ArticleFrontiers in immunology2018
CDG: An Online Server for Detecting Biologically Closest Disease-Causing Genes and its Application to Primary Immunodeficiency.
Article in Frontiers in immunology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Deciphering the clinical and genetic spectrum of early-onset inborn errors of immunity in a Brazilian pediatric cohort.Frontiers in immunology · 2026Article
- Expanding the utility of variant effect predictions with phenotype-specific models.Nature communications · 2025Article
- Article
- A Machine Learning Approach to Identifying Causal Monogenic Variants in Inflammatory Bowel Disease.Gastro hep advances · 2022Article
- Identifying disease-causing mutations in genomes of single patients by computational approaches.Human genetics · 2020Review
- De novo variants in exomes of congenital heart disease patients identify risk genes and pathways.Genome medicine · 2020Article
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Authors and funding
12 authors.
Funding
Abstract
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 determined 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 five 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.
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Registered trials
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