Patient-Level Analysis of Single Cell Disease Atlas with Optimal Transport of Gaussian Mixtures Variational Autoencoders
Project description
PILOT-GM-VAE (Paper)
Patient-Level Analysis of Single Cell Disease Atlas with Optimal Transport of Gaussian Mixtures Variational Autoencoders. We introduce here PatIent-Level Analysis with Optimal Transport based on Gausian Mixture Variational AutoEncoders. PILOT-GM-VAE explores the power of GM-VAE to estimate models describing complex single cell distributions with efficient optimal transport algorithms for estimating the distance between GMs.
git clone https://github.com/CostaLab/PILOT-GM-VAE.git
cd PILOT-GM-VAE
conda create --name PILOT-GM-VAE python
conda activate PILOT-GM-VAE
pip install pilotgm
Navigate to Tutorial.
Then please use the provided Tutorial.
Data sets
You can access the used data sets by PILOT-GM-VAE in Part 1 , Part 2
and Part 3
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