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
maui works with Python 3.6 and TensorFlow 1.1 (does not yet support the yet unreleased TensorFlow 2.0). 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
Survival analysis functionality supplied by lifelines 1. It may be installed directly from pip using
pip install lifelines.
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
Open an issue, send us a pull request, or shoot us an e-mail.
maui is released under the GNU General Public License v3.0 or later.
@jonathanronen, BIMSBbioinfo, 2018