Metadata-Version: 2.1
Name: sainsc
Version: 0.2.1
Summary: Segmentation-free Analysis of In Situ Capture data
Author-email: Niklas Müller-Bötticher <niklas.mueller-boetticher@charite.de>
License: MIT License
        
        Copyright (c) 2024 Niklas Müller-Bötticher, Naveed Ishaque, Roland Eils, Berlin Institute of Health @ Charité
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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Project-URL: Homepage, https://github.com/HiDiHlabs/sainsc
Project-URL: Documentation, https://sainsc.readthedocs.io
Project-URL: Repository, https://github.com/HiDiHlabs/sainsc
Project-URL: Issues, https://github.com/HiDiHlabs/sainsc/issues
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Rust
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Typing :: Typed
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: anndata>=0.9
Requires-Dist: matplotlib
Requires-Dist: matplotlib-scalebar
Requires-Dist: numba>=0.44
Requires-Dist: numpy>=1.21
Requires-Dist: pandas
Requires-Dist: polars[pandas]>=1
Requires-Dist: scikit-image>=0.18
Requires-Dist: scipy>=1.9
Requires-Dist: seaborn>=0.11
Requires-Dist: typing-extensions>=4
Provides-Extra: spatialdata
Requires-Dist: spatialdata>=0.1; extra == "spatialdata"
Provides-Extra: docs
Requires-Dist: sphinx; extra == "docs"
Requires-Dist: sphinx-autoapi>=3.1; extra == "docs"
Requires-Dist: sphinx-copybutton; extra == "docs"
Requires-Dist: sphinx-rtd-theme; extra == "docs"
Requires-Dist: myst-nb; extra == "docs"
Provides-Extra: data
Requires-Dist: pooch>=1; extra == "data"
Provides-Extra: dev
Requires-Dist: sainsc[data,docs,spatialdata]; extra == "dev"
Requires-Dist: pre-commit; extra == "dev"

# sainsc

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
[![Code style: Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)
[![Imports: isort](https://img.shields.io/badge/%20imports-isort-%231674b1?style=flat&labelColor=ef8336)](https://pycqa.github.io/isort/)
[![Checked with mypy](https://www.mypy-lang.org/static/mypy_badge.svg)](http://mypy-lang.org/)
[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit)](https://github.com/pre-commit/pre-commit)

/ˈsaiəns/

_"**S**egmentation-free **A**nalysis of **In S**itu **C**apture data"_
or alternatively
"_**S**tupid **A**cronyms **In Sc**ience_"

`sainsc` is a segmentation-free analysis tool for spatial transcriptomics from in situ
capture technologies (but also works for imaging-based technologies). It is easily
integratable with the [scverse](https://github.com/scverse) (i.e. `scanpy` and `squidpy`)
by exporting data in [`AnnData`](https://anndata.readthedocs.io/) or
[`SpatialData`](https://spatialdata.scverse.org/) format.

## Installation

`sainsc` is available on [PyPI](https://pypi.org/) and [bioconda](https://bioconda.github.io/).

```sh
# PyPI
pip install sainsc
```

```sh
# or conda
conda install bioconda::sainsc
```

For detailed installation instructions please refer to the
[documentation](https://sainsc.readthedocs.io/page/installation.html).

## Documentation

For an extensive documentation of the package please refer to the
[ReadTheDocs page](https://sainsc.readthedocs.io)

## Versioning

This project follows the [SemVer](https://semver.org/) guidelines for versioning.

## Citations

If you are using `sainsc` for your research please cite

Müller-Bötticher, N., Tiesmeyer, S., Eils, R., and Ishaque, N.
"Sainsc: a computational tool for segmentation-free analysis of in-situ capture"
bioRxiv (2024) https://doi.org/10.1101/2024.08.02.603879

## License

This project is licensed under the MIT License - for details please refer to the
[LICENSE](./LICENSE) file.
