Simulation of B cell receptor repertoires
Project description
AIRRSHIP - Adaptive Immune Receptor Repertoire Simulation of Human Immunoglobulin Production
AIRRSHIP simulates B cell receptor (BCR) sequences for use in benchmarking applications where BCR sequences of known origin are required.
AIRRSHIP replicates the VDJ recombination process from haplotype through to somatic hypermutation. Recombination metrics are derived from a range of experimental sequences allowing faithful replication of true repertoires. Users may also control a wide range of parameters that influence allele usage, junctional diversity and somatic hypermutation rates. The current model extends to human heavy chain BCR sequences only.
Installation
pip install airrship
Documentation
Full documentation is available here.
Example datasets
If you do not wish to install and run AIRRSHIP yourself or want to explore the output yourself first, a small example repertoire is hosted at the AIRRSHIP GitHub repository. Larger example repertoire files are available at Zenodo.
Publications
A preprint is currently available at https://doi.org/10.1101/2022.12.20.521228.
Project details
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 airrship-0.1.5.tar.gz
.
File metadata
- Download URL: airrship-0.1.5.tar.gz
- Upload date:
- Size: 688.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.7.12
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2f03832b5f7463e19231523c62997cf089588e3a3edcb4ea1cb83c315c2e3a5d |
|
MD5 | 641b6b0ca79cd15e88d631b192f6d31b |
|
BLAKE2b-256 | 348264013caf338cd2586057edf9b456f6365b0b4e68ec1be5d45320ccb17db4 |
File details
Details for the file airrship-0.1.5-py3-none-any.whl
.
File metadata
- Download URL: airrship-0.1.5-py3-none-any.whl
- Upload date:
- Size: 690.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.7.12
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 46b081125701ee2e3c18e4cf9396aa64b050d82a8de4d3bd32c5121da49ea894 |
|
MD5 | 29662c31301e8bdb26fc330085c4b2af |
|
BLAKE2b-256 | cd4c516bd121d3cad000e40bf47d1ade18fe2958ae79fc646d58fc5531e9f813 |