Arboreto

Overview

Arboreto is a Python library from Aerts Lab for inferring gene regulatory networks (GRNs) from gene expression data. It parallelizes tree-based ensemble regression (GRNBoost2, GENIE3) with Dask across local cores or remote clusters.

Core capability: Identify which transcription factors (TFs) regulate which target genes based on expression patterns across observations (cells, samples, conditions).

Upstream: PyPI 0.1.6 (2021-02-09, latest). Docs: arboreto.readthedocs.io. Primary downstream consumer: pySCENIC.

Quick Start

Install arboreto:

uv pip install arboreto

Basic GRN inference:

import pandas as pd
from arboreto.algo import grnboost2

if __name__ == '__main__':
    # Load expression data (genes as columns)
    expression_matrix = pd.read_csv('expression_data.tsv', sep='\t')

    # Infer regulatory network
    network = grnboost2(expression_data=expression_matrix)

    # Save results (TF, target, importance)
    network.to_csv('network.tsv', sep='\t', index=F…