sifrimlab / scVAE

scVAE: Variational Autoencoder for single-cell omics data

Author: Jose Ignacio Alvira

Requirements:

• python: 3.8
• numpy: 1.19.1
• pandas: 1.1.3
• scikit-learn: 0.23.2
• tensorflow: 2.2.0

(Optional):

• tensorflow-gpu: 2.2.0

Usage

scVAE.py contains all the necessary functions and class definitions to create your own VAE model. In train.py and train.ipynb you can find an example on how to use it the results for a simulated dataset.