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
v2, August 2022
Update of OLIDA content with articles published up to January 2022.
v1, April 2022
Original OLIDA publication.
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/.
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
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Supported By:






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),
The Service Public de Wallonie Recherche by DIGITALWALLONIA4.AI through the ARIAC project (2010235),
Innoviris Joint R&D project Genome4Brussels project (2020 RDIR 55b),
The Research Foundation – Flanders (F.W.O) infrastructure project associated with ELIXIR Belgium (I0022819N).
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