Python library for single-cell adaptive immune receptor repertoire (AIRR) analysis
Project description
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 scirpyGet it from Bioconda:
conda install -c conda-forge -c bioconda scirpyInstall the latest development version:
pip install git+https://github.com/scverse/scirpy.git@masterdocker 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
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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