Metadata-Version: 2.1
Name: pyvitae
Version: 2.0.3
Summary: Joint Trajectory Inference for Single-cell Genomics Using Deep Learning with a Mixture Prior
Home-page: https://github.com/jaydu1/VITAE
Author: Jin-Hong Du
Author-email: jinhongd@andrew.cmu.edu
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: tensorflow (==2.4)
Requires-Dist: tensorflow-probability (==0.12)
Requires-Dist: pandas
Requires-Dist: jupyter
Requires-Dist: umap-learn (>=0.5.0)
Requires-Dist: matplotlib
Requires-Dist: numba
Requires-Dist: seaborn
Requires-Dist: leidenalg
Requires-Dist: scikit-learn
Requires-Dist: networkx
Requires-Dist: statsmodels
Requires-Dist: scanpy (>=1.8.2)

# 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, Tianyu Chen, Ming Gao, and Jingshu Wang

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

