Generic and queryable data integration schema for transcriptomics and epigenomics studies
The expansion of multi-omics datasets raises significant challenges for data integration and querying. To overcome these challenges, we developed a generic RDF-based integration schema that connects various types of differential -omics data, epigenomics, and regulatory information. This schema employs the FALDO ontology to enable querying based on genomic locations. It is designed to be fully or partially populated, providing both flexibility and extensibility while supporting complex queries. We validated the schema by reproducing two recently published studies, one in biomedicine and the other in environmental science, proving its genericity and its ability to integrate data efficiently. This schema serves as an effective tool for managing and querying a wide range of multi-omics datasets.
Authors
- E. Becker (ORCID: https://orcid.org/0000-0002-7673-0582)
- Matéo Boudet (ORCID: https://orcid.org/0000-0002-7028-7620)
- Fabrice Legeai (ORCID: https://orcid.org/0000-0002-6472-4839)
- Olivier Dameron (ORCID: https://orcid.org/0000-0001-8959-7189)
- Yael Tirlet
Institutions
- Centre National de la Recherche Scientifique (FR)
- Institut de Recherche en Informatique et Systèmes Aléatoires (FR)
- Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR)
- Institut de Génétique, Environnement et Protection des Plantes (FR)
- L'Institut Agro (FR)
- Université de Rennes (FR)
Publication Details
- Journal
- Computational and Structural Biotechnology Journal
- Published
- 2024-11-19
- DOI
- https://doi.org/10.1016/j.csbj.2024.11.022
- Primary Topic
- Gene expression and cancer classification
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Agence Nationale de la Recherche