https://github.com/theislab/graphcompass
GraphCompass: Graph Comparison Tools for Differential Analyses in Spatial Systems
https://github.com/theislab/graphcompass
Last synced: 5 months ago
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GraphCompass: Graph Comparison Tools for Differential Analyses in Spatial Systems
- Host: GitHub
- URL: https://github.com/theislab/graphcompass
- Owner: theislab
- License: mit
- Created: 2024-01-23T19:33:42.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2025-07-11T14:20:21.000Z (about 1 year ago)
- Last Synced: 2026-01-15T00:52:45.506Z (6 months ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 2.86 MB
- Stars: 38
- Watchers: 1
- Forks: 2
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
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README
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).
## Features
GraphCompass provides differential analysis methods to study spatial organization across conditions at three levels of abstraction:
1. Cell-type-specific subgraphs:
i. Portrait method,
ii. Diffusion method.
3. Cellular neighborhoods:
i. GLMs for neighborhood enrichment analysis.
4. Entire graphs:
i. Wasserstein WL kernel,
ii. Filtration curves.
Tutorials for the different methods can be found in the `notebooks` folder.
## Requirements
You will find all the necessary dependencies in the `pyproject.toml` file. Dependencies are automatically installed when you install GraphCompass.
## Installation
You can install _GraphCompass_ via [pip] from [PyPI](https://pypi.org/project/graphcompass/).
```console
$ pip install graphcompass
```
or
you can install _GraphCompass_ by cloning the repository and running:
```console
$ pip install -e .
```
## Citation
Mayar Ali, Merel Kuijs, Soroor Hediyeh-zadeh, Tim Treis, Karin Hrovatin, Giovanni Palla, Anna C Schaar, Fabian J Theis, GraphCompass: spatial metrics for differential analyses of cell organization across conditions, *Bioinformatics*, Volume 40, Issue Supplement\_1, July 2024, Pages i548–i557, https://doi.org/10.1093/bioinformatics/btae242
## Contributing
**[COMING SOON]** Contributions are very welcome.
To learn more, see the [Contributor Guide].
## License
Distributed under the terms of the [MIT license][license],
_GraphCompass_ is free and open source software.
## Issues
If you encounter any problems,
please [file an issue] along with a detailed description.
## Credits
This project was generated from [@cjolowicz]'s [Hypermodern Python Cookiecutter] template.
[@cjolowicz]: https://github.com/cjolowicz
[pypi]: https://pypi.org/
[hypermodern python cookiecutter]: https://github.com/cjolowicz/cookiecutter-hypermodern-python
[file an issue]: https://github.com/theislab/graphcompass/issues
[pip]: https://pip.pypa.io/
[license]: https://github.com/theislab/graphcompass/blob/main/LICENSE
[COMING SOON] [contributor guide]: https://github.com/theislab/graphcompass/blob/main/CONTRIBUTING.md