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https://github.com/scverse/scirpy

A scanpy extension to analyse single-cell TCR and BCR data.
https://github.com/scverse/scirpy

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A scanpy extension to analyse single-cell TCR and BCR data.

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README 

        
# 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/).

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.





  




[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 3.10 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:

    ```



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/