Benign-Ex: Delineating Regions of the Human Genome Benign to Copy Number Variation

While copy number variants (CNVs) have been identified as an important cause of rare genetic disorders, they have also been identified in unaffected control populations, making clinical interpretation of these lesions challenging. Discriminating benign CNVs from those pathogenic for rare genetic disorders, therefore, relies on understanding what regions of the human genome are tolerant to copy number variation. Benign-Ex is a python-based program that uses information from databases of CNVs to generate one or more benign interval map(s) and then identifies the optimal map by computing the overlap with known pathogenic regions. We utilized Benign-Ex to identify the optimal set of benign intervals from two distinct CNV databases: Database of Genomic Variants (DGV) and Clinical Genome Resource (ClinGen). Benign-Ex called 41.1% of the genome benign using data from DGV and 37.6% of the genome benign using data from ClinGen. The benign regions from DGV and ClinGen were not spatially correlated, underscoring the importance of integrating both research and clinical databases for determining CNV benignity. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was supported by R01DE021071 (MP and JM), the Stead Family Department of Pediatrics (AW, HM, BD) and the Interdisciplinary Genetics T32 Predoctoral Training Grant (T32 GM 008629; AW). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This study used ONLY openly available human data that were obtained from the Database of Genomic Variants () and the Clinical Genome Resource via the UCSC Genome Table Browser () I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes Benign-Ex is publicly available on GitHub at . Full simulation data is available upon request. All other data produced and analyzed in the present study are included in this published article and its supplementary information.