Somatic copy number classifier with matched white-blood-cell correction (GRAIL prototype), CCGA substudy 1

Overview

Somatic copy number classifier with matched white-blood-cell correction (GRAIL prototype): As the SCNA classifier, with white-blood-cell WGS at the same depth used to remove clonal haematopoiesis noise.

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Evaluations and results

2 evaluations · 2 results. Different protocols are not a single leaderboard.

Sorted by Sensitivity at 98% specificity (training set, post hoc 98% specificity threshold) (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.

Tested configuration	Protocol and dataset	Sensitivity at 98% specificity (training set, post hoc 98% specificity threshold)	Sensitivity at 98% specificity (validation set, post hoc 98% specificity threshold)
Somatic copy number classifier with matched white-blood-cell correction (GRAIL prototype), CCGA substudy 1Evaluation	CCGA substudy 1 training set: cancer signal sensitivity at 98% specificity under 10-fold cross-validation, CCGA substudy 1 training set (1,414 analysable participants)	33% (30%–37%)	Not reported
Somatic copy number classifier with matched white-blood-cell correction (GRAIL prototype), CCGA substudy 1Evaluation	CCGA substudy 1 validation set: cancer signal sensitivity at 98% specificity, CCGA substudy 1 validation set (847 analysable participants)	Not reported	30% (26%–34%)

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Exact evaluated configurations and original reported results
Tested configuration	Protocol and dataset	Finding	Evidence and details
Configuration: Somatic copy number classifier with matched white-blood-cell correction (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)	33% (30%–37%) Sensitivity at 98% specificity (training set, post hoc 98% specificity threshold) percent · higher Uncertainty: 95% CI 30 to 37. Clopper-Pearson exact binomial interval (STAR Methods, statistical analysis) Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source SCNA-WBC on CCGA substudy 1 training set: cancer signal sensitivity at 98% specificity under 10-fold cross-validation ctdnajam-20261010-protocol-ccga1-training-cv-sens-98spec Aggregation: Not reported Evaluation of cell-free DNA approaches for multi-cancer early detection · Table 3, row 'SCNA-WBC', training set, sensitivity and TP/total cancer samples 278/833
Configuration: Somatic copy number classifier with matched white-blood-cell correction (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)	30% (26%–34%) Sensitivity at 98% specificity (validation set, post hoc 98% specificity threshold) percent · higher Uncertainty: 95% CI 26 to 34. Clopper-Pearson exact binomial interval (STAR Methods, statistical analysis) Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source SCNA-WBC 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 'SCNA-WBC', validation set, sensitivity and TP/total cancer samples 139/464

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Sources and history

Release 2026-10-10-457d7eaef7d6 · Record review: source checked

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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

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Technical metadata and extraction receipts

Stable ID: ctdnajam-20261010-config-scna-wbc

areas: dna-genomes
contexts: clinical_research
method types: supervised_machine_learning
reported name: SCNA-WBC
foundation model eligible: false
source locator: Table 2; STAR Methods, WGS: SCNA and SCNA-WBC classifiers
parameters: Whole-genome sequencing of cfDNA, about 30x; matched white-blood-cell WGS at about 30x
missing metadata: version: reason: unreported; note: Prototype classifier; no release or commit is printed

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