Protocol

OncoKB benchmark (positive set not stated), median-score threshold (Chen et al. 2020 Additional file 9)

Accuracy, sensitivity, specificity, PPV and NPV of 33 predictors using median-score threshold.

Overview

Accuracy, sensitivity, specificity, PPV and NPV of 33 predictors using median-score threshold.

Consult the linked sources for architecture or protocol details. Missing evidence is not evidence of a missing capability.

33 recorded evaluations, 165 metric rows. A comparison chart has not yet been validated for these results. The table retains the individual findings and their sources.

View coverage and remaining gaps across all benchmarks

Results

Results are available, but no reviewed comparison panel is linked in this release.

All evaluations

33 evaluations · 165 results. Different protocols are not a single leaderboard.

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Tested model or methodProtocolDatasetEvaluation setupMetricEvidence origin

Applied filters: All linked evaluations

Exact evaluated configurations and original reported results
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 checked Methods, coverage and source CADD 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 checked Methods, coverage and source CADD 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 checked Methods, coverage and source CADD 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 checked Methods, coverage and source CADD 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 checked Methods, coverage and source CADD 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), 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 checked Methods, coverage and source CanDrA 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 checked Methods, coverage and source CanDrA 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 checked Methods, coverage and source CanDrA 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 checked Methods, coverage and source CanDrA 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 checked Methods, coverage and source CanDrA 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 checked Methods, coverage and source CHASM 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 checked Methods, coverage and source CHASM 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 checked Methods, coverage and source CHASM 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 checked Methods, coverage and source CHASM 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 checked Methods, coverage and source CHASM 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 checked Methods, coverage and source CTAT-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 checked Methods, coverage and source CTAT-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 checked Methods, coverage and source CTAT-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 checked Methods, coverage and source CTAT-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 checked Methods, coverage and source CTAT-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)'
Configuration: CTAT-population (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)	0.66 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 checked Methods, coverage and source CTAT-population 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'), B7; Algorithm 'CTAT-population'; column 'Accuracy (±2σ)'
Configuration: CTAT-population (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)	0.66 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 checked Methods, coverage and source CTAT-population 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'), F7; Algorithm 'CTAT-population'; column 'NPV (±2σ)'
Configuration: CTAT-population (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)	0.66 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 checked Methods, coverage and source CTAT-population 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'), E7; Algorithm 'CTAT-population'; column 'PPV (±2σ)'
Configuration: CTAT-population (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)	0.66 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 checked Methods, coverage and source CTAT-population 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'), C7; Algorithm 'CTAT-population'; column 'Sensitivity (±2σ)'
Configuration: CTAT-population (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)	0.66 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 checked Methods, coverage and source CTAT-population 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'), D7; Algorithm 'CTAT-population'; column 'Specificity (±2σ)'

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Comprehensive assessment of computational algorithms in predicting cancer driver mutations · Original source · Genome Biology 21:43, published 2020-02-20; PMC7033911 full-text XML
Chen et al. 2020, Additional file 9: Performance metrics of 33 algorithms, median-score threshold, benchmark 2 (OncoKB) · Original source · 13059_2020_1954_MOESM9_ESM.xlsx

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Stable ID: somatic-oncogenicity-20261009-protocol-chen2020-oncokb-median

areas: dna-genomes
contexts: clinical_research
protocol: Binary predictions by median-score threshold (each algorithm's median score on the benchmark) compared with the truth labels with reportROC; 400 positives and 400 negatives sampled 100 times; mean and two standard deviations reported.
version: Additional file 9
metric: accuracy
limitations: Binary metrics are means over 100 random draws of 400 positives and 400 negatives; the bracketed range is the mean plus or minus two standard deviations, not a confidence interval.; Predictor scores date from dbNSFP v4.0 and 2019 web servers; current releases (for example AlphaMissense, CHASMplus, BoostDM) are not included.; The threshold is each algorithm's median score on the benchmark draw, which is not available when classifying a new variant; with balanced draws it makes sensitivity, specificity, PPV and NPV nearly equal, so the table ranks tools rather than measuring a usable operating point.; OncoKB annotations are biased towards known, often actionable cancer genes (Discussion).; Some predictors were trained on known cancer mutations, so performance on literature-curated drivers may be inflated.; The OncoKB set has 421 or 497 likely neutral negatives (Methods and Results disagree) and 400 are drawn per repeat, so the draws overlap heavily and the spread understates sampling uncertainty. Results and Methods also disagree on the positive counts, and which positive set fed the binary metrics is not stated.; Two authors (H. Liang, G.B. Mills) co-developed CanDrA (reference 7), and the cell viability labels come from the same group's assays; CanDrA rows are author_reported.
source locator: Additional file 9; Methods 'Calculation of five evaluation metrics based on categorical predictions'

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