popEVE
Deep generative model that combines evolutionary and human population data to score variant deleteriousness on a scale calibrated across the proteome.
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. 2 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.
- popEVE rank score, dbNSFP 5.3.1a (Lee 2026) Configuration · configuration · 3 evaluations · 6 results
- popEVE (Livesey and Marsh 2025) Configuration · configuration · 6 evaluations · 7 results
Overview
An explanatory profile has not yet been reviewed for this record.
Consult the linked sources for architecture or protocol details. Missing evidence is not evidence of a missing capability.
Use this method
How it works, versions and access
Strengths, limitations and unresolved questions
Evidence
Source checking verifies the cited claim or transcription. It does not establish independent reproduction.
Evidence table
Inspect claims, sources and review details
Trace each statement to its source and review. A context-only reference supports the record generally; it does not verify an individual field. Source checking does not reproduce an experiment.
One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.
1 evidence row matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Description Deep generative model that combines evolutionary and human population data to score variant deleteriousness on a scale calibrated across the proteome. Individual claims | Proteome-wide model for human disease genetics (popEVE) qa-descriptions-20261011-e-source-popeve: Abstract Version: Europe PMC full-text XML for PMC12695638, Nature Genetics 2025 | source checked ["automated-source-review","ai-assisted-source-review"] · 2026-10-11 Audit detailsApproved with two corrections, both applied: the MutFormer source licence is CC BY 4.0 per the arXiv abstract page, and the MetaRNN source locator now names the Background passage. Checked the 27 Chen 2020 descriptions row by row against Table 1 (PMC7033911) and spot-checked AlphaMissense, MisFit, popEVE, VARITY, MetaRNN, MutFormer and gMVP against their abstracts; accurate. Licences on the other new sources match Europe PMC. Field: Claim: metadata-correction-edda4c75f5b01ddb5028 Source artifact SHA-256: Hash scope: SHA-256 of one retrieval of the Europe PMC full-text XML. These renderings are not always byte-stable; the article text is the evidence. |
Sources and history
Release 2026-10-22-1b7cf027e4f6 · 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
- Proteome-wide model for human disease genetics (popEVE) · Original source · Europe PMC full-text XML for PMC12695638, Nature Genetics 2025
Technical metadata and extraction receipts
Stable ID: somatic-oncogenicity-20261009-method-popeve
- areas
- dna-genomes
- contexts
- clinical_research
- method types
- specialist
- reported name
- popEVE
- 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
- subject: popEVE: description
- configuration of: popEVE rank score, dbNSFP 5.3.1a (Lee 2026)
- configuration of: popEVE (Livesey and Marsh 2025)