CNV-ClinViewer: Enhancing the clinical interpretation of large copy-number variants online
Macnee, M.; Perez-Palma, E.; Brünger, T.; Klöckner, C.; Platzer, K.; Stefanski, A.; Montanucci, L.; Bayat, A.; Radtke, M.; Collins, R. L.; Talkowski, M.; Blankenberg, D.; Moller, R. S.; Lemke, J. R.; Nothnagel, M.; May, P.; Lal, D.
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PurposeLarge 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. MethodsWe developed a web-application combining >250,000 patient and population CNVs together with a large set of biomedical annotations and provide tools for CNV classification based on ACMG/ClinGen guidelines and gene-set enrichment analyses. ResultsHere, we introduce the CNV-ClinViewer (https://cnv-ClinViewer.broadinstitute.org), 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. ConclusionOverall, this resource facilitates semi-automated clinical CNV interpretation and genomic loci exploration and, in combination with clinical judgment, 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.
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