Relevance of Three-category CNV classification, per-class agreement on deletions (Zhang et al. Table 4, DEL) to "Select a copy-number variant detection and characterisation workflow"

Stable ID: use-case-mapping-cnv-20261011-zhang2026-three-category-deletions

field

links:assessed_by:cnv-20261011-zhang2026-protocol-three-category-deletions

value

cnv-20261011-zhang2026-protocol-three-category-deletions

relevance

proxy

endpoint

Per-class agreement of AnnotSV, ClassifyCNV, dbCNV, MarCNV-ISV and X-CNV against expert ACMG classifications (906 deletions)

rationale

Proxy: automated pathogenicity classification of already detected CNVs bears on the characterisation and analyst-assessment part of the question, but no detection from sequencing reads is evaluated and the reference is expert ACMG labelling.

constraints

Inspect every linked evaluation's source locator before citing a result.; Do not combine this mapping's evaluations with detection results from other protocols; the endpoint is classification, not detection.

limitations

Reference labels are expert ACMG classifications, a semi-quantitative standard with known inter-reviewer variability (Discussion paragraph 5).; The set is enriched for pregnancy-loss and prenatal cases and is imbalanced (benign is about half of the duplications), which the authors say affects the metrics (Discussion paragraphs 5 and 6).; Classification of already detected CNVs from their coordinates; no read data or detection step is evaluated.; Some training sets of the evaluated tools (ClinVar, ClinGen, DGV) may overlap the published cohorts used as reference; the paper does not test this.; Two of the three authors (X. Zhang and D. Chen) are authors of dbCNV (reference 24), developed in the same laboratory, so the dbCNV rows are author_reported. dbCNV's original test set was that laboratory's internal dataset, and this benchmark includes the laboratory's internal CNV-seq cases (December 2019 to November 2025); overlap is not tested. The paper declares no competing interests.

citation locators

source id: cnv-20261011-zhang2026-source-article; locator: Table 4 rows 'DEL' B, VUS, P; Results 'Analysis of three-category performance'

source locator

cnv-20261011-zhang2026-source-article: Table 4 rows 'DEL' B, VUS, P; Results 'Analysis of three-category performance'

headline metric

recall

comparison group

zhang2026-cnv-classification

comparison title

Automated ACMG CNV classification tools against expert labels (Zhang et al. 2026)

stratum label

Three-category, deletions

stratum order

3

reason

Recorded from the 2026-10-11 use-case literature pass (data/omics/use-case-coverage-cnv-20261011-zhang2026). Independently reviewed in docs/reviews/use-cases/splicing-cnv-use-cases-2026-10-12.md.

review

method: source-hash-verification; independent-cell-check; automated-source-review; scope-review; reviewer: claude; reviewer note: Independent Claude review agent reviewer-scnv; did not extract this batch; no human review claimed; date: 2026-10-12; artifact sha256: a0810a8bff1ab3d2603a4832a56291cc182c8530aa8dffc6ac5318abd989ada0; retrieval url: https://www.ebi.ac.uk/europepmc/webservices/rest/PMC13018948/fullTextXML; method note: Drafted by the collector agent uc-splicing-cnv from the pinned source.; note: Checked by reviewer-scnv against the pinned source; verdict in docs/reviews/use-cases/splicing-cnv-use-cases-2026-10-12.md and in this batch's review.md.

reviewed evaluations

cnv-20261011-zhang2026-eval-three-category-deletions-annotsv; cnv-20261011-zhang2026-eval-three-category-deletions-classifycnv; cnv-20261011-zhang2026-eval-three-category-deletions-dbcnv; cnv-20261011-zhang2026-eval-three-category-deletions-marcnv-isv; cnv-20261011-zhang2026-eval-three-category-deletions-x-cnv

pins

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• subject: Select a copy-number variant detection and characterisation workflow