Cluster your data matrix with the Leiden algorithm.
Project description
# leiden_clustering [![pipy](https://img.shields.io/pypi/v/leiden_clustering?color=informational)](https://pypi.python.org/pypi/leiden_clustering) [![License](https://img.shields.io/badge/License-BSD%203–Clause-blue.svg)](https://opensource.org/licenses/BSD-3-Clause)
## Description Class wrapper based on [scanpy](https://scanpy.readthedocs.io/en/stable/) to use the Leiden algorithm to directly cluster your data matrix with a scikit-learn flavor.
## Requirements Developed using: - scanpy v1.7.2 - sklearn v0.23.2 - umap v0.4.6 - numpy v1.19.2 - leidenalg
## Installation ### pip `shell pip install leiden_clustering ` ### local `shell git clone https://github.com/MiqG/leiden_clustering.git cd leiden_clustering pip install -e . `
## Usage `python from leiden_clustering import LeidenClustering import numpy as np X = np.random.randn(100,10) clustering = LeidenClustering() clustering.fit(X) clustering.labels_ `
## License leiden_clsutering is distributed under a BSD 3-Clause License (see [LICENSE](https://github.com/CRG-CNAG/leiden_clustering/blob/main/LICENSE)).
## References - Traag, V.A., Waltman, L. & van Eck, N.J. From Louvain to Leiden: guaranteeing well-connected communities. Sci Rep 9, 5233 (2019). DOI: https://doi.org/10.1038/s41598-019-41695-z
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.