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GHGA – German Human Genome-Phenome Archive

Subject Area Medicine
Biology
Term since 2020
Website Homepage
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 441914366
 
Human genome sequencing and other omics data modalities are of critical importance for biomedical research and the future development of healthcare. There is a desire and a moral imperative to handle such data in an open and FAIR manner. However, it is equally important that the data are kept safe and secure, and access is restricted to legitimate research use. Existing European infrastructures, particularly the European Genome-Phenome Archive (EGA), cannot adequately address the legal requirements specific to Germany. Moreover, EGA is exclusively designed as an archive and does not address the needs of research communities to analyze protected human large-scale data in a user-friendly manner, foster scientific discoveries, or enable replication across distinct cohorts. The absence of a safe, legally compliant, and ethically appropriate infrastructure for omics data in Germany is a major hurdle to translating the potential of existing and forthcoming medical omics data in Germany and in a European context. The German Human Genome-Phenome Archive (GHGA) will address these issues by providing a national infrastructure for secure and safe storage, access management, dissemination, and analysis of human omics data (e.g., genomics, transcriptomics, proteomics) under a coherent ethico-legal framework. GHGA will build on existing German omics data providers and their IT infrastructures to establish a harmonized distributed infrastructure for omics data. Via direct connection to major omics data providers, we will streamline data deposition via automatic transfer of all available metadata. Internationally, GHGA will be embedded into European infrastructures as a federated German EGA node. This will allow German researchers to help shape future international standards for data exchange and take on leading roles in international research consortia (e.g., the 1+ Million European Genomes Initiative [MEGA]). By going significantly beyond a mere archival functionality, GHGA will enable and democratize access to even the largest population-scale datasets. Secure, private, cloud-based access to the data will reduce the need for data download and enable compute-intensive applications (including artificial intelligence applications on omics data). Community-specific tailored access portals combined with the curation of reference data collections will ensure the utility of GHGA's datasets to researcher and clinician communities – who in turn will help shape the further development of GHGA. The initial focus of GHGA on cancer and rare diseases is aligned with that of forthcoming national initiatives, most notably, Germany’s upcoming medical genome sequencing programme (genomDE). Training and outreach activities will help raise a new generation of scientists familiar with GHGA and omics data analysis. GHGA will closely interact with other planned NFDI initiatives through data linkage and joint standardization and harmonization efforts.
DFG Programme NFDI technical and methodological consortia
International Connection United Kingdom
Co-Spokespersons Professor Dr. Peer Bork; Dr. Ivo Buchhalter; Dr. Andreas Dahl; Professor Dr. Julien Gagneur; Dr. Wolfgang Huber; Dr. Daniel Hübschmann, Ph.D.; Professor Dr. Oliver Kohlbacher; Dr. Jan Korbel; Professor Dr. Martin Lablans; Professor Dr.-Ing. Ulrich Lang, from 10/2020 until 10/2022; Professor Dr. Peter Lichter; Professorin Dr. Fruzsina Molnar-Gabor; Susanne Motameny; Professor Dr. Sven Nahnsen; Professor Dr.-Ing. Uwe Ohler; Professor Dr. Stephan Ossowski, Ph.D.; Professorin Dr. Annette Peters; Professor Dr. Olaf Riess; Professor Dr. Philip Caspar Rosenstiel, Ph.D.; Professor Dr. Thorsten Schlomm; Professor Dr. Joachim L. Schultze; Professor Dr. Jörn E. Walter; Professor Dr. Thomas Walter; Professor Dr.-Ing. Stefan Wesner, since 10/2022; Professorin Dr. Juliane Winkelmann; Professorin Dr. Eva Winkler, Ph.D.
 
 

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