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PROVEAN (Chen et al. 2020)

PROVEAN scores as used in the cited comparison.

Overview

PROVEAN scores as used in the cited comparison.

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

Evaluations and results

4 evaluations · 20 results. Different protocols are not a single leaderboard.

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Exact evaluated configurations and original reported results
Tested configuration	Protocol and dataset	Finding	Evidence and details
Configuration: PROVEAN (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)	0.67 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 PROVEAN 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'), B3; Algorithm 'PROVEAN'; column 'Accuracy (±2σ)'
Configuration: PROVEAN (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 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 PROVEAN 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'), F3; Algorithm 'PROVEAN'; column 'NPV (±2σ)'
Configuration: PROVEAN (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)	0.61 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 PROVEAN 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'), E3; Algorithm 'PROVEAN'; column 'PPV (±2σ)'
Configuration: PROVEAN (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)	0.89 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 PROVEAN 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'), C3; Algorithm 'PROVEAN'; column 'Sensitivity (±2σ)'
Configuration: PROVEAN (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)	0.45 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 PROVEAN 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'), D3; Algorithm 'PROVEAN'; column 'Specificity (±2σ)'
Configuration: PROVEAN (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)	0.69 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 PROVEAN 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'), B2; Algorithm 'PROVEAN'; column 'Accuracy (±2σ)'
Configuration: PROVEAN (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)	0.7 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 PROVEAN 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'), F2; Algorithm 'PROVEAN'; column 'NPV (±2σ)'
Configuration: PROVEAN (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)	0.69 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 PROVEAN 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'), E2; Algorithm 'PROVEAN'; column 'PPV (±2σ)'
Configuration: PROVEAN (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)	0.7 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 PROVEAN 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'), C2; Algorithm 'PROVEAN'; column 'Sensitivity (±2σ)'
Configuration: PROVEAN (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)	0.68 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 PROVEAN 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'), D2; Algorithm 'PROVEAN'; column 'Specificity (±2σ)'
Configuration: PROVEAN (Chen et al. 2020)	Protocol: Cell viability drivers versus neutral, default categorical calls (Chen et al. 2020 Additional file 22) Dataset: Missense mutations with Ba/F3 and MCF10A cell viability calls (published and new)	0.62 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 PROVEAN on cell viability drivers versus neutral, default categorical calls (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-viability-default Aggregation: Not reported 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) · Additional file 22 (sheet 'Additional_file_22'), B3; Algorithm 'PROVEAN'; column 'Accuracy (±2σ)'
Configuration: PROVEAN (Chen et al. 2020)	Protocol: Cell viability drivers versus neutral, default categorical calls (Chen et al. 2020 Additional file 22) Dataset: Missense mutations with Ba/F3 and MCF10A cell viability calls (published and new)	0.7 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 PROVEAN on cell viability drivers versus neutral, default categorical calls (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-viability-default Aggregation: Not reported 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) · Additional file 22 (sheet 'Additional_file_22'), F3; Algorithm 'PROVEAN'; column 'NPV (±2σ)'
Configuration: PROVEAN (Chen et al. 2020)	Protocol: Cell viability drivers versus neutral, default categorical calls (Chen et al. 2020 Additional file 22) Dataset: Missense mutations with Ba/F3 and MCF10A cell viability calls (published and new)	0.57 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 PROVEAN on cell viability drivers versus neutral, default categorical calls (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-viability-default Aggregation: Not reported 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) · Additional file 22 (sheet 'Additional_file_22'), E3; Algorithm 'PROVEAN'; column 'PPV (±2σ)'
Configuration: PROVEAN (Chen et al. 2020)	Protocol: Cell viability drivers versus neutral, default categorical calls (Chen et al. 2020 Additional file 22) Dataset: Missense mutations with Ba/F3 and MCF10A cell viability calls (published and new)	0.78 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 PROVEAN on cell viability drivers versus neutral, default categorical calls (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-viability-default Aggregation: Not reported 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) · Additional file 22 (sheet 'Additional_file_22'), C3; Algorithm 'PROVEAN'; column 'Sensitivity (±2σ)'
Configuration: PROVEAN (Chen et al. 2020)	Protocol: Cell viability drivers versus neutral, default categorical calls (Chen et al. 2020 Additional file 22) Dataset: Missense mutations with Ba/F3 and MCF10A cell viability calls (published and new)	0.48 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 PROVEAN on cell viability drivers versus neutral, default categorical calls (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-viability-default Aggregation: Not reported 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) · Additional file 22 (sheet 'Additional_file_22'), D3; Algorithm 'PROVEAN'; column 'Specificity (±2σ)'
Configuration: PROVEAN (Chen et al. 2020)	Protocol: Cell viability drivers versus neutral, median-score threshold (Chen et al. 2020 Additional file 21) Dataset: Missense mutations with Ba/F3 and MCF10A cell viability calls (published and new)	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	Independent external evaluation · Source checked Methods, coverage and source PROVEAN on cell viability drivers versus neutral, median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-viability-median Aggregation: Not reported 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) · Additional file 21 (sheet 'Additional_file_21'), B25; Algorithm 'PROVEAN'; column 'Accuracy (±2σ)'
Configuration: PROVEAN (Chen et al. 2020)	Protocol: Cell viability drivers versus neutral, median-score threshold (Chen et al. 2020 Additional file 21) Dataset: Missense mutations with Ba/F3 and MCF10A cell viability calls (published and new)	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	Independent external evaluation · Source checked Methods, coverage and source PROVEAN on cell viability drivers versus neutral, median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-viability-median Aggregation: Not reported 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) · Additional file 21 (sheet 'Additional_file_21'), F25; Algorithm 'PROVEAN'; column 'NPV (±2σ)'
Configuration: PROVEAN (Chen et al. 2020)	Protocol: Cell viability drivers versus neutral, median-score threshold (Chen et al. 2020 Additional file 21) Dataset: Missense mutations with Ba/F3 and MCF10A cell viability calls (published and new)	0.58 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 PROVEAN on cell viability drivers versus neutral, median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-viability-median Aggregation: Not reported 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) · Additional file 21 (sheet 'Additional_file_21'), E25; Algorithm 'PROVEAN'; column 'PPV (±2σ)'
Configuration: PROVEAN (Chen et al. 2020)	Protocol: Cell viability drivers versus neutral, median-score threshold (Chen et al. 2020 Additional file 21) Dataset: Missense mutations with Ba/F3 and MCF10A cell viability calls (published and new)	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	Independent external evaluation · Source checked Methods, coverage and source PROVEAN on cell viability drivers versus neutral, median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-viability-median Aggregation: Not reported 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) · Additional file 21 (sheet 'Additional_file_21'), C25; Algorithm 'PROVEAN'; column 'Sensitivity (±2σ)'
Configuration: PROVEAN (Chen et al. 2020)	Protocol: Cell viability drivers versus neutral, median-score threshold (Chen et al. 2020 Additional file 21) Dataset: Missense mutations with Ba/F3 and MCF10A cell viability calls (published and new)	0.58 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 PROVEAN on cell viability drivers versus neutral, median-score threshold (Chen et al. 2020) somatic-oncogenicity-20261009-protocol-chen2020-viability-median Aggregation: Not reported 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) · Additional file 21 (sheet 'Additional_file_21'), D25; Algorithm 'PROVEAN'; 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

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Technical metadata and extraction receipts

Stable ID: somatic-oncogenicity-20261009-config-chen2020-provean

areas: dna-genomes
contexts: clinical_research
method types: specialist
reported name: PROVEAN
version: Scores from dbNSFP v4.0
foundation model eligible: false
protocol: Delta alignment score; features: Sequence homology
source locator: Table 1; Methods 'Inter-correlation analysis among algorithms'
configuration: default positive category: Deleterious; default negative category: Neutral

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