trVAE - Regularized Conditional Variational Autoencoders
Project description
trVAE
Introduction
A Keras (with tensorflow backend) implementation of trVAE. trVAE is a deep generative model which learns mapping between multiple different styles (conditions). trVAE can be used for style transfer in images, single-cell perturbations response across celltypes, times and etc.
Getting Started
Installation
Installation with pip
To install the latest version from PyPI, simply use the following bash script:
pip install trvae
or install the development version via pip:
pip install git+https://github.com/theislab/trvae.git
or you can first install flit and clone this repository:
pip install flit
git clone https://github.com/theislab/trVAE
cd trVAE
flit install
Examples
Reproducing paper results:
In order to reproduce paper results visit here.
References
Lotfollahi, Mohammad and Wolf, F. Alexander and Theis, Fabian J. "scGen predicts single-cell perturbation responses." Nature Methods, 2019. pdf
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