Whole-genome methylation classifier (GRAIL prototype), CCGA substudy 1
Configuration as run in the cited comparison.
Overview
Whole-genome methylation classifier (GRAIL prototype): Removes fragments with methylation states common in non-cancer samples, keeps mostly hyper- or hypo-methylated fragments with at least 5 CpGs, scores their cancer likelihood by genome location, and classifies the top-ranked fragment likelihoods with kernel logistic regression.
Consult the linked sources for architecture or protocol details. Missing evidence is not evidence of a missing capability.
Evaluations and results
3 evaluations · 3 results. Different protocols are not a single leaderboard.
Sorted by Accuracy (cancer signal origin among 127 jointly detected validation cancers) (higher is better). The best value in each column is highlighted. Decimals are rounded for display; each value links to the printed value and its source.
All 3 result rows with coverage, uncertainty and sources
Filter evaluations
Applied filters: All linked evaluations
| Tested configuration | Protocol and dataset | Finding | Evidence and details |
|---|---|---|---|
| Configuration: Whole-genome methylation classifier (GRAIL prototype), CCGA substudy 1 | Protocol: CCGA substudy 1 validation set: cancer signal origin accuracy among jointly detected cancers Dataset: CCGA substudy 1 validation cancers detected by all three representative classifiers (127) | 75% Accuracy (cancer signal origin among 127 jointly detected validation cancers) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourcectdnajam-20261010-protocol-ccga1-validation-cso-accuracy Aggregation: Not reported Evaluation of cell-free DNA approaches for multi-cancer early detection · Results, cancer signal origin prediction: 75% (95/127) |
| Configuration: Whole-genome methylation classifier (GRAIL prototype), CCGA substudy 1 | Protocol: CCGA substudy 1 training set: cancer signal sensitivity at 98% specificity under 10-fold cross-validation Dataset: CCGA substudy 1 training set (1,414 analysable participants) | 39% (36%–43%) Sensitivity at 98% specificity (training set, post hoc 98% specificity threshold) percent · higher Uncertainty: 95% CI 36 to 43. Clopper-Pearson exact binomial interval (STAR Methods, statistical analysis) Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourcectdnajam-20261010-protocol-ccga1-training-cv-sens-98spec Aggregation: Not reported Evaluation of cell-free DNA approaches for multi-cancer early detection · Table 3, row 'WG methylation', training set, sensitivity and TP/total cancer samples 328/833 |
| Configuration: Whole-genome methylation classifier (GRAIL prototype), CCGA substudy 1 | Protocol: CCGA substudy 1 validation set: cancer signal sensitivity at 98% specificity Dataset: CCGA substudy 1 validation set (847 analysable participants) | 34% (30%–39%) Sensitivity at 98% specificity (validation set, post hoc 98% specificity threshold) percent · higher Uncertainty: 95% CI 30 to 39. Clopper-Pearson exact binomial interval (STAR Methods, statistical analysis) Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceWG methylation on CCGA substudy 1 validation set: cancer signal sensitivity at 98% specificity ctdnajam-20261010-protocol-ccga1-validation-sens-98spec Aggregation: Not reported Evaluation of cell-free DNA approaches for multi-cancer early detection · Table 3, row 'WG methylation', validation set, sensitivity and TP/total cancer samples 158/464 |
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How it works, versions and access
Strengths, limitations and unresolved questions
Evidence
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Evidence table
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Sources and history
Release 2026-10-10-457d7eaef7d6 · Record review: source checked
1 source record and release history
- Evaluation of cell-free DNA approaches for multi-cancer early detection · Original source · Cancer Cell 40(12):1537-1549.e12, published 2022-12-12; publisher PDF (1-s2.0-S153561082200513X-main.pdf) as deposited by the Francis Crick Institute on figshare, 10.25418/crick.21731870.v1
Technical metadata and extraction receipts
Stable ID: ctdnajam-20261010-config-wg-methylation
- areas
- dna-genomes
- contexts
- clinical_research
- method types
- supervised_machine_learning
- reported name
- WG methylation
- foundation model eligible
- false
- source locator
- Table 2; STAR Methods, WGBS: WG methylation classifier
- parameters
- Whole-genome bisulfite sequencing of cfDNA, about 30x
- missing metadata
- version: reason: unreported; note: Prototype classifier; no release or commit is printed
Related records
- configuration of: Whole-genome methylation classifier (GRAIL prototype)
- system: WG methylation on CCGA substudy 1 validation set: cancer signal origin accuracy among jointly detected cancers
- system: WG methylation on CCGA substudy 1 training set: cancer signal sensitivity at 98% specificity under 10-fold cross-validation
- system: WG methylation on CCGA substudy 1 validation set: cancer signal sensitivity at 98% specificity