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 3.12 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

Agent Skill

decoupler ships an Agent Skill that teaches coding agents to use the library correctly. Install it into your agent's skills directory by choosing a framework with --agent {claude,codex,agents,claude-science} (or an explicit directory with --dest):

decoupler-install-skills --agent claude

Re-run with --force after upgrading, use --check to see whether an installed copy is up to date, or --print-path to show where the bundled copy lives inside the package.

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.

License

Enrichment methods inside decoupler can be used for academic or commercial purposes, except viper which holds a non-commercial license.

The data redistributed by OmniPath does not have a single license, each original resource has its own. By default, decoupler assumes an academic license, but commercial or nonprofit licenses can be specified in the license parameter of decoupler's OmniPath functions. Here one can find the license information of all the resources in OmniPath.

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