FAIR Genomes metadata schema promoting Next Generation Sequencing data reuse in Dutch healthcare and research

The genomes of thousands of individuals are profiled within Dutch healthcare and research each year. However, this valuable genomic data, associated clinical data and consent are captured in different ways and stored across many systems and organizations. This makes it difficult to discover rare disease patients, reuse data for personalized medicine and establish research cohorts based on specific parameters. FAIR Genomes aims to enable NGS data reuse by developing metadata standards for the data descriptions needed to FAIRify genomic data while also addressing ELSI issues. We developed a sema... Mehr ...

Verfasser: van der Velde, K Joeri
Singh, Gurnoor
Kaliyaperumal, Rajaram
Liao, XiaoFeng
de Ridder, Sander
Rebers, Susanne
Kerstens, Hindrik H D
de Andrade, Fernanda
van Reeuwijk, Jeroen
De Gruyter, Fini E
Hiltemann, Saskia
Ligtvoet, Maarten
Weiss, Marjan M
van Deutekom, Hanneke W M
Jansen, Anne M L
Stubbs, Andrew P
Vissers, Lisenka E L M
Laros, Jeroen F J
van Enckevort, Esther
Stemkens, Daphne
't Hoen, Peter A C
Beliën, Jeroen A M
van Gijn, Mariëlle E
Swertz, Morris A
Dokumenttyp: Artikel
Erscheinungsdatum: 2022
Schlagwörter: Delivery of Health Care / Genomics / High-Throughput Nucleotide Sequencing / Humans / Metadata / Software / Information Systems / Education / Library and Information Sciences / Statistics and Probability / Computer Science Applications / Statistics / Probability and Uncertainty / Journal Article
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-27457769
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : https://dspace.library.uu.nl/handle/1874/446203

The genomes of thousands of individuals are profiled within Dutch healthcare and research each year. However, this valuable genomic data, associated clinical data and consent are captured in different ways and stored across many systems and organizations. This makes it difficult to discover rare disease patients, reuse data for personalized medicine and establish research cohorts based on specific parameters. FAIR Genomes aims to enable NGS data reuse by developing metadata standards for the data descriptions needed to FAIRify genomic data while also addressing ELSI issues. We developed a semantic schema of essential data elements harmonized with international FAIR initiatives. The FAIR Genomes schema v1.1 contains 110 elements in 9 modules. It reuses common ontologies such as NCIT, DUO and EDAM, only introducing new terms when necessary. The schema is represented by a YAML file that can be transformed into templates for data entry software (EDC) and programmatic interfaces (JSON, RDF) to ease genomic data sharing in research and healthcare. The schema, documentation and MOLGENIS reference implementation are available at https://fairgenomes.org .