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Python library for single-cell adaptive immune receptor repertoire (AIRR) analysis

Project description

Build Status Documentation Status PyPI Bioconda AIRR-compliant The uncompromising python formatter

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.

The scirpy workflow

Getting started

Please refer to the documentation. In particular, the

In the documentation, you can also learn more about our immune-cell receptor model.


The case study from our preprint is available here.


You need to have Python 3.7 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:

  1. Install the latest release of scirpy from PyPI:
pip install scirpy
  1. Get it from Bioconda:
conda install -c conda-forge -c bioconda scirpy
  1. Install the latest development version:
pip install git+
  1. Run it in a container using Docker or Podman:
docker pull<tag>

where tag is one of these tags.


We are happy to assist with problems when using scirpy. Please report any bugs, feature requests, or help requests using 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.


Please use the issue tracker.


Sturm, G. Tamas, GS, …, Finotello, F. (2020). Scirpy: A Scanpy extension for analyzing single-cell T-cell receptor sequencing data. Bioinformatics. doi:10.1093/bioinformatics/btaa611

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