Metadata-Version: 2.1
Name: maui-tools
Version: 0.1.4
Summary: Multi-omics Autoencoder Integration
Home-page: https://github.com/BIMSBbioinfo/maui
Author: Jonathan Ronen
Author-email: yablee@gmail.com
License: GPLv3
Platform: UNKNOWN
Description-Content-Type: text/markdown
Requires-Dist: pytest
Requires-Dist: numpy (>=1.14.5)
Requires-Dist: pandas
Requires-Dist: scipy
Requires-Dist: scikit-learn
Requires-Dist: keras
Requires-Dist: tensorflow
Requires-Dist: pytest (>=3.6.0)

<div align="center">
	<img src="hex-maui.png" alt="maui">
</div>

# maui

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Multi-omics Autoencoder Integration (**maui**) is a python package for multi-omics data analysis. It is based on a bayesian latent factor model, with inference done using artificial neural networks. For details, check out our pre-print on bioRxiv: https://www.biorxiv.org/content/early/2018/11/12/464743

## Installation

maui works with Python 3.6. The easiest way to install is from pypi:

	pip install -U maui-tools

This will install all necessary dependencies including keras an tensorflow. The default tensorflow (cpu) will be installed. If tensorflow GPU is needed, please install it prior to installation of maui.

The development version may be installed by cloning this repo and running `python setup.py install`, or, using `pip` directly from github:

	pip install -e git+https://github.com/BIMSBbioinfo/maui.git#egg=maui


#### Optional dependencies

Survival analysis functionality supplied by lifelines [1]. It may be installed directly from pip using `pip install lifelines`.

## Usage

See [the vignette](vignette/maui_vignette.ipynb), and check out [the documentation](https://maui.readthedocs.io/en/latest/).


## Citation

>  Evaluation of colorectal cancer subtypes and cell lines using deep learning. Jonathan Ronen, Sikander Hayat, Altuna Akalin. bioRxiv 464743; doi: https://doi.org/10.1101/464743

## Contributing

Open an issue, send us a pull request, or shoot us an e-mail.

## License

maui is released under the [GNU General Public License v3.0](LICENSE) or later.

---------------------
@jonathanronen, BIMSBbioinfo, 2018


[1]: https://github.com/CamDavidsonPilon/lifelines


