Metadata-Version: 2.1
Name: cellograph
Version: 0.0.5
Summary: cellograph
Home-page: https://github.com/jashahir/cellograph
Author: Jamshaid Shahir, Purvis Lab, University of North Carolina at Chapel Hill
Author-email: jashahir@live.unc.edu
License: MIT License - See LICENSE file
Keywords: big-data,manifold-learning,computational-biology,graph neural networks,single-cell,genomics
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: tensorflow (>=2.7.0)
Requires-Dist: Keras (==2.4.3)
Requires-Dist: phate (==1.0.7)
Requires-Dist: scanpy (==1.9.1)
Requires-Dist: scvelo (==0.2.4)
Requires-Dist: pandas (==1.2.2)
Requires-Dist: anndata (==0.8.0)
Requires-Dist: numpy (==1.20.1)
Requires-Dist: scipy (==1.6.1)
Requires-Dist: scikit-learn
Requires-Dist: seaborn (>=0.11.2)
Requires-Dist: spektral (==1.1.0)

# Cellograph

Cellograph is a graph neural network model that uses a two-layer graph convolutional network to analyze single-cell RNA sequencing data (but can extended to other single-cell modalities). More details can be found in [Shahir et al, 2023].

To learn how to implement Cellograph, take a look at our tutorial here.
