# decoupler-py
**Repository Path**: mirrors_grst/decoupler-py
## Basic Information
- **Project Name**: decoupler-py
- **Description**: Python package to perform enrichment analysis from omics data.
- **Primary Language**: Unknown
- **License**: GPL-3.0
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-04-04
- **Last Updated**: 2026-05-16
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README
# decoupler - Ensemble of methods to infer biological activities 
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[](https://codecov.io/gh/saezlab/decoupler-py)
[](https://pepy.tech/project/decoupler)
[](https://anaconda.org/conda-forge/decoupler-py)
[](https://anaconda.org/conda-forge/decoupler-py)
[](https://anaconda.org/conda-forge/decoupler-py)
`decoupler` is a 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, for the R version go [here](https://github.com/saezlab/decoupleR).
For further information and example tutorials, please check our [documentation](https://decoupler-py.readthedocs.io/en/latest/index.html).
If you have any question or problem do not hesitate to open an [issue](https://github.com/saezlab/decoupler-py/issues).
## Installation
`decoupler` can be installed from `pip` (lightweight installation)::
```
pip install decoupler
```
It can also be installed from `conda` and `mamba` (this includes extra dependencies):
```
mamba create -n=decoupler conda-forge::decoupler-py
```
Alternatively, to stay up-to-date with the newest unreleased version, install from source:
```
pip install git+https://github.com/saezlab/decoupler-py.git
```
## scverse
`decoupler` is part of the [scverse](https://scverse.org) ecosystem, a collection of tools for single-cell omics data analysis in python.
For more information check the link.
## 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](https://omnipathdb.org/info) 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.