DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants

TLDR

The genetic basis of human diseases is central to precision medicine and drug discovery, yet fragmentation, heterogeneity, limited availability, and inconsistent conceptualization of data impede its full potential. To remove these barriers, we developed DisGeNET, one of the largest freely available collections of genes and variants implicated in human diseases. DisGeNET aggregates data from expert‑curated repositories, GWAS catalogues, animal models, and literature, annotates it uniformly with controlled vocabularies and community ontologies, supplies original prioritization metrics, and is accessible via a web interface, Cytoscape app, RDF SPARQL endpoint, scripts, and an R package. The platform supports diverse research aims, including exploring disease molecular mechanisms and comorbidities, analyzing disease‑gene properties, generating drug‑action and adverse‑effect hypotheses, validating computationally predicted disease genes, and benchmarking text‑mining methods.

Abstract

The information about the genetic basis of human diseases lies at the heart of precision medicine and drug discovery. However, to realize its full potential to support these goals, several problems, such as fragmentation, heterogeneity, availability and different conceptualization of the data must be overcome. To provide the community with a resource free of these hurdles, we have developed DisGeNET (http://www.disgenet.org), one of the largest available collections of genes and variants involved in human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype-phenotype relationships. The information is accessible through a web interface, a Cytoscape App, an RDF SPARQL endpoint, scripts in several programming languages and an R package. DisGeNET is a versatile platform that can be used for different research purposes including the investigation of the molecular underpinnings of specific human diseases and their comorbidities, the analysis of the properties of disease genes, the generation of hypothesis on drug therapeutic action and drug adverse effects, the validation of computationally predicted disease genes and the evaluation of text-mining methods performance.