CDG: An Online Server for Detecting Biologically Closest Disease-Causing Genes and its Application to Primary Immunodeficiency - Requena, David; Maffucci, Patrick; Bigio, Benedetta; Shang, Lei; Abhyankar, Avinash; Boisson, Bertrand; Stenson, Peter D.; Cooper, David N.; Cunningham-Rundles, Charlotte; Casanova, Jean-Laurent; Abel, Laurent; Itan, Yuval (Frontiers in Immunology, 2018)
High-throughput genomic technologies yield about 20,000 variants in the protein-coding exome of each individual. A commonly used approach to select candidate disease-causing variants is to test whether the associated gene has been previously reported to be disease-causing. In the absence of known disease-causing genes, it can be challenging to associate candidate genes with specific genetic diseases. To facilitate the discovery of novel gene-disease associations, we calculated the putative biologically-closest known genes and their associated diseases for 13,005 human genes not currently reported to be disease-associated. We used these data to construct the Closest Disease-Causing Genes (CDG) server, which can be used to infer the closest genes with an associated disease for a user-defined list of genes or diseases. We demonstrate the utility of the CDG server in 5 immunodeficiency patient exomes across different diseases and modes of inheritance, where CDG dramatically reduced the number of candidate genes to be evaluated. This resource will be a considerable asset for ascertaining the potential relevance of genetic variants found in patient exomes to specific diseases of interest. The CDG database and online server are freely available to non-commercial users at: http://lab.rockefeller.edu/casanova/CDG.