file 9 (sheet 'Additional_file_9'), E26; Algorithm 'CanDrA'; column 'PPV (±2σ)' |
| Configuration: CanDrA (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.59 recall fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceCanDrA on OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-median Aggregation: Not reported 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) · Additional file 9 (sheet 'Additional_file_9'), C26; Algorithm 'CanDrA'; column 'Sensitivity (±2σ)' |
| Configuration: CanDrA (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.59 specificity fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceCanDrA on OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-median Aggregation: Not reported 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) · Additional file 9 (sheet 'Additional_file_9'), D26; Algorithm 'CanDrA'; column 'Specificity (±2σ)' |
| Configuration: CHASM (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.65 accuracy fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCHASM on OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-median Aggregation: Not reported 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) · Additional file 9 (sheet 'Additional_file_9'), B15; Algorithm 'CHASM'; column 'Accuracy (±2σ)' |
| Configuration: CHASM (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.65 negative-predictive-value fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCHASM on OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-median Aggregation: Not reported 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) · Additional file 9 (sheet 'Additional_file_9'), F15; Algorithm 'CHASM'; column 'NPV (±2σ)' |
| Configuration: CHASM (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.65 precision fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCHASM on OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-median Aggregation: Not reported 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) · Additional file 9 (sheet 'Additional_file_9'), E15; Algorithm 'CHASM'; column 'PPV (±2σ)' |
| Configuration: CHASM (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.65 recall fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCHASM on OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-median Aggregation: Not reported 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) · Additional file 9 (sheet 'Additional_file_9'), C15; Algorithm 'CHASM'; column 'Sensitivity (±2σ)' |
| Configuration: CHASM (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.64 specificity fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCHASM on OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-median Aggregation: Not reported 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) · Additional file 9 (sheet 'Additional_file_9'), D15; Algorithm 'CHASM'; column 'Specificity (±2σ)' |
| Configuration: CTAT-cancer (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.63 accuracy fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCTAT-cancer on OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-median Aggregation: Not reported 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) · Additional file 9 (sheet 'Additional_file_9'), B18; Algorithm 'CTAT-cancer'; column 'Accuracy (±2σ)' |
| Configuration: CTAT-cancer (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.63 negative-predictive-value fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCTAT-cancer on OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-median Aggregation: Not reported 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) · Additional file 9 (sheet 'Additional_file_9'), F18; Algorithm 'CTAT-cancer'; column 'NPV (±2σ)' |
| Configuration: CTAT-cancer (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.63 precision fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCTAT-cancer on OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-median Aggregation: Not reported 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) · Additional file 9 (sheet 'Additional_file_9'), E18; Algorithm 'CTAT-cancer'; column 'PPV (±2σ)' |
| Configuration: CTAT-cancer (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.63 recall fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCTAT-cancer on OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-median Aggregation: Not reported 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) · Additional file 9 (sheet 'Additional_file_9'), C18; Algorithm 'CTAT-cancer'; column 'Sensitivity (±2σ)' |
| Configuration: CTAT-cancer (Chen et al. 2020) | Protocol: OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9) Dataset: OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) | 0.63 specificity fraction · higher Uncertainty: Not yet extracted: Printed as 'mean (lower-upper)' under the column header '(±2σ)': per Methods, the mean and two standard deviations over 100 random draws. That is not a confidence interval, and the schema's standard_deviation type would need a standard deviation derived from rounded bounds, so no structured uncertainty is recorded. The printed range is kept in printed_source_cell; every range is symmetric about the mean to rounding. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceCTAT-cancer on OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-oncokb-median Aggregation: Not reported 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) · Additional file 9 (sheet 'Additional_file_9'), D18; Algorithm 'CTAT-cancer'; column 'Specificity (±2σ)' |
Source checking is not independent reproduction. Release 2026-10-10-7fcc3e48a123.
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5 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| attributes.population Methods: 816 oncogenic, 1,384 likely oncogenic and 421 likely neutral mutations (271 inconclusive excluded); Results: 773 oncogenic and 497 likely neutral used in the main comparison Context-only references | Comprehensive assessment of computational algorithms in predicting cancer driver mutations Results 'Benchmark 2'; Methods 'OncoKB annotation benchmark' and 'Calculation of five evaluation metrics' Version: Genome Biology 21:43, published 2020-02-20; PMC7033911 full-text XML | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| attributes.source_locator Results 'Benchmark 2'; Methods 'OncoKB annotation benchmark' and 'Calculation of five evaluation metrics' Context-only references | Comprehensive assessment of computational algorithms in predicting cancer driver mutations Results 'Benchmark 2'; Methods 'OncoKB annotation benchmark' and 'Calculation of five evaluation metrics' Version: Genome Biology 21:43, published 2020-02-20; PMC7033911 full-text XML | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| attributes.split 400 positives and 400 negatives drawn at random, 100 times, for the binary metrics Context-only references | Comprehensive assessment of computational algorithms in predicting cancer driver mutations Results 'Benchmark 2'; Methods 'OncoKB annotation benchmark' and 'Calculation of five evaluation metrics' Version: Genome Biology 21:43, published 2020-02-20; PMC7033911 full-text XML | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| description Benchmark 2 truth set in Chen et al. 2020. Context-only references | Comprehensive assessment of computational algorithms in predicting cancer driver mutations Results 'Benchmark 2'; Methods 'OncoKB annotation benchmark' and 'Calculation of five evaluation metrics' Version: Genome Biology 21:43, published 2020-02-20; PMC7033911 full-text XML | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| name OncoKB-annotated somatic missense mutations (oncogenic, likely oncogenic and likely neutral) Context-only references | Comprehensive assessment of computational algorithms in predicting cancer driver mutations Results 'Benchmark 2'; Methods 'OncoKB annotation benchmark' and 'Calculation of five evaluation metrics' Version: Genome Biology 21:43, published 2020-02-20; PMC7033911 full-text XML | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Release 2026-10-10-7fcc3e48a123 · Record review: source checked
Stable ID: somatic-oncogenicity-20261009-data-chen2020-oncokb