Metadata-Version: 2.1
Name: cpa-tools
Version: 0.4.0
Summary: Compositional Perturbation Autoencoder (CPA)
Home-page: https://github.com/theislab/cpa/
License: BSD-3-Clause
Author: Mohsen Naghipourfar
Author-email: naghipourfar@berkeley.edu
Requires-Python: >=3.7.2,<3.11
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
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Project-URL: Documentation, https://cpa-tools.readthedocs.io
Description-Content-Type: text/markdown

# CPA - Compositional Perturbation Autoencoder


## What is CPA?

![Alt text](https://user-images.githubusercontent.com/33202701/156530222-c61e5982-d063-461c-b66e-c4591d2d0de4.png?raw=true "Title")

`CPA` is a framework to learn effects of perturbations at the single-cell level. CPA encodes and learns phenotypic drug response across different cell types, doses and drug combinations. CPA allows:

* Out-of-distribution predictions of unseen drug combinations at various doses and among different cell types.
* Learn interpretable drug and cell type latent spaces.
* Estimate dose response curve for each perturbation and their combinations.
* Access the uncertainty of the estimations of the model.


Usage and installation
-------------------------------
See [here](https://cpa-tools.readthedocs.io/en/latest/index.html) for documentation and tutorials.

Support and contribute
-------------------------------
If you have a question or new architecture or a model that could be integrated into our pipeline, you can
post an [issue](https://github.com/theislab/cpa/issues/new)

