> For the complete documentation index, see [llms.txt](https://help.connected.illumina.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.connected.illumina.com/emedgene/emedgene-analyze-manual/variant_page/evidence_section/acmg_cnv_classification_wizard.md). # ACMG CNV Classification wizard The **ACMG CNV Classification wizard** is located in the [**Evidence tab**](/emedgene/emedgene-analyze-manual/variant_page/evidence_section.md) of the [**Variant page**](/emedgene/emedgene-analyze-manual/variant_page/variant_page.md). It is available for tagged genomic variants. The tool automatically scores sections 1, 2, and 3, and partially scores sections 4 and 5 of the ACMG/ClinGen guidelines, including the full **PVS1** calculation required for intragenic variants. All relevant data is summarized in an accessible table. CNV classification follows the ACMG/ClinGen technical standards described in *Riggs et al., 2020* (PMID: 31690835). ![](/files/oRVHR4J9rnMc3cgZedLA) This tool is designed to save significant review time, reducing manual effort by up to 75–90% (ASHG 2020 abstract). ## Factors considered in CNV scoring When determining the automated classification, the system considers: * **Inheritance patterns** – whether the CNV is de novo or segregates in a family * **Gene content** – the number and type of genes affected, including ClinGen dosage sensitivity and predicted haploinsufficient genes * **Overlap with known pathogenic regions** – alignment with established genomic regions linked to disease By combining these elements, the scoring logic provides a clearer and more consistent starting point for CNV interpretation. {% hint style="info" %} **Tip:** Automated scoring provides a strong baseline, but it may not capture every detail of a case. Consider adjusting the classification manually if: * Family inheritance information is incomplete or uncertain * Breakpoint overlaps are ambiguous or affect multiple overlapping genes * New literature or curated evidence suggests a different pathogenicity than what is auto-assigned Manual review ensures that edge cases are interpreted accurately and remain clinically relevant. {% endhint %} {% hint style="warning" %} **Warning:** Automated CNV scoring relies heavily on reference databases such as ClinGen, DECIPHER, and gnomAD. If a gene or region is not yet well-curated in these databases, the classification may be incomplete or misleading. Always confirm key findings with manual review and supporting evidence before final reporting. {% endhint %} ## How to review and edit the ACMG Classification of a CNV The ACMG CNV classification wizard includes: 1. Automatically calculated **ACMG class and score** ![](/files/82hJ5KSNI2RPfARe9QPe) 2. **ACMG score slider** that shows the ranges of ACMG values for each classification and highlights where the current CNV falls: * Benign: ≤ –0.99 * Likely Benign: –0.98…–0.90 * VUS: –0.89…0.89 * Likely Pathogenic: 0.90…0.98 * Pathogenic: ≥ 0.99 ![](/files/2Xpec2HDdi5Zchbs5W5B) 3. **Reclassify** **button** that enables Edit mode ![](/files/5v9TIug4UR7qNQbaG8Md) 4. **Gene Number:** * **Gene Number** shows the total protein-coding RefSeq genes overlapped by the CNV. Of these: * Established ClinGen genes (dosage sensitivity or insensitivity defined by ClinGen scores) * Predicted haploinsufficient genes, based on gnomAD pLI ≥ 0.9 and DECIPHER HI index ≤ 10 ![](/files/GMojYIWSoQHeiOg1hO88) 5. **Genes affected by breakpoints** * This lists the protein-coding RefSeq genes that are directly impacted at the CNV breakpoints. For each gene, the wizard shows where the breakpoint occurs in relation to the gene’s canonical transcript. Note that in some cases a breakpoint may fall within more than one gene, since genes can overlap in the genome. ![](/files/zvhgGKQdfepN9n5qbcqD) 6. **Gene table** that provides a summary of the affected protein-coding genes: * Gene description: * Name - HGNC gene symbol, * Strand orientation; * Overlap info: * Gene - percentage of a gene involved in a CNV, * CNV - percentage of a CNV that overlaps with a gene; * ClinGen dosage sensitivity scores: * TS - ClinGen triplosensitivity score, * HI - ClinGen haploinsufficiency score; * HI predictors: * gnomAD pLI score (colored in red if pLI > 0.9), * DECIPHER HI index (colored in red if HI < 10); * Canonical transcript: * RefSeq ID, * 5’ UTR - affected or not, * CDS: * exons involved out of total, * NMD flag if the CNV is predicted to undergo nonsense mediated decay. * ClinVar flag if there are Clinvar Path SNV in the last exon * 3’ UTR - affected or not.
7. **Evidence sections:** 1. Color - coded criteria * Green = benign evidence * Grey = neutral evidence * Red = pathogenic evidence ![](/files/ChfB7WAmaftDi4EEa4W1) b. Clicking on a section box reveals the active criterion, its score, and notes box. Here you can: * Add notes * Change the criterion's score where applicable\* * Select a different criterion with the 'Edit tag' option * You may also reclassify the CNV by adjusting evidence section-by-section using the **Reclassify** option ![](/files/pxVFAvDiO5CSvAHVbxOf) ![](/files/t4GEfLXUsrx4X8BbdVhN) ![](/files/pxVFAvDiO5CSvAHVbxOf) ![](/files/t4GEfLXUsrx4X8BbdVhN) ![](/files/j3JIEb5qipg2lDI16YlV) **\*Criteria with variable score:** * 2F, 2I * 4A, 4B, 4C, 4D, 4E, 4I, 4J, 4K, 4L, 4M, 4N, 4O * 5A, 5B, 5C, 5E, 5G, 5H ## Learn more
ACMG SNV Classification wizardCompare the SNV ACMG workflow for reviewing tags, strengths, and final classification.:arrow-up-right-from-square: Learn more
Logic behind ACMG classification of SNVsReview the SNV score thresholds, combination rules, and classification logic.:arrow-up-right-from-square: Learn more
Individual ACMG criteria evaluationExplore detailed explanations for individual ACMG criteria used in SNV interpretation.:arrow-up-right-from-square: Learn more
Evidence tabReturn to the Evidence tab overview for related interpretation workflows and tools.:arrow-up-right-from-square: Learn more
### Disease source used in ACMG evaluation When a gene–disease association is available from multiple databases (for example: OMIM, CGD, Orphanet etc.), the Gene-related diseases card in the Variant Page display all available disease sources. Although multiple disease entries may appear, **ACMG inheritance-based logic relies exclusively on the OMIM disease entry** to determine the mode of inheritance. * ACMG rule evaluation uses only the **OMIM** source when assessing inheritance-dependent evidence. * If OMIM does not contain a pre-populated inheritance mode, **ACMG rules that depend on inheritance will not be triggered**, even if inheritance information exists in another disease source. #### Impact on ACMG evaluation - CNVs For **copy number variants (CNVs)**, inheritance information plays a **central role in the ACMG/ClinGen CNV scoring framework.** Unlike SNVs, CNV interpretation incorporates inheritance as **explicit scoring evidence** that can increase or decrease support for pathogenicity. Inheritance information derived from OMIM influences the following CNV evidence categories: * **De novo CNVs (5A)**\ CNVs identified as de novo provide positive evidence toward pathogenicity. Accurate inheritance determination is required to apply this evidence. * **Inherited CNVs from an unaffected parent (5B-5C)**\ CNVs inherited from an apparently unaffected parent contribute negative evidence, reducing support for pathogenicity in many disease contexts. * **Segregation with phenotype (5D)**\ CNVs that segregate with disease within a family add supportive evidence toward pathogenic classification. * **Lack of segregation (5E)**\ CNVs that do not segregate with affected family members weaken pathogenicity evidence. * **Uninformative or phenotype-based inheritance (5F-5H)**\ When inheritance data is missing or unclear, inheritance-based evidence may not be applied, and classification relies more heavily on genomic content and phenotype consistency. {% hint style="warning" %} **Warning:** If OMIM does not define an inheritance mode for the associated disease, **inheritance-based CNV scoring components may not be applied**, even if inheritance information is available from other disease sources. {% endhint %} --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://help.connected.illumina.com/emedgene/emedgene-analyze-manual/variant_page/evidence_section/acmg_cnv_classification_wizard.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.