Configuration

BayesDel_addAF rank score, dbNSFP 5.3.1a (Lee 2026)

BayesDel_addAF as scored in the cited benchmark.

Overview

BayesDel_addAF as scored in the cited benchmark.

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

Evaluations and results

3 evaluations · 6 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: BayesDel_addAF rank score, dbNSFP 5.3.1a (Lee 2026)	Protocol: CGC missense oncogenicity, all genes (Lee 2026, OncoCal tool_performance.tsv) Dataset: Missense variants in 768 Cancer Gene Census genes with open oncogenicity labels	0.712 average-precision unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source BayesDel_addAF on CGC missense, all genes (Lee 2026) somatic-oncogenicity-20261009-protocol-lee2026-all Aggregation: Not reported An openly licensed benchmark and per-gene calibration map for missense pathogenicity predictors on activating cancer drivers; OncoCal repository, tables/tool_performance.tsv (per-tool AUROC and AUPRC by gene role) · OncoCal tables/tool_performance.tsv at commit 40b7770f2a76, row tool 'BayesDel_addAF', group 'all', column 'AUPRC'
Configuration: BayesDel_addAF rank score, dbNSFP 5.3.1a (Lee 2026)	Protocol: CGC missense oncogenicity, all genes (Lee 2026, OncoCal tool_performance.tsv) Dataset: Missense variants in 768 Cancer Gene Census genes with open oncogenicity labels	0.864 auroc unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source BayesDel_addAF on CGC missense, all genes (Lee 2026) somatic-oncogenicity-20261009-protocol-lee2026-all Aggregation: Not reported An openly licensed benchmark and per-gene calibration map for missense pathogenicity predictors on activating cancer drivers; OncoCal repository, tables/tool_performance.tsv (per-tool AUROC and AUPRC by gene role) · OncoCal tables/tool_performance.tsv at commit 40b7770f2a76, row tool 'BayesDel_addAF', group 'all', column 'AUROC'
Configuration: BayesDel_addAF rank score, dbNSFP 5.3.1a (Lee 2026)	Protocol: CGC missense oncogenicity, oncogenes (gain of function) (Lee 2026, OncoCal tool_performance.tsv) Dataset: Missense variants in 768 Cancer Gene Census genes with open oncogenicity labels	0.764 average-precision unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source BayesDel_addAF on CGC missense, oncogenes (gain of function) (Lee 2026) somatic-oncogenicity-20261009-protocol-lee2026-oncogene Aggregation: Not reported An openly licensed benchmark and per-gene calibration map for missense pathogenicity predictors on activating cancer drivers; OncoCal repository, tables/tool_performance.tsv (per-tool AUROC and AUPRC by gene role) · OncoCal tables/tool_performance.tsv at commit 40b7770f2a76, row tool 'BayesDel_addAF', group 'oncogene', column 'AUPRC'
Configuration: BayesDel_addAF rank score, dbNSFP 5.3.1a (Lee 2026)	Protocol: CGC missense oncogenicity, oncogenes (gain of function) (Lee 2026, OncoCal tool_performance.tsv) Dataset: Missense variants in 768 Cancer Gene Census genes with open oncogenicity labels	0.878 auroc unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source BayesDel_addAF on CGC missense, oncogenes (gain of function) (Lee 2026) somatic-oncogenicity-20261009-protocol-lee2026-oncogene Aggregation: Not reported An openly licensed benchmark and per-gene calibration map for missense pathogenicity predictors on activating cancer drivers; OncoCal repository, tables/tool_performance.tsv (per-tool AUROC and AUPRC by gene role) · OncoCal tables/tool_performance.tsv at commit 40b7770f2a76, row tool 'BayesDel_addAF', group 'oncogene', column 'AUROC'
Configuration: BayesDel_addAF rank score, dbNSFP 5.3.1a (Lee 2026)	Protocol: CGC missense oncogenicity, tumour suppressors (loss of function) (Lee 2026, OncoCal tool_performance.tsv) Dataset: Missense variants in 768 Cancer Gene Census genes with open oncogenicity labels	0.684 average-precision unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source BayesDel_addAF on CGC missense, tumour suppressors (loss of function) (Lee 2026) somatic-oncogenicity-20261009-protocol-lee2026-tsg Aggregation: Not reported An openly licensed benchmark and per-gene calibration map for missense pathogenicity predictors on activating cancer drivers; OncoCal repository, tables/tool_performance.tsv (per-tool AUROC and AUPRC by gene role) · OncoCal tables/tool_performance.tsv at commit 40b7770f2a76, row tool 'BayesDel_addAF', group 'TSG', column 'AUPRC'
Configuration: BayesDel_addAF rank score, dbNSFP 5.3.1a (Lee 2026)	Protocol: CGC missense oncogenicity, tumour suppressors (loss of function) (Lee 2026, OncoCal tool_performance.tsv) Dataset: Missense variants in 768 Cancer Gene Census genes with open oncogenicity labels	0.892 auroc unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source BayesDel_addAF on CGC missense, tumour suppressors (loss of function) (Lee 2026) somatic-oncogenicity-20261009-protocol-lee2026-tsg Aggregation: Not reported An openly licensed benchmark and per-gene calibration map for missense pathogenicity predictors on activating cancer drivers; OncoCal repository, tables/tool_performance.tsv (per-tool AUROC and AUPRC by gene role) · OncoCal tables/tool_performance.tsv at commit 40b7770f2a76, row tool 'BayesDel_addAF', group 'TSG', column 'AUROC'

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Release 2026-10-10-6e93f504adfc · Record review: source checked

2 source records and release history

An openly licensed benchmark and per-gene calibration map for missense pathogenicity predictors on activating cancer drivers · Original source · bioRxiv 2026.07.16.739080 v1, posted 2026-07-23; full-text HTML page
OncoCal repository, tables/tool_performance.tsv (per-tool AUROC and AUPRC by gene role) · Original source · commit 40b7770f2a768ba800c4f4c6b48e2bfe967ed14a (2026-07-11)

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Technical metadata and extraction receipts

Stable ID: somatic-oncogenicity-20261009-config-lee2026-bayesdel-addaf

areas: dna-genomes
contexts: clinical_research
method types: supervised_machine_learning
reported name: BayesDel_addAF
version: dbNSFP 5.3.1a rank score (GRCh38)
foundation model eligible: false
source locator: OncoCal tool_performance.tsv column 'tool'; preprint Methods 'Features'

Related records

configuration of: BayesDel
system: BayesDel_addAF on CGC missense, all genes (Lee 2026)
system: BayesDel_addAF on CGC missense, oncogenes (gain of function) (Lee 2026)
system: BayesDel_addAF on CGC missense, tumour suppressors (loss of function) (Lee 2026)

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