# spatiomic

`spatiomic` is a computational library for the analysis of spatial proteomics, mainly via pixel-based clustering, differential cluster abundance analysis and spatial statistics.

The main goal of this package is to organize different packages and methods that are commonly used when dealing with high-dimensional imaging data behind a single API that allows for scalable high-performance computing applications, whenever possible on the GPU.

Exemplary pixel-based clustering output:

<div style="width: 80%; max-width: 480px; margin: 0 auto; display: flex; justify-content: center;">
    <img alt="Mouse kidney image" src="./_static/example.png" style="border-radius: 0.25rem;" />
</div>

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:::{grid-item-card}  Complex tissue lab
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:link: https://scholar.google.com/citations?user=ZoSBUv4AAAAJ
Our group focuses on the development of novel imaging and computational workflows for spatial omics. Check out our
Google Scholar page for more information.
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:::{grid-item-card}  GitHub
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:link: https://github.com/complextissue/
Our code is published on GitHub, feel free to check it out.
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:::{dropdown} Citation
`spatiomic` was developed at [Aarhus University](https://au.dk/) and the [Institute of Medical Systems Biology, Hamburg](https://ims.bio/) by [Malte Kuehl](https://github.com/maltekuehl/). If you use this package in an academic setting, please cite our work according to the information in the `CITATION.cff` file in our [GitHub repository](https://github.com/complextissue/spatiomic/).
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