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Bionty.

Project description

Stars Coverage pypi

Bionty

Public biological ontologies for data scientists: look up, search, inspect, validate, and standardize terms.

To make it easy to customize and extend ontologies in a simple database backend, Bionty plugs into LaminDB: see this guide.

Entities

Check out sources.yaml for details.

Didn't see your favorite source or version? Bionty is extendable!

Installation

Bionty is a Python package available for pyversions

pip install bionty

Usage overview & quickstart

import bionty as bt

Look up terms with auto-complete

lookup = bt.ExperimentalFactor().lookup()
# access via Python-friendly keys
lookup.single_cell_rna_sequencing

# access via dictionary
lookup_dict = lookup.dict()
lookup_dict["single-cell RNA sequencing"]

Search ontology terms

celltype_bionty = bt.CellType()
# Free text search against a field
celltype_bionty.search("gamma delta T cell")

Validate, inspect & standardize terms

gene_bionty = bt.Gene()
# Validate against a field of reference
gene_bionty.validate(["A1BG", "FANCD1"], gene_bionty.symbol)
# Run full inspection on the gene symbols
gene_bionty.inspect(["A1BG", "FANCD1"], gene_bionty.symbol)
# Convert synonyms to standardized gene symbols
gene_bionty.standardize(["A1BG", "FANCD1"])

Access a reference DataFrame

# Reference table of the human genes
df = bt.Gene(species="human").df()

Track ontology sources

# Display currently used sources
bt.display_currently_used_sources()

# Display all managed sources
bt.display_available_sources()

# Local yaml file specifying all managed sources
bt.LOCAL_SOURCES

# Access to the Mondo ontology
disease = bt.Disease(source="mondo")

# Access to the Human Disease ontology
disease = bt.Disease(source="doid", version="2023-01-30")

Documentation

Read the docs.

Project details


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