ArticleScientific reports2020
ClassifyCNV: a tool for clinical annotation of copy-number variants.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.
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Who cites it
58 citing papers in PubMed, 99 citations in OpenAlex.
- Integrative and systematic genomic approaches to improve diagnosis in rare and undiagnosed diseases: results from the RareBoost project.European journal of human genetics : EJHG · 2026Article
- Copy number variant analysis by exome sequencing is an effective approach to optimize diagnostic yield for developmental disorders-the DDD-Africa study.European journal of human genetics : EJHG · 2026Article
- Can automated copy number variation pathogenicity prediction tools replace manual review under the ACMG framework? A clinical validation.Global medical genetics · 2026Article
- CNV-Hub: an integrated web-based platform for CNV classification and interpretation using multi-algorithm consensus.NAR genomics and bioinformatics · 2026Article
- Pathogenic germline variations and cancer risks in pediatric patients referred for genetic testing.Nature medicine · 2026Article
- Horizon: CNV interpretation through rapid automated ACMG-aligned pathogenicity analysis.Human genetics · 2026Article
- Copy Number Variant analysis by exome sequencing is an effective approach to optimize diagnostic yield for developmental disorders - the DDD-Africa study.medRxiv : the preprint server for health sciences · 2026Article
- Alzheimer's disease: genetic background in the era of next-generation sequencing technologies.Brain communications · 2026Review
- Article
- Improving variant interpretation and diagnosis in Koolen-de Vries syndrome through a curated genotype-phenotype repository.Molecular genetics and genomics : MGG · 2025Article
- Germline pathogenic variation impacts somatic alterations and patient outcomes in pediatric central nervous system tumors.Nature communications · 2025Article
- Application and clinical utility assessment of natural language processing-based software for copy-number variants interpretation.Journal of translational medicine · 2025Article
- The promises and pitfalls of automated variant interpretation: a comprehensive review.Briefings in bioinformatics · 2025Review
- Germline pathogenic variation impacts somatic alterations and patient outcomes in pediatric CNS tumors.medRxiv : the preprint server for health sciences · 2025Article
- AI-powered precision medicine: utilizing genetic risk factor optimization to revolutionize healthcare.NAR genomics and bioinformatics · 2025Review
- Expanding the phenotypic and genetic landscape of congenital neutropenia through whole-exome and genome sequencing.HemaSphere · 2025Article
- Systematic assessment of structural variant annotation tools for genomic interpretation.Life science alliance · 2025Article
- Germline predisposition in multiple myeloma.iScience · 2025Article
- An evaluation of genetic predisposition to congenital anomalies and pediatric cancer supportsGenetics in medicine open · 2025Article
- Case report: Deciphering the clinical significance of a novel partialFrontiers in oncology · 2025Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Copy-number variants (CNVs) are an important part of human genetic variation. They can be benign or can play a role in human disease by creating dosage imbalances and disrupting genes and regulatory elements. Accurate identification and clinical annotation of CNVs is essential, however, manual evaluation of individual CNVs by clinicians is challenging on a large scale. Here, we present ClassifyCNV, an easy-to-use tool that implements the 2019 ACMG classification guidelines to assess CNV pathogenicity. ClassifyCNV uses genomic coordinates and CNV type as input and reports a clinical classification for each variant, a classification score breakdown, and a list of genes of potential importance for variant interpretation. We validate ClassifyCNV's performance using a set of known clinical CNVs and a set of manually evaluated variants. ClassifyCNV matches the pathogenicity category for 81% of manually evaluated variants with the significance of the remaining pathogenic and benign variants automatically determined as uncertain, requiring a further evaluation by a clinician. ClassifyCNV facilitates the implementation of the latest ACMG guidelines in high-throughput CNV analysis, is suitable for integration into NGS analysis pipelines, and can decrease time to diagnosis. The tool is available at https://github.com/Genotek/ClassifyCNV .
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.