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The COVID-19 host genetics initiative brings together the human genetics community to generate, share, and analyze data to learn the genetic determinants of COVID-19 susceptibility, severity, and outcomes. Such discoveries could help to generate hypotheses for drug repurposing, identify individuals at unusually high or low risk, and contribute to global knowledge of the biology of SARS-CoV-2 infection and disease.

This site is a university repository providing access to the publication output of the institution. Some items may not be available as full-text.

This site provides access to the research output of the institution. Users may set up Atom or RSS feeds to be alerted to new content. The interface is available in English.

The Database of Genomic Variants archive (DGVa) is a repository that provides archiving, accessioning and distribution of publicly available genomic structural variants, in all species.

DisGeNET is a discovery platform containing one of the largest collections available of genes and variants involved in human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models, and the scientific literature, and covers the whole landscape of human diseases. The current version of DisGeNET (v7.0) contains 1,134,942 gene-disease associations (GDAs), between 21,671 genes and 30,170 diseases, disorders, traits, and clinical or abnormal human phenotypes, and 369,554 variant-disease associations (VDAs), between 194,515 variants and 14,155 diseases, traits, and phenotypes. The 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, a REST API, and an R package.

PPMI is an observational clinical study to verify progression markers in Parkinson’s disease. The study is designed to establish a comprehensive set of clinical, imaging and biosample data that will be used to define biomarkers of PD progression. Once these biomarkers are defined, they can be used in therapeutic studies. The clinical, imaging and biologic data are accessible to researchers in real time through the website. If used as a public resource without login, this resource functions as a dashboard.

The National Institute on Alcohol Abuse and Alcoholism Data Archive (NIAAA-DA) is a data repository that houses and shares hundreds of alcohol-related, human subjects study data generated by NIAAA-funded research. NIAAA-DA is housed within the NIMH Data Archive (NDA) which provides infrastructure for sharing research data, tools, methods, and analyses enabling collaborative science and discovery. De-identified human subjects data, harmonized to a common standard, are available to qualified researchers. Summary data is available to all.