Metadata-Version: 2.4
Name: graphcompass
Version: 0.2.5
Summary: Spatial metrics for differential analyses of cell organization across conditions
Project-URL: Homepage, https://github.com/theislab/graphcompass
Project-URL: Bug Tracker, https://github.com/theislab/graphcompass/issues
Project-URL: Source Code, https://github.com/theislab/graphcompass
Author: Mayar Ali, Merel Kuijs
Maintainer-email: Mayar Ali <mayar.ali@helmholtz-munich.de>, Merel Kuijs <merelsentina.kuijs@helmholtz-munich.de>
License: MIT License
        
        Copyright © 2024 Mayar Ali and Merel Kuijs
        
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License-File: LICENSE
Keywords: bio-informatics,cell spatial organization,graph analytics,spatial data analysis,spatial omics,tissue architecture
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Framework :: Jupyter
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Typing :: Typed
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Description-Content-Type: text/markdown

[![PyPI](https://img.shields.io/pypi/v/graphcompass.svg)](https://pypi.org/project/graphcompass/)

# GraphCompass
GraphCompass (**Graph** **Comp**arison Tools for Differential **A**nalyses in **S**patial **S**ystems) is a Python-based framework that brings together a robust suite of graph analysis and visualization methods, specifically tailored for the differential analysis of cell spatial organization using spatial omics data. It is developed on top on [`Squidpy`](https://github.com/scverse/squidpy/) and [`AnnData`](https://github.com/scverse/anndata).

Visit our [`repository`](https://github.com/theislab/graphcompass/) for documentation and tutorials.

## GraphCompass key analysis features include:

- Cell-type-specific subgraphs comparison.
- Cellular neighborhoods comparison.
- Entire graphs comparison.

## Installation
Install GraphCompass via PyPI by running:

    pip install graphcompass

## Contributing to GraphCompass
We are happy to collaborate. If you want to contribute to GraphCompass, head over to our GitHub repository and open an issue to discuss what you would like to change.
