Metadata-Version: 2.4
Name: scab
Version: 0.2.4
Summary: Single cell analysis of B cells
Home-page: https://github.com/brineylab/scab
Author: Bryan Briney
Author-email: briney@scripps.edu
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: abstar>=0.7.1
Requires-Dist: abutils>=0.5.2
Requires-Dist: anndata
Requires-Dist: click
Requires-Dist: dnachisel
Requires-Dist: fastcluster
Requires-Dist: harmonypy
Requires-Dist: humanize
Requires-Dist: leidenalg
Requires-Dist: matplotlib
Requires-Dist: mnemonic
Requires-Dist: natsort
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: prettytable
Requires-Dist: pytest
Requires-Dist: python-Levenshtein
Requires-Dist: pyyaml
Requires-Dist: sample-sheet
Requires-Dist: scanpy
Requires-Dist: scanorama
Requires-Dist: scipy
Requires-Dist: scrublet
Requires-Dist: scvelo
Requires-Dist: seaborn>=0.11
Requires-Dist: umap-learn
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license-file
Dynamic: requires-dist
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# scab

Single cell analysis of B cells.
scab is a core component of the ab\[x\] toolkit for antibody sequence analysis.
  
  - Source code: [github.com/briney/scab](https://github.com/briney/scab)  
  - Documentation: [scab.readthedocs.org](https://scab.readthedocs.io)  
  - Download: [pypi.python.org/pypi/scab](https://pypi.python.org/pypi/scab)  
  
### install  
`pip install scab`  


### api  
The intended use of scab is through the public API, enabling incorporation of scab's methods and utilities into integrated analysis pipelines or for interative analysis of antibody repertoires in notebook-style computing environments like Jupyter. See the scab [documentation](http://scab.readthedocs.io) for more detail about the API.  


### testing  
To run the test suite, clone or download the repository and run `pytest ./` from the top-level directory. The same tests are run after every commit using TravisCI.  
  

### requirements  
Python 3.6+  
abstar
abutils>=0.2.5
anndata
dnachisel
fastcluster
harmonypy
leidenalg
matplotlib
mnemonic
natsort
numpy
pandas
prettytable
pytest
python-Levenshtein
scanpy
scanorama
scipy
scrublet
scvelo
seaborn>=0.11
umap-learn
  
All of the above dependencies can be installed with pip, and will be installed automatically when installing scab with pip.  
If you're new to Python, a great way to get started is to install the [Anaconda Python distribution](https://www.continuum.io/downloads), which includes pip as well as a ton of useful scientific Python packages.
  
