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 preprint is available here.
Installation
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:
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/icbi-lab/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. 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.
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
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file scirpy-0.9.1.tar.gz.
File metadata
- Download URL: scirpy-0.9.1.tar.gz
- Upload date:
- Size: 24.8 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: python-requests/2.26.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 585f7c4da32e50e8fd24db7d20cb12ec459077b0958104dc2b721a3ae387cb90 |
|
| MD5 | d76824e4232365cb78e7dccbc2892d43 |
|
| BLAKE2b-256 | e2b8d088a38f5f3db0901415ede0c2a202e885eaceea78eff8ee68701fa0c1dc |
Provenance
File details
Details for the file scirpy-0.9.1-py3-none-any.whl.
File metadata
- Download URL: scirpy-0.9.1-py3-none-any.whl
- Upload date:
- Size: 1.3 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: python-requests/2.26.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 3b4d051817a3300e4a5cfa2e1772c9fcf47a621d255c7b24f3ea9b3e2219588a |
|
| MD5 | 01a2fcfc0495c823ffabc39fe6f7c8e7 |
|
| BLAKE2b-256 | 0595feeb11b123bf186801911ad7a9c6ee4004f6e21c288bf8c032a332ac85c1 |
