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Condition out-of-sample prediction

Project description

trVAE PyPI version Build Status

Introduction

A Keras (tensorflow < 2.0) implementation of trVAE (transfer Variational Autoencoder) .

trVAE can be used for style transfer in images, predicting perturbations responses and batch-removal for single-cell RNA-seq.

  • For pytorch implementation check Here

Getting Started

Installation

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+https://github.com/theislab/trvae.git

or you can first install flit and clone this repository:

git clone https://github.com/theislab/trVAE
cd trVAE
pip install -r requirements
python setup.py install 

Examples

  • For perturbation prediction and batch-removal check this example from Haber et al.

Reproducing paper results:

In order to reproduce paper results visit here.

Project details


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