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Shaurita D. Hutchins

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Full license MIT

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Requires: Python >=3.9
Provides-Extra: dev
Package Info

Harmonizome Python Wrapper

A Python wrapper around the Ma’ayan Lab Harmonizome API and download endpoints. The package provides a Python interface for querying Harmonizome entities, downloading Harmonizome datasets, and loading the downloaded artifacts into pandas DataFrames.

Installation

pip install harmonizome

Quick Start

from harmonizome import Harmonizome

# Inspect one gene from the API
gene_info = Harmonizome.get('gene', 'BRCA1')
print(f"Gene: {gene_info['name']}")

# Download one dataset artifact
for filename in Harmonizome.download(['ENCODE']):
    print(f"Downloaded: {filename}")

Features

  • API Wrapper: Query genes, gene sets, attributes, and datasets from the Ma’ayan Lab Harmonizome API
  • Dataset Downloads: Download complete Harmonizome datasets (~30GB total) from the Ma’ayan Lab service
  • DataFrame Support: Load data directly as pandas DataFrames
  • Sparse Matrix Support: Efficient handling of large sparse datasets
  • Python 3.9+ Support: Targets the package minimum version and newer

Quick API Reference

Core Methods

Harmonizome.get(entity, name=None, start_at=None)

Retrieve entities from the Ma’ayan Lab Harmonizome API.

  • entity: Type of entity (‘gene’, ‘gene_set’, ‘attribute’, etc.)
  • name: Specific entity name (optional)
  • start_at: Cursor position for pagination (optional)

Harmonizome.download(datasets=None, what=None)

Download Harmonizome dataset files from the Ma’ayan Lab service to local directories.

  • datasets: List of dataset names (defaults to all datasets)
  • what: List of file types to download (defaults to all types)

Harmonizome.download_df(datasets=None, what=None, sparse=False)

Download Harmonizome dataset files and load them as pandas DataFrames.

  • datasets: List of dataset names
  • what: List of file types to download
  • sparse: Use sparse matrices for memory efficiency

Entity Types

Examples

Querying Genes

brca1 = Harmonizome.get('gene', 'BRCA1')
print(f"BRCA1 description: {brca1['description']}")

Downloading Datasets

# Download one dataset
for filename in Harmonizome.download(['ENCODE']):
    print(f"Downloaded: {filename}")

Working with DataFrames

# Load one dataset into a pandas DataFrame
for df in Harmonizome.download_df(['ENCODE']):
    print(f"DataFrame: {df.shape}")
    break

Working with Gene Associations as DataFrames

You can fetch all associations for a gene and convert them to a pandas DataFrame:

from harmonizome import Harmonizome

gene = "STAT3"
gene_data = Harmonizome.get_gene_data(gene, use_cache=True)

# Get all associations as a DataFrame
df = gene_data.to_dataframe()

# Filter to one dataset
dataset_df = df[df["dataset"] == "ENCODE Transcription Factor Binding Site Profiles"]
print(dataset_df.head())

API Reference: GeneData.to_dataframe()

gene_data.to_dataframe(dataset: str = None) -> pandas.DataFrame
  • Returns a DataFrame with columns: ‘gene_set’, ‘dataset’, ‘thresholdValue’, ‘standardizedValue’.
  • Optionally filter by dataset name.

File Types

The following file types are available for download:

  • gene_attribute_matrix.txt.gz: Gene-attribute association matrix
  • gene_list_terms.txt.gz: List of genes with terms
  • attribute_list_entries.txt.gz: List of attributes with entries

Requirements

  • Python 3.9+
  • numpy >= 1.19.0
  • pandas >= 1.3.0
  • scipy >= 1.7.0

Development

# Install development dependencies
pip install -e .

# Run tests
pytest

License

This project is licensed under the MIT License.

Data Source and Citation

This wrapper depends on the public Harmonizome resource maintained by the Ma’ayan Lab. If you use this package in your research, cite the Harmonizome resource itself:

Rouillard AD, Gundersen GW, Fernandez NF, Wang Z, Monteiro CD, McDermott MG, Ma'ayan A. The harmonizome: a collection of processed datasets gathered to serve and mine knowledge about genes and proteins. Database (Oxford). 2016 Jul 3;2016:baw100. doi: 10.1093/database/baw100.