CADD
Combined Annotation-Dependent Depletion: a genome-wide variant deleteriousness score that integrates more than 60 genomic features in a machine learning model trained to separate simulated de novo variants from variants fixed in human populations since the human-chimpanzee split. It scores single nucleotide variants and short insertions and deletions anywhere in the reference assembly, not only missense variants.
Results are recorded on linked configurations and versions of this method. Their settings and evaluations are kept separate below.
Results on linked records
This method has no results of its own in this release. 21 linked records have results. They are not assigned to the underlying method: each record keeps its own settings and evaluations, and its scores are on its own page.
- CADD_phred_a (Cubuk et al. 2021) Configuration · configuration · 2 evaluations · 5 results
- CADD_phred_b (Cubuk et al. 2021) Configuration · configuration · 2 evaluations · 4 results
- MSC-CADD-based (Cubuk et al. 2021) Configuration · uses this model · 2 evaluations · 5 results
- CADD v1.7 PHRED, pre-computed (Pearce et al. 2026) Configuration · configuration · 2 evaluations · 2 results
- CADD (Brandes et al. 2023 head-to-head comparison) Configuration · configuration · 2 evaluations · 4 results
- CADD in-frame indel scores (Brandes et al. 2023) Configuration · configuration · 4 evaluations · 4 results
- CADD (Evo 2 paper variant effect evaluations) Configuration · configuration · 26 evaluations · 52 results
- CADD v1.7 (evaluation mode not printed (Table 4 has no Eval. column), GUANinE v1.1) Configuration · configuration · 1 evaluation · 1 result
- CADD v1.7 (Position) (evaluation mode not printed (Table 4 has no Eval. column), GUANinE v1.1) Configuration · configuration · 1 evaluation · 1 result
- CADD v1.7 (Position) (zero-shot, GUANinE v1.1) Configuration · configuration · 1 evaluation · 1 result
- CADD v1.7 (zero-shot, GUANinE v1.1) Configuration · configuration · 1 evaluation · 1 result
- CADD.LogisticRegression.chrom (TraitGym) Configuration · configuration · 2 evaluations · 2 results
- CADD.plus.RawScore (TraitGym) Configuration · configuration · 2 evaluations · 2 results
- CADD (Chen et al. 2020) Configuration · configuration · 2 evaluations · 10 results
- CADD_raw rank score, dbNSFP 5.3.1a (Lee 2026) Configuration · configuration · 3 evaluations · 6 results
- CADD (Riepe et al. 2021) Configuration · configuration · 3 evaluations · 33 results
- CADD_1.6 (Livesey and Marsh 2025) Configuration · configuration · 5 evaluations · 6 results
- CADD_1.7 (Livesey and Marsh 2025) Configuration · configuration · 6 evaluations · 7 results
- CADD (Livesey and Marsh 2025) Configuration · configuration · 1 evaluation · 1 result
- CADD [ProteinGym 144fe22 clinical summary] Configuration · configuration · 1 evaluation · 1 result
- CADD (Pejaver et al. 2022 calibration) Configuration · configuration · 3 evaluations · 10 results
Overview
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Consult the linked sources for architecture or protocol details. Missing evidence is not evidence of a missing capability.
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Evidence
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Evidence table
Inspect claims, sources and review details
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One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.
3 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Description Combined Annotation-Dependent Depletion: a genome-wide variant deleteriousness score that integrates more than 60 genomic features in a machine learning model trained to separate simulated de novo variants from variants fixed in human populations since the human-chimpanzee split. It scores single nucleotide variants and short insertions and deletions anywhere in the reference assembly, not only missense variants. Individual claims | Comprehensive assessment of computational algorithms in predicting cancer driver mutations Record description; cited Rentzsch et al. 2019, Nucleic Acids Research 47:D886 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Genome Biology 21:43, published 2020-02-20; PMC7033911 full-text XML | source checked ["automated-source-review"] · 2026-10-10 Audit detailsRemove the author-year citation from the description (issue #88 follow-up) and reword the sentence where the citation sat mid-sentence, keeping every functional fact. Independent review 2026-10-10: correct as made. Field: Claim: metadata-correction-qa-20261010-f888ec0c116647dccdf3 Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Description Combined Annotation-Dependent Depletion: a genome-wide variant deleteriousness score that integrates more than 60 genomic features in a machine learning model trained to separate simulated de novo variants from variants fixed in human populations since the human-chimpanzee split. It scores single nucleotide variants and short insertions and deletions anywhere in the reference assembly, not only missense variants. Individual claims | An openly licensed benchmark and per-gene calibration map for missense pathogenicity predictors on activating cancer drivers Record description; cited Rentzsch et al. 2019, Nucleic Acids Research 47:D886 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: bioRxiv 2026.07.16.739080 v1, posted 2026-07-23; full-text HTML page | source checked ["automated-source-review"] · 2026-10-10 Audit detailsRemove the author-year citation from the description (issue #88 follow-up) and reword the sentence where the citation sat mid-sentence, keeping every functional fact. Independent review 2026-10-10: correct as made. Field: Claim: metadata-correction-qa-20261010-f888ec0c116647dccdf3 Source artifact SHA-256: Hash scope: SHA-256 of one retrieval of the full-text HTML page, which is mutable (site chrome, metrics). The PDF request returned HTTP 429. |
| Description Combined Annotation-Dependent Depletion: a genome-wide variant deleteriousness score that integrates more than 60 genomic features in a machine learning model trained to separate simulated de novo variants from variants fixed in human populations since the human-chimpanzee split. It scores single nucleotide variants and short insertions and deletions anywhere in the reference assembly, not only missense variants. Individual claims | Benchmarking deep learning splice prediction tools using functional splice assays Record description; cited Rentzsch et al. 2019, Nucleic Acids Research 47:D886 Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Human Mutation 42(7):799, published online 2021-05-20; PMC8360004 full-text XML | source checked ["automated-source-review"] · 2026-10-10 Audit detailsRemove the author-year citation from the description (issue #88 follow-up) and reword the sentence where the citation sat mid-sentence, keeping every functional fact. Independent review 2026-10-10: correct as made. Field: Claim: metadata-correction-qa-20261010-f888ec0c116647dccdf3 Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Sources and history
Release 2026-10-22-1b7cf027e4f6 · Record review: source checked
3 source records and release history
- Comprehensive assessment of computational algorithms in predicting cancer driver mutations · Original source · Genome Biology 21:43, published 2020-02-20; PMC7033911 full-text XML
- 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
- Benchmarking deep learning splice prediction tools using functional splice assays · Original source · Human Mutation 42(7):799, published online 2021-05-20; PMC8360004 full-text XML
Technical metadata and extraction receipts
Stable ID: somatic-oncogenicity-20261009-method-cadd
- areas
- dna-genomes
- contexts
- clinical_research
- method types
- supervised_machine_learning
- reported name
- CADD
- entity level
- method
- source locator
- Algorithm lists of the cited sources
- missing metadata
- version: reason: inapplicable; note: Family record; score sources are on configurations
Related records
- configuration of: CADD_phred_a (Cubuk et al. 2021)
- configuration of: CADD_phred_b (Cubuk et al. 2021)
- uses model: MSC-CADD-based (Cubuk et al. 2021)
- configuration of: CADD v1.7 PHRED, pre-computed (Pearce et al. 2026)
- configuration of: CADD (Brandes et al. 2023 head-to-head comparison)
- configuration of: CADD in-frame indel scores (Brandes et al. 2023)
- configuration of: CADD (Evo 2 paper variant effect evaluations)
- configuration of: CADD v1.7 (evaluation mode not printed (Table 4 has no Eval. column), GUANinE v1.1)
- configuration of: CADD v1.7 (Position) (evaluation mode not printed (Table 4 has no Eval. column), GUANinE v1.1)
- configuration of: CADD v1.7 (Position) (zero-shot, GUANinE v1.1)
- configuration of: CADD v1.7 (zero-shot, GUANinE v1.1)
- configuration of: CADD.LogisticRegression.chrom (TraitGym)
- configuration of: CADD.plus.RawScore (TraitGym)
- subject: CADD: description
- configuration of: CADD (Chen et al. 2020)
- configuration of: CADD_raw rank score, dbNSFP 5.3.1a (Lee 2026)
- configuration of: CADD (Riepe et al. 2021)
- configuration of: CADD_1.6 (Livesey and Marsh 2025)
- configuration of: CADD_1.7 (Livesey and Marsh 2025)
- configuration of: CADD (Livesey and Marsh 2025)
- configuration of: CADD [ProteinGym 144fe22 clinical summary]
- configuration of: CADD (Pejaver et al. 2022 calibration)