Facilitating the interpretation of rare pathogenic variation in a clinical setting with DECIPHER. G. J. Swaminathan1, E. Bragin1, E. A. Chatzimichali1, S. Brent1, A. P. Bevan1, H. V. Firth1,2, M. E. Hurles1 1) Wellcome Trust Sanger Institute, Hinxton, Cambridge, Cambridgeshire, United Kingdom; 2) Cambridge University Department of Medical Genetics, Addenbrookes Hospital, Cambridge CB2 2QQ, United Kingdom.

   DECIPHER (Est. 2004) (https://decipher.sanger.ac.uk) is a web-based tool and database that aids the discovery and interpretation of pathogenic genetic variation (sequence and/or copy-number) in rare disorders obtained in a clinical setting or as part of an approved research study. Over 250 academic departments in genetic medicine contribute phenotype-linked variation data to the database for analysis and interpretation. Following informed consent, shared anonymised patient data enables the identification of clusters of patients with similar phenotype-linked genomic findings and encourages collaboration and contact between members. DECIPHER also facilitates contact between external users and consortium members making it an invaluable collaborative resource for genomic research and clinical diagnosis. Since 2010 alone, over 600 peer-reviewed research publications have benefited from such collaborations. The database contains more than 30000 patient records of which over 14000 have been consented for anonymous sharing with the wider community.
DECIPHER accepts the deposition of both sequence (point mutations, inDels) and copy-number variants with associated phenotypes and other relevant information (pathogenicity, inheritance, genotype etc.). Data are analysed in real-time and displayed in the context of affected gene/s scored by different prioritization criteria (OMIM, haploinsufficiency etc.) along with positional overlaps with known diseases/syndromes and patients with shared phenotypes. A purpose-built highly customizable genome browser (Genoverse: http://genoverse.org) provides visualization of the deposited variant/s against data in DECIPHER and other data sources including ClinVar, LSDB, ISCA etc. Different levels of data sharing are provided for, including sharing of selected data within a group (individuals, specific communities, projects) as well as fully anonymised public access. DECIPHER also provides programmatic access to public anonymous patient data as part of the Genomic Matchmaker Exchange project of the Global Alliance for Genomic Health (GA4GH) initiative.
We will present features of the DECIPHER database and illustrate the critical role it plays as a clinical and research utility for the interpretation of rare genetic disorders.

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