Scirpy: A Scanpy extension for analyzing single-cell immune-cell receptor sequencing data
Scirpy is a scalable python-toolkit to analyse T cell receptor (TCR) or B cell receptor (BCR) repertoires from single-cell RNA sequencing (scRNA-seq) data. It seamlessly integrates with the popular scanpy library and provides various modules for data import, analysis and visualization.

Getting started
Please refer to the documentation. In particular, the
Tutorial, and the
In the documentation, you can also learn more about our immune-cell receptor model.
Case-study
The case study from our paper is available here.
Installation
You need to have Python 3.8 or newer installed on your system. If you don’t have Python installed, we recommend installing Miniconda.
There are several alternative options to install scirpy:
Install the latest release of
scirpy
from PyPI:
pip install scirpy
Get it from Bioconda:
conda install -c conda-forge -c bioconda scirpy
Install the latest development version:
pip install git+https://github.com/scverse/scirpy.git@master
docker pull quay.io/biocontainers/scirpy:<tag>
where tag
is one of these tags.
Support
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.
For bug report or feature requests, please use the 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.
Release notes
See the release section.
Contact
Please use the issue tracker.
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.
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. 2022 Apr 10. doi: 10.1038/s41587-023-01733-8.