# decoupler - Ensemble of methods to infer biological activities <img src="https://github.com/saezlab/decoupleR/blob/master/inst/figures/logo.svg?raw=1" align="right" width="120" class="no-scaled-link" />
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`decoupler` is a package containing different enrichment statistical methods to extract biological activities 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
Footprint 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 license, each original resource carries their own.
[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.
<https://doi.org/10.1093/bioadv/vbac016>
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"description": "# decoupler - Ensemble of methods to infer biological activities <img src=\"https://github.com/saezlab/decoupleR/blob/master/inst/figures/logo.svg?raw=1\" align=\"right\" width=\"120\" class=\"no-scaled-link\" />\n<!-- badges: start -->\n[](https://github.com/saezlab/decoupler-py/actions)\n[](https://github.com/saezlab/decoupler-py/issues/)\n[](https://pepy.tech/project/decoupler)\n[](https://decoupler-py.readthedocs.io/en/latest/?badge=latest)\n[](https://codecov.io/gh/saezlab/decoupler-py)\n\n[](https://anaconda.org/conda-forge/decoupler-py)\n[](https://anaconda.org/conda-forge/decoupler-py)\n<!-- badges: end -->\n\n`decoupler` is a package containing different enrichment statistical methods to extract biological activities from omics data within a unified framework.\nThis is its faster and memory efficient Python implementation, for the R version go [here](https://github.com/saezlab/decoupleR).\n\nFor further information and example tutorials, please check our [documentation](https://decoupler-py.readthedocs.io/en/latest/index.html).\n\nIf you have any question or problem do not hesitate to open an [issue](https://github.com/saezlab/decoupler-py/issues).\n\n## Installation\n\n`decoupler` can be installed from `pip` (lightweight installation)::\n```\npip install decoupler\n```\n\nIt can also be installed from `conda` and `mamba` (this includes extra dependencies):\n```\nmamba create -n=decoupler conda-forge::decoupler-py\n```\n\nAlternatively, to stay up-to-date with the newest unreleased version, install from source: \n```\npip install git+https://github.com/saezlab/decoupler-py.git\n```\n\n## scverse\n`decoupler` is part of the [scverse](https://scverse.org) ecosystem, a collection of tools for single-cell omics data analysis in python.\nFor more information check the link.\n\n## License\nFootprint methods inside decoupler can be used for academic or commercial purposes, except `viper` which holds a non-commercial license. \n\nThe data redistributed by OmniPath does not have a license, each original resource carries their own. \n[Here](https://omnipathdb.org/info) one can find the license information of all the resources in OmniPath.\n\n## Citation\n\nBadia-i-Mompel P., V\u00e9lez Santiago J., Braunger J., Geiss C., Dimitrov D.,\nM\u00fcller-Dott S., Taus P., Dugourd A., Holland C.H., Ramirez Flores R.O.\nand Saez-Rodriguez J. 2022. decoupleR: Ensemble of computational methods\nto infer biological activities from omics data. Bioinformatics Advances.\n<https://doi.org/10.1093/bioadv/vbac016>\n\n",
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