Charlotte Nachtegael, Barbara Gravel, Arnau Dillen, Guillaume Smits, Ann Nowé, Sofia Papadimitriou, Tom Lenaerts
Improving the understanding of the oligogenic nature of diseases requires access to high-quality, well-curated Findable, Accessible, Interoperable, Reusable (FAIR) data. Although first steps were taken with the development of the Digenic Diseases Database, leading to novel computational advancements to assist the field, these were also linked with a number of limitations, for instance, the ad hoc curation protocol and the inclusion of only digenic cases. The OLIgogenic diseases DAtabase (OLIDA) presents a novel, transparent and rigorous curation protocol, introducing a confidence scoring mechanism for the published oligogenic literature. The application of this protocol on the oligogenic literature generated a new repository containing 916 oligogenic variant combinations linked to 159 distinct diseases. Information extracted from the scientific literature is supplemented with current knowledge support obtained from public databases. Each entry is an oligogenic combination linked to a disease, labelled with a confidence score based on the level of genetic and functional evidence that supports its involvement in this disease. These scores allow users to assess the relevance and proof of pathogenicity of each oligogenic combination in the database, constituting markers for reporting improvements on disease-causing oligogenic variant combinations. OLIDA follows the FAIR principles, providing detailed documentation, easy data access through its application programming interface and website, use of unique identifiers and links to existing ontologies.DATABASE URL: https://olida.ibsquare.be.
Nachtegael, C, Gravel, B, Dillen, A, Smits, G, Nowé, A, Papadimitriou, S & Lenaerts, T 2022, 'Scaling up oligogenic diseases research with OLIDA: the Oligogenic Diseases Database', Database : the journal of biological databases and curation, vol. 2022, baac023. https://doi.org/10.1093/database/baac023
Nachtegael, C., Gravel, B., Dillen, A., Smits, G., Nowé, A., Papadimitriou, S., & Lenaerts, T. (2022). Scaling up oligogenic diseases research with OLIDA: the Oligogenic Diseases Database. Database : the journal of biological databases and curation, 2022, Article baac023. https://doi.org/10.1093/database/baac023
@article{f0344afc78f14f62923245171be9423a,
title = "Scaling up oligogenic diseases research with OLIDA: the Oligogenic Diseases Database",
abstract = "Improving the understanding of the oligogenic nature of diseases requires access to high-quality, well-curated Findable, Accessible, Interoperable, Reusable (FAIR) data. Although first steps were taken with the development of the Digenic Diseases Database, leading to novel computational advancements to assist the field, these were also linked with a number of limitations, for instance, the ad hoc curation protocol and the inclusion of only digenic cases. The OLIgogenic diseases DAtabase (OLIDA) presents a novel, transparent and rigorous curation protocol, introducing a confidence scoring mechanism for the published oligogenic literature. The application of this protocol on the oligogenic literature generated a new repository containing 916 oligogenic variant combinations linked to 159 distinct diseases. Information extracted from the scientific literature is supplemented with current knowledge support obtained from public databases. Each entry is an oligogenic combination linked to a disease, labelled with a confidence score based on the level of genetic and functional evidence that supports its involvement in this disease. These scores allow users to assess the relevance and proof of pathogenicity of each oligogenic combination in the database, constituting markers for reporting improvements on disease-causing oligogenic variant combinations. OLIDA follows the FAIR principles, providing detailed documentation, easy data access through its application programming interface and website, use of unique identifiers and links to existing ontologies.DATABASE URL: https://olida.ibsquare.be.",
keywords = "Databases, Factual, Software, Vocabulary, Controlled",
author = "Charlotte Nachtegael and Barbara Gravel and Arnau Dillen and Guillaume Smits and Ann Now{\'e} and Sofia Papadimitriou and Tom Lenaerts",
note = "{\textcopyright} The Author(s) 2022. Published by Oxford University Press.",
year = "2022",
month = apr,
day = "12",
doi = "10.1093/database/baac023",
language = "English",
volume = "2022",
journal = "Database : the journal of biological databases and curation",
issn = "1758-0463",
publisher = "Oxford University Press",
}