CNV-ClinViewer: enhancing the clinical interpretation of large copy-number variants online

Abstract

Motivation: Pathogenic copy-number variants (CNVs) can cause a heterogeneous spectrum of rare and severe disorders. However, most CNVs are benign and are part of natural variation in human genomes. CNV pathogenicity classification, genotype-phenotype analyses, and therapeutic target identification are challenging and time-consuming tasks that require the integration and analysis of information from multiple scattered sources by experts.

Results: Here, we introduce the CNV-ClinViewer, an open-source web application for clinical evaluation and visual exploration of CNVs. The application enables real-time interactive exploration of large CNV datasets in a user-friendly designed interface and facilitates semi-automated clinical CNV interpretation following the ACMG guidelines by integrating the ClassifCNV tool. In combination with clinical judgment, the application enables clinicians and researchers to formulate novel hypotheses and guide their decision-making process. Subsequently, the CNV-ClinViewer enhances for clinical investigators' patient care and for basic scientists' translational genomic research.

Availability and implementation: The web application is freely available at https://cnv-ClinViewer.broadinstitute.org and the open-source code can be found at https://github.com/LalResearchGroup/CNV-clinviewer.

Figure 1.

Development and use of CNV-ClinViewer. CNV data as well as clinical and genomic annotations are collected, processed and annotated, and quarterly updated. Users can copy-paste CNV(s) or upload CNVs in a tab-separated or Excel file for real-time exploration and interpretation.

Figure 2.

Semi-automated classification and download of CNV reports. (A) The integrated semi-automated classification of uploaded CNVs is based on 2019 ACMG/ClinGen Technical Standards for CNVs by ClassifyCNV³ and is one of the key features of the CNV-ClinViewer. The resulting scores and applied evidence categories can be inspected in a table overview and also downloaded. (B) A comprehensive report on individual CNVs, including details about the clinical significance classification and the overlap with established/predicted haploinsufficient/triplosensitive and clinically relevant genes and genomic regions, can be downloaded.

Figure 3.

Genomic viewer. A genomic viewer allows inspecting the uploaded CNVs and their genomic region alongside biomedical annotations and other pathogenic and general population CNV datasets. Here, the user can visually compare and dynamically filter uploaded CNVs, perform a seamless evaluation of the gene content, identify disease-prone regions and find unknown patterns of CNV localization to generate hypotheses for further research. An extended view of the genomic viewer can be found in Supplementary Fig. S1.

Figure 4.

Additional features. (A) Users can retrieve, filter, and download information about the intersecting genes, gene–disease associations, known dosage sensitive regions, and known CNV syndromes. (B) Users can perform gene-set enrichment analyses (GSEA) to infer information on genes within a selected genomic region or CNV by comparing it to >180 annotated gene sets representing prior biological knowledge such as pathways, Human Phenotype Ontology (HPO) terms, and known (rare) diseases.