How to use DisGeNET web interface

The web interface for the data contained in DisGeNET has been created using Onexus, a modular framework to manage the complete life cycle of data analysis.

1. DisGeNET Web Interface User guide

In the DisGeNET Web Interface User Guide, you will find a tutorial addressing the following type of questions:

  • What genes are associated to Disease X?
  • What subtypes of Disease X are in the database?
  • How to retrieve the genes associated to several diseases at once?
  • Which genes support the association between Disease X and Disease Y?
  • What diseases are associated to protein class C?

How to use the plugin

1. DisGeNET Cytoscape Plugin User guide

In the user guide, you will find also a tutorial on the use of the plugin.

Download the User Guide

Tutorial Day ECCB 2016


Date: September, 4 (13:30-17:00 pm)

    13:30 – 14:00 - Overview of the database
    14:00 – 14:30 - The Web interface, supporting user-friendly data exploration and downloading
    14:30 – 15:00 - The DisGeNET Cytoscape app
    15:00 – 15:30 - Coffee Break
    15:30 – 16:00 - The SPARQL endpoint and Faceted Browser
    16:00 – 17:00 - The disgenet2r R package


Participants should bring their own laptop. They should have installed before the tutorial the following software:

- Cytoscape version 3.x (
- R version 3.3.x (

They should also download the DisGeNET SQLite database


  • The slides of the introduction to the database can be found here
  • The detailed tutorial for the session can be downloaded here
  • The CUI list for example 3.3 can be downloaded here


1. What kind of information can I find in DisGeNET?

DisGeNET contains a compilation of genes associated to diseases, that comes from different publicly available databases: the Comparative Toxicogenomics DatabaseTM (CTDTM), UniProt/SwissProt, ClinVar, Orphanet, the NHGRI-EBI GWAS Catalog, the Genetic Association Database (GAD), the Mouse Genome Database (MGD), and the Rat Genome Database (RGD). It also contains gene-disease associations retrieved using text mining approaches (LHGDN and BeFree data). For more information on LHGDN, see (Bauer-Mehren et al, 2011) and, (Bauer-Mehren et al, 2010) . For further details on BeFree system, see our web page and Bravo et al., 2014.

2. How is the score for a gene-disease pair computed?

For a seamless integration and ranking of gene-disease associations, we developed a gene-disease association score. DisGeNET gene-disease score takes into account the number and type of sources (level of curation, organisms), and the number of publications supporting the association. The score ranges from 0 to 1. For further details, click here .

3. What kind of questions can be answered with DisGeNET?

You can find information concerning a particular gene: what are the diseases associated, or what other genes are involved in these diseases. Similarly, you can find all genes associated to a disease of interest and a list of diseases that share genes with the specific disease under study. Additionally, for many of these associations, you can also obtain the association type between the gene and the disease, and the pubmed identifier of the paper reporting the association. A sentence describing the gene and the disease association is also provided, or the title of the paper reporting the association.

4. What is meant by "association type"?

The "association type" describes the different flavors of the gene-disease relationship, which are described in the GeneDiseaseAssociation.owl. For instance, the Genetic Variation association type is used when a sequence variation is associated to the disease phenotype. This ontology was developed to achieve a seamless integration of gene-disease association data coming from different databases.

5. What is the disease vocabulary used for diseases?

All entries in DisGeNET are mapped to the UMLS® CUIs. The source databases use MeSH, or MIM identifiers, or disease names for disease terms.

6. What species are covered in DisGeNET?

DisGeNET is focused on human genes and their association to diseases. We also include gene-disease associations described in animal models (mouse, rat) and map the genes to the human orthologs.

7. How can I download the information in DisGeNET?

DisGeNET data can be obtained in different ways: by downloading the SQLite database, by downloading the RDF data dump, through the Cytoscape plugin, or by downloading the tab separated files at the Downloads page. Alternatively, you can download the results of your analysis by using the downloads button on the top right in the web interface.

8. What is the Panther Class associated to the genes?

We have added the Panther Class as a new gene attribute, that allows to classify the genes in classes according to their molecular function. For more information, check the PANTHER Protein Class ontology. Currently, the mappings are performed to the second level category of Panther Ontology, that is, the terms directly related to "protein class". The list of the categories, and their representation in DisGeNET data is shown in the table below. It is possible to obtain all diseases associated to the genes in one of a panther class by using the search box on top of the tabs "Genes", "Summary of All Associations" and "All Data".

Panther Class Name Number of genes
nucleic acid binding 1871
receptor 1355
hydrolase 1287
transcription factor 1209
enzyme modulator 1137
transferase 1074
signaling molecule 988
transporter 880
cytoskeletal protein 660
oxidoreductase 551
defense/immunity protein 493
kinase 458
protease 440
cell adhesion molecule 424
calcium-binding protein 341
extracellular matrix protein 333
transfer/carrier protein 322
ligase 314
membrane traffic protein 282
phosphatase 271
chaperone 161
cell junction protein 154
lyase 138
isomerase 131
structural protein 120
transmembrane receptor regulatory/adaptor protein 58
surfactant 55
storage protein 20
viral protein 6