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Condition out-of-sample prediction

Project description

trVAE PyPI version Build Status


A Keras (tensorflow < 2.0) implementation of trVAE (transfer Variational Autoencoder) . trVAE is a deep generative model which learns mapping between multiple different styles (conditions). trVAE can be used for style transfer in images, predicting single-cell perturbations responses and batch removal.

  • For pytorch implementation check Here

Getting Started


Before installing trVAE package, we suggest you to create a new Python 3.6 (or 3.7) virtual env (or conda env) with the following steps:

1. Installing virtualenv

pip install virtualenv

2. Create a virtual with Python 3.6

virtualenv trvae-env --python=python3.6 

3. trVAE package installation

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+

or you can first install flit and clone this repository:

git clone
cd trVAE
pip install -r requirements
python install 


  • For perturbation prediction check this example from Haber et al..

Reproducing paper results:

In order to reproduce paper results visit here.

Project details

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Files for trVAE, version 1.1.1
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Filename, size trVAE-1.1.1.tar.gz (32.1 MB) File type Source Python version None Upload date Hashes View

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