Metadata-Version: 2.4
Name: scirpy
Version: 0.22.5
Summary: Python library for single-cell adaptive immune receptor repertoire (AIRR) analysis
Project-URL: Documentation, https://scirpy.readthedocs.io/
Project-URL: Home-page, https://github.com/scverse/scirpy
Project-URL: Source, https://github.com/scverse/scirpy
Author: Gregor Sturm, Tamas Szabo
Maintainer-email: Gregor Sturm <mail@gregor-sturm.de>
License: BSD 3-Clause License
        
        Copyright (c) 2020 Gregor Sturm
        Copyright (c) 2020 Tamas Szabo
        Copyright (c) 2020 Francesca Finotello
        Copyright (c) 2020 Institute of Bioinformatics, Medical University of Innsbruck
        Copyright (c) 2025 scverse®
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License-File: LICENSE
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Requires-Python: >=3.11
Requires-Dist: adjusttext>=0.7
Requires-Dist: airr>=1.4.1
Requires-Dist: anndata>=0.9
Requires-Dist: awkward>=2.1
Requires-Dist: igraph!=0.10,!=0.10.1
Requires-Dist: joblib>=1.3.1
Requires-Dist: logomaker!=0.8.5
Requires-Dist: mudata>=0.2.3
Requires-Dist: networkx>=2.5
Requires-Dist: numba>=0.60
Requires-Dist: numpy>=1.17
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Requires-Dist: pooch>=1.7
Requires-Dist: pycairo>=1.20; sys_platform == 'win32'
Requires-Dist: python-levenshtein
Requires-Dist: scanpy>=1.9.3
Requires-Dist: scikit-learn
Requires-Dist: scipy
Requires-Dist: squarify
Requires-Dist: tqdm>=4.63
Provides-Extra: cupy
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Provides-Extra: dandelion
Requires-Dist: sc-dandelion>=0.3.5; extra == 'dandelion'
Provides-Extra: diversity
Requires-Dist: scikit-bio>=0.5.7; extra == 'diversity'
Provides-Extra: parasail
Requires-Dist: parasail!=1.2.1; extra == 'parasail'
Provides-Extra: rpack
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Description-Content-Type: text/markdown

# Scirpy: single-cell immune receptor analysis in Python

[![Tests][badge-tests]][link-tests]
[![Documentation][badge-docs]][link-docs]
[![PyPI][badge-pypi]][link-pypi]
[![bioconda][badge-bioconda]][link-bioconda]
[![airr][badge-airr]][link-airr]
[![Powered by NumFOCUS][badge-numfocus]][link-numfocus]

Scirpy is a package to analyse T cell receptor (TCR) or B cell receptor (BCR)
repertoires from single-cell RNA sequencing (scRNA-seq) data in Python.
It seamlessly integrates with [scanpy][] and [mudata][] and provides various modules for data import, analysis and visualization.

[//]: # "numfocus-fiscal-sponsor-attribution"

scirpy is part of the scverse® project ([website](https://scverse.org), [governance](https://scverse.org/about/roles)) and is fiscally sponsored by [NumFOCUS](https://numfocus.org/).
If you like scverse® and want to support our mission, please consider making a tax-deductible [donation](https://numfocus.org/donate-to-scverse) to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.

<div align="center">
<a href="https://numfocus.org/project/scverse">
  <img
    src="https://raw.githubusercontent.com/numfocus/templates/master/images/numfocus-logo.png"
    width="200"
  >
</a>
</div>

[badge-tests]: https://img.shields.io/github/actions/workflow/status/scverse/scirpy/test.yaml?branch=main
[link-tests]: https://github.com/scverse/scirpy/actions/workflows/test.yml
[badge-docs]: https://img.shields.io/readthedocs/scirpy
[badge-pypi]: https://img.shields.io/pypi/v/scirpy?logo=PyPI
[link-pypi]: https://pypi.org/project/scirpy/
[link-bioconda]: http://bioconda.github.io/recipes/scirpy/README.html
[badge-bioconda]: https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat
[badge-airr]: https://img.shields.io/static/v1?label=AIRR-C%20sw-tools%20v1&message=compliant&color=008AFF&labelColor=000000&style=flat
[link-airr]: https://docs.airr-community.org/en/stable/swtools/airr_swtools_standard.html
[scverse]: https://scverse.org
[scanpy]: https://scanpy.readthedocs.io/
[mudata]: https://github.com/scverse/mudata
[badge-numfocus]: https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A
[link-numfocus]: http://numfocus.org

## Getting started

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

- [Tutorial][link-tutorial], and the
- [API documentation][link-api].

## Installation

You need to have Python 3.11 or newer installed on your system. If you don't have
Python installed, we recommend installing [Mambaforge](https://github.com/conda-forge/miniforge#mambaforge).

There are several alternative options to install scirpy:

1. Install the latest release of `scirpy` from [PyPI](https://pypi.org/project/scirpy/):

    ```bash
    pip install scirpy
    ```

2. Get it from [Bioconda][link-bioconda]:

    First **setup conda channels [as described here](https://bioconda.github.io/#usage)**. Then install scirpy:

    ```bash
    conda install scirpy
    ```

3. Install the latest development version:

    ```bash
    pip install git+https://github.com/scverse/scirpy.git@main
    ```

4. Run it in a container using [Docker][] or [Podman][]:

    ```bash
    docker pull quay.io/biocontainers/scirpy:<tag>
    ```

where `tag` is one of [these tags](https://quay.io/repository/biocontainers/scirpy?tab=tags).

## Release notes

See the [changelog][changelog].

## Support and Contact

We are happy to assist with problems when using scirpy.

- If you need help with scirpy or have questions regarding single-cell immune-cell receptor analysis in general, please join us in the [scverse discourse][scverse-discourse].
- For bug report or feature requests, please use the [issue tracker][issue-tracker].

We try to respond within two working days, however fixing bugs or implementing new features
can take substantially longer, depending on the availability of our developers.

## Citation

If you use `scirpy` in your work, please cite the `scirpy`
publication as follows:

> **Scirpy: A Scanpy extension for analyzing single-cell T-cell
> receptor sequencing data**
>
> Gregor Sturm, Tamas Szabo, Georgios Fotakis, Marlene Haider, Dietmar
> Rieder, Zlatko Trajanoski, Francesca Finotello
>
> _Bioinformatics_ 2020 Sep 15. doi:
> [10.1093/bioinformatics/btaa611](https://doi.org/10.1093/bioinformatics/btaa611).

You can cite the scverse publication as follows:

> **The scverse project provides a computational ecosystem for
> single-cell omics data analysis**
>
> Isaac Virshup, Danila Bredikhin, Lukas Heumos, Giovanni Palla, Gregor
> Sturm, Adam Gayoso, Ilia Kats, Mikaela Koutrouli, Scverse Community,
> Bonnie Berger, Dana Pe’er, Aviv Regev, Sarah A. Teichmann, Francesca
> Finotello, F. Alexander Wolf, Nir Yosef, Oliver Stegle & Fabian J.
> Theis
>
> _Nat Biotechnol._ 2023 Apr 10. doi:
> [10.1038/s41587-023-01733-8](https://doi.org/10.1038/s41587-023-01733-8).

[scverse-discourse]: https://discourse.scverse.org/
[issue-tracker]: https://github.com/scverse/scirpy/issues
[changelog]: https://scirpy.readthedocs.io/latest/changelog.html
[link-docs]: https://scirpy.readthedocs.io
[link-api]: https://scirpy.readthedocs.io/latest/api.html
[link-tutorial]: https://scirpy.scverse.org/en/latest/tutorials.html
[Docker]: https://www.docker.com/
[Podman]: https://podman.io/
