decoupler - Ensemble of methods to infer enrichment scores

decoupler is a python package containing different enrichment statistical methods to extract biologically driven scores from omics data within a unified framework. This is its faster and memory efficient Python implementation, a deprecated version in R can be found here.

decoupler is part of the scverse® project (website, governance) and is fiscally sponsored by NumFOCUS. If you like scverse® and want to support our mission, please consider making a tax-deductible donation to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.

Getting started

Please refer to the documentation, in particular, the API documentation.

Installation

You need to have Python 3.10 or newer installed on your system. If you don’t have Python installed, we recommend installing uv.

There are several alternative options to install decoupler:

1. Install the latest stable release from PyPI with minimal dependancies:

pip install decoupler

2. Install the latest stable full release from PyPI with extra dependancies:

pip install decoupler[full]

3. Install the latest stable version from conda-forge using mamba or conda (pay attention to the -py suffix at the end):

mamba create -n=dcp conda-forge::decoupler-py

4. Install the latest development version:

pip install git+https://github.com/scverse/decoupler.git@main

Release notes

See the changelog.

Contact

For questions and help requests, you can reach out in the scverse discourse. If you found a bug, please use the issue tracker.

Citation

Badia-i-Mompel P., Vélez Santiago J., Braunger J., Geiss C., Dimitrov D., Müller-Dott S., Taus P., Dugourd A., Holland C.H., Ramirez Flores R.O. and Saez-Rodriguez J. 2022. decoupleR: Ensemble of computational methods to infer biological activities from omics data. Bioinformatics Advances. https://doi.org/10.1093/bioadv/vbac016