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v0.1
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cobioda authored Dec 19, 2024
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# Single-Cell In-Situ python package
<div align="center">

# **scispy**

**Single-Cell In-Situ Spatial-Omics Data Analysis**

---

<p align="center">
<a href="https://scispy.readthedocs.io/en/latest/" target="_blank">Documentation</a>
<a href="https://scispy.readthedocs.io/en/latest/notebooks/tutorial.html" target="_blank">Examples</a>
<a href="https://www.biorxiv.org/" target="_blank">Preprint</a>
</p>

[![Tests][badge-tests]][link-tests]
[![Documentation][badge-docs]][link-docs]
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[link-tests]: https://github.com/bfxomics/scispy/actions/workflows/test.yml
[badge-docs]: https://img.shields.io/readthedocs/scispy

scispy is a pthon package for in-situ spatial-omics datasets analysis, mainly developped for vizgen merscope,
scispy is build on top of spatialdata and spatialdata-io and spatialdata-plot librairies which can handle for
Nanostring (cosmx) and 10xGenomics (Xenium) experiments.
</div>

## Background

<p>
A pthon package build on top of spatialdata for Single-Cell In-Situ Spatial-Omics data analysis, developped to handle Vizgen (merscope), Nanostring (cosmx) and 10xGenomics (Xenium) experiments.
</p>

<p align="center">
<img src="https://github.com/cobioda/scispy/docs/_static/scispy.png" width="500px">
</p>

## Features

- **Read in-situ spatial-omics assays experiments**: build on top of spatialdata package
- **Automatic cell type annotation**: scanvi implementation
- **Import anatomical .csv shape file from xenium explorer**: as anndata observation
- **Automatic run pseudobulk data analysis**: using decoupler and pydeseq2 packages
- **Compute cell type proportion in region**: integrating statistical test in case of replicates
- **Produce high quality spatial figures**: build on top of spatialdata_plot package

## Getting started

Please refer to the [documentation][link-docs]. In particular, the

- [API documentation][link-api].
- [Tutorials][link-tutorial]

## Installation

You need to have Python 3.9 or newer installed on your system.

<!--
1) Install the latest release of `scispy` from `PyPI <https://pypi.org/project/scispy/>`_:
```bash
pip install scispy
```
-->

Install the latest development version:
1. Create a conda environment (Python >= 3.10)
2. Install scispy using pip:

```bash
conda create -n scispy python==3.10
conda activate scispy
pip install git+https://github.com/cobioda/scispy.git@main
```

## Release notes

See the [changelog][changelog].

## Contact

For questions and help requests, you can reach out the main developer of this package: in the [kevin lebrigand](mailto:[email protected]).
If you found a bug, please use the [issue tracker][issue-tracker].

## Citation
## Contribution

> preprint available soon
If you found a bug or you want to propose a new feature, please use the [issue tracker][issue-tracker].

[issue-tracker]: https://github.com/cobioda/scispy/issues
[changelog]: https://scispy.readthedocs.io/en/latest/changelog.html
[link-docs]: https://scispy.readthedocs.io
[link-api]: https://scispy.readthedocs.io/en/latest/api.html
[link-tutorial]: https://scispy.readthedocs.io/en/latest/notebooks/tutorial.html

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