DisGeNET

Dataset Description

DisGeNET is a discovery platform containing one of the largest publicly available collections of genes and variants associated to human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. TDC uses the curated subset from UNIPROT, CGI, ClinGen, Genomics England, CTD (human subset), PsyGeNET, and Orphanet. TDC maps disease ID to disease definition through MedGen and maps GeneID to uniprot amino acid sequence.

Task Description

Regression. Given the disease description and the amino acid sequence of the gene, predict their association.

Usage Example

from tdc_ml.multi_pred import GDA

data = GDA(name='DisGeNET')

# Access the data
df = data.get_data()
print(df.head())

# Get train/val/test splits
split = data.get_split()
print(split)

References

• [1] Piñero, Janet, et al. “The DisGeNET knowledge platform for disease genomics: 2019 update.” Nucleic acids research 48.D1 (2020): D845-D855.
• [2] Halavi, Maryam, et al. “MedGen.” The NCBI Handbook [Internet]. 2nd edition. National Center for Biotechnology Information (US), 2018.