Metadata-Version: 2.1
Name: pyvitae
Version: 1.0.4
Summary: Model-based Trajectory Inference for Single-Cell RNA Sequencing Using Deep Learning with a Mixture Prior
Home-page: https://github.com/jaydu1/VITAE
Author: Jin-Hong Du
Author-email: dujinhong@uchicago.edu
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: tensorflow (>=2.3.0)
Requires-Dist: tensorflow-probability (>=0.11.0)
Requires-Dist: pandas
Requires-Dist: jupyter
Requires-Dist: umap-learn
Requires-Dist: matplotlib
Requires-Dist: numba
Requires-Dist: seaborn
Requires-Dist: scikit-learn
Requires-Dist: louvain
Requires-Dist: scikit-misc
Requires-Dist: networkx

# Model-based Trajectory Inference for Single-Cell RNA Sequencing Using Deep Learning with a Mixture Prior


This package provides computational tools to perform trajectory inference on scRNA-seq data with Variational Autoencoders. For more details, please refer to https://github.com/jaydu1/VITAE.

# Project Members
Jin-Hong Du, Ming Gao, and Jingshu Wang

# License
This project is licensed under the terms of the MIT license.

