Bionty: Curate metadata using ontologies#
Access public & custom ontologies with auto-complete. Map synonyms with ease.
If you’d like to maintain in-house along with public ontologies, you can manage them with Bionty’s SQL interface: lnschema-bionty.
Species: NCBI Taxonomy, Ensembl Species
CellLine: Cell Line Ontology
CellType: Cell Ontology
Disease: Mondo, Human Disease
Phenotype: Human Phenotype
Pathway: Gene Ontology, Pathway Ontology
Readout: Experimental Factor Ontology
BFXPipeline: largely based on nf-core
Check out versions.yaml for details.
Bionty is a Python package available for
pip install bionty
Look up ontology records with auto-complete#
import bionty as bt gene = bt.Gene() gene.lookup().LNMA
See Look up records of species, gene, protein, cell marker for more.
import pandas as pd # Create an example Pandas DataFrame of various cell types. df = pd.DataFrame( index=[ "placental epithelial cell", "capillary", "This cell type does not exist", ] ) # The DataFrame can either be curated by ontology ID (id="ontology_id") # or by ontology term names (id="name"). curated_df = bt.CellType(id="name").curate(df) # ✅ 2 terms (66.7%) are mapped. # 🔶 1 terms (33.3%) are not mapped.
See Curate entity identifiers for more.
Track ontology sources#
# Display all managed versions bt.display_available_versions() # Access to the Mondo ontology disease = bt.Disease(database="mondo") # Access to the Human Disease ontology disease = bt.Disease(database="doid", version="2023-01-30")
Didn’t see your favorite source or version? See how to Extend Bionty.