General Information

OLIDA was developed by the Interuniversity Institute of Bioinformatics in Brussels (IB)²

OLIDA completely overhauled DIDA, a novel database that provided for the first time detailed information on genes and associated genetic variants involved in digenic diseases, the simplest form of oligogenic inheritance, with the aim of increasing the data quality, content and accessibility. OLIDA was designed to allow storage of information on any type of oligogenic diseases in addition to the digenic diseases present in DIDA.

While DIDA will be kept online for historical purposes, it will be deprecated in the future. OLIDA should be used instead as it contains more data and comes with more advanced features.

OLIDA is still under active development at (IB)2 with new features planned for the future. Occasional down time is possible when the site gets updated.


Updates

v3.3, December 2023

Update of variants ID 136, 137, 639, 947, 1661 and 2144, as they contained typos.

Many thanks to Dr Anaïs Mottaz, Post-doctoral researcher at Hôpitaux Universitaires de Genève, for finding the errors.

Update of the combination OLI1415 due to a missing variant, the missing variant was added under the ID 3399; gene combination with ID 992 was modified in consequence with their manual score and metascore downgraded to 0.


v3.2, October 2023

Update of combinations OLI1032, OLI1033, OLI1034, OLI1035, OLI1036, OLI1037 and OLI1038, to add the Meniere disease to the list of diseases linked to the variant combinations.

Special thanks to Dr Douglas Stewart, Consultant Paediatric Nephrologist at the Royal Hospital for Children, Glasgow, for finding the error.


v3.1, July 2023

Changes in diseases-related statistics plots to include gene combinations and add genes for CNVs when available.


v3, May 2023

Update of OLIDA content with articles published up to February 2023.

Three existing gene combinations (189, 606 and 635) had their scores upgraded and involved variant combinations were reviewed for potential change of score.

Several variant combinations had part of their scores changed :

  • OLI285: Gene Manual harmonized and Gene Metascore upgraded from 0 to 2, in consequence Functional Metascore were upgraded from 0 to 2, increasing the Final Metascore from 0 to 1
  • OLI286: Gene Manual harmonized and Gene Metascore upgraded from 0 to 2, in consequence Functional Metascore were upgraded from 0 to 2, increasing the Final Metascore from 0 to 1
  • OLI834 : Gene Manual score upgraded from 0 to 2
  • OLI836 : Gene Manual, Gene Manual harmonized, Gene Metascore upgraded from 0 to 2, in consequence Functional Manual and Metascore were upgraded from 0 to 2, increasing the Final Manual and Metascore from 0 to 1
  • OLI847: Gene Manual harmonized and Gene Metascore upgraded from 0 to 2, in consequence Functional Metascore was upgraded from 0 to 2, increasing the Final Metascore from 0 to 1
  • OLI868: Gene Manual harmonized and Gene Metascore upgraded from 0 to 1, in consequence Functional Metascore was upgraded from 0 to 1, no change in Final Metascore
  • OL1108: Gene Manual harmonized and Gene Metascore upgraded from 0 to 1, in consequence Functional Metascore was upgraded from 0 to 1, no change in Final Metascore

382 new variant combinations were added to the database.

The variant combination OLI1126 was deleted and merged with a previously existing combination, OLI084, after correction of the variants coordinates.

The API was also updated to include all the metadata found in OPTIONS until now.


v2, August 2022

Update of OLIDA content with articles published up to January 2022.


v1, April 2022

Original OLIDA publication.


Contact

If you have any questions about OLIDA that are not answered in the documentation, feel free to contact us at olida@ibsquare.be. We will try to get back at you as soon as possible.


OLIDA – publications and citations

OLIDA

When using data from OLIDA please cite:

  • Nachtegael C. and Gravel B., Dillen A., Smits G., Nowé A., Papadimitriou S., Lenaerts T. Scaling up oligogenic diseases research with OLIDA: the Oligogenic Diseases Database. Database, April 2022. DOI: https://doi.org/10.1093/database/baac023
    Citation files: BibTex, RIS

Predictors trained using our data

The data from digenic diseases of DIDA was used in our research group and around the world to train machine learning predictors aiming to predict and understand the cause of digenic diseases. They can be found on the about page of the website of DIDA at http://dida.ibsquare.be/about/.

VarCoPP 2.0

VarCoPP 2.0 is the update of the VarCoPP predictor, trained with the data from OLIDA with a decent confidence score, aiming to predicting potential pathogenic digenic variant combinations. The model is integrated on the ORVAL platform.

Citing VarCoPP 2.0:

  • Versbraegen, N., Gravel, B., Nachtegael, C., Renaux A., Verkinderen E., Nowé A., Lenaerts T.,Papadimitriou S. Faster and more accurate pathogenic combination predictions with VarCoPP2.0. BMC Bioinformatics, May 2023. DOI: https://doi.org/10.1186/s12859-023-05291-3
    Citation files: BibTex, RIS

ORVAL

ORVAL is a sister platform to OLIDA that incorporates the VarCoPP predictor, the digenic effect predictor and other analytical tools, to explore oligogenic variant combinations and predicted pathogenic gene networks in an individual. It is available at orval.ibsquare.be.

Citing ORVAL:

  • Renaux A., Papadimitriou S., Versbraegen N., Nachtegael C., Boutry S., Nowé A., Smits G., Lenaerts T. ORVAL: A novel platform for the prediction and exploration of disease-causing oligogenic variant combinations. Nucleic Acids Research, May 2019. DOI: https://doi.org/10.1093/nar/gkz437
    Citation files: BibTex, RIS

BOCK and ARBOCK

BOCK is a knowledge graph constructed to explore disease-causing genetic interactions, integrating curated information on oligogenic diseases from clinical cases with relevant biomedical networks and ontologies. Using this graph, they developed a novel predictive framework based on heterogenous paths connecting gene pairs. This method trains an interpretable decision set model that not only accurately predicts pathogenic gene interactions, but also unveils the patterns associated with these diseases. BOCK is available at https://zenodo.org/records/8124854.

Citing BOCK:

  • Renaux A., Terwagne C., Cochez M., Tiddi I., Nowé A., Lenaerts T. A knowledge graph approach to predict and interpret disease-causing gene interactions. BMC Bioinformatics, August 2023. DOI: https://doi.org/10.1186/s12859-023-05451-5
    Citation files: BibTex, RIS


Special Thanks to:

Members of the OLIDA community, who helped in maintaining its high-quality content:

  • Dr Douglas Stewart, Consultant Paediatric Nephrologist at the Royal Hospital for Children, Glasgow
  • Dr Anaïs Mottaz, Post-doctoral researcher at Hôpitaux Universitaires de Genève


Data Privacy

We hereby declare that:

  1. We use Google Analytics to track general visitor traffic information. We do not take any responsibility for the data stored by this third party application.
  2. The personally identifiable data of the users collected through this website, with your consent, is only accessible for selected researchers of Vrije Universiteit Brussel (VUB) and Université Libre de Bruxelles (ULB), both Universities acting as Data Controllers, who manage the OLIDA web service. The data will not be shared with any person. Data will be kept during all time of registration with the website. Users can request a full purge of their personal data at any time by removing their account and selecting the purge option.
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This work was supported by

The European Regional Development Fund (ERDF) and the Brussels-Capital Region-Innoviris within the framework of the Operational Programme 2014–2020 through the ERDF-2020 project ICITY-RDI.BRU (27.002.53.01.4524),

Fonds de la Recherche Scientifique (F.R.S-F.N.R.S) through a FRIA grant (40008622), a postdoctoral fellowship (40005602) and a research project (35276964),

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