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

Author:

Macnee Marie1ORCID,Pérez-Palma Eduardo2ORCID,Brünger Tobias1,Klöckner Chiara3,Platzer Konrad3ORCID,Stefanski Arthur45,Montanucci Ludovica4,Bayat Allan67,Radtke Maximilian3,Collins Ryan L89ORCID,Talkowski Michael89,Blankenberg Daniel4ORCID,Møller Rikke S67,Lemke Johannes R3ORCID,Nothnagel Michael110,May Patrick11ORCID,Lal Dennis1458ORCID

Affiliation:

1. Cologne Center for Genomics (CCG), University of Cologne , Cologne, Germany

2. Universidad del Desarrollo, Centro de Genética y Genómica, Facultad de Medicina Clínica Alemana , Santiago, Chile

3. Institute of Human Genetics, University of Leipzig Medical Center , Leipzig, Germany

4. Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic , Cleveland, OH, USA

5. Epilepsy Center, Neurological Institute, Cleveland Clinic , Cleveland, OH, USA

6. Department of Epilepsy Genetics and Personalized Medicine, Member of ERN Epicare, Danish Epilepsy Centre , Dianalund, Denmark

7. Department of Regional Health Research, Faculty of Health Sciences, University of Southern Denmark , Odense, Denmark

8. Broad Institute of Massachusetts Institute of Technology and Harvard , Cambridge, MA, USA

9. Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School , Boston, MA, USA

10. University Hospital Cologne , Cologne, Germany

11. Luxembourg Centre for Systems Biomedicine, University Luxembourg , Esch-sur-Alzette, Luxembourg

Abstract

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.

Funder

German Federal Ministry for Education and Research

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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