URL: www.gentrepid.org

The identification of genes responsible for human disease enables an understanding of disease mechanisms and is essential for the development of diagnostics and therapeutics. Genetic studies can successfully identify genomic regions linked to a particular disease phenotype. Taking the next step of isolating the disease-causing gene can be difficult. For linkage analysis, genomic regions are often large, particularly for complex diseases. Genome-wide association (GWA) studies have greater power to detect genetic variants that confer modest disease risks than linkage analysis does, but even these may identify hundreds of SNPs. Currently, published GWA studies list only the 20–50 most-significant SNPs and their neighboring genes (the “most-significant SNPs/genes” approach), while paying little attention to the rest. A system that predicts and prioritizes candidates using this genetic information would be a great boon. Here we present the Gentrepid web server, a system for predicting candidate disease genes associated with specific phenotypes using genetic and experimental biological data. The Gentrepid web server allows a user to enter a disease interval and the particular phenotype they are interested in. Standard OMIM phenotypes are available and nove