CDG: Closest Disease-causing Genes
An online resource for the identification and discovery of gene-disease associations.
CDG online servers:
CDG databases:
- CDG predicted gene-phenotype associations, based on HGMD (.xlsx format, 30.95MB)
- CDG known gene-phenotype associations, based on HGMD (.xlsx format, 463KB)
- CDG predicted gene-phenotype associations, based on OMIM (.xlsx format, 22.30MB)
- CDG known gene-phenotype associations, based on OMIM (.xlsx format, 112KB)
A major challenge in medical genomics is to select new potential disease-causing genes from patients' next generation sequencing data (NGS) when the genes obtained had not been previously associated to any phenotype.
To facilitate the discovery of novel gene-disease associations, the CDG database and server provide the putative biologically-closest known disease-causing genes (and their associated phenotypes) for 13,005 human genes not reported to be disease-causing. And, for any list of diseases, their predicted associated genes. CDG also reports the 5,430 known gene-disease associations if corresponding.
Citation:
When using the CDG server or database, please cite the following article:
David Requena, Patrick Maffucci, Benedetta Bigio, Lei Shang, Avinash Abhyankar, Bertrand Boisson, Peter D. Stenson, David N. Cooper, Charlotte Cunningham-Rundles, Jean-Laurent Casanova, Laurent Abel, and Yuval Itan. (2018) CDG: an online server for detecting biologically closest disease-causing genes and its application to primary immunodeficiency. Frontiers in Immunology 9:1340.
Link: https://www.frontiersin.org/articles/10.3389/fimmu.2018.01340/full
Related resources:
- The Human Gene Connectome (HGC) server
Link: http://lab.rockefeller.edu/casanova/HGC
References: PNAS 110(14):5558-63, BMC Genomics 15:256 - The Human Gene Damage Index (GDI) server
Link: http://lab.rockefeller.edu/casanova/GDI
Reference: PNAS 112(44):13615-20 - The Mutation Significance Cut-off (MSC) server
Link: http://lab.rockefeller.edu/casanova/MSC
Reference: Nat Methods 13:109-10
Contact:
In case of problems or questions, please e-mail Yuval Itan (yuval.itan@mssm.edu) or David Requena (drequena@rockefeller.edu).
