Metadata-Version: 2.1
Name: epiaster
Version: 0.0.2
Summary: ASTER: accurate estimation of cell-type numbers in single-cell chromatin accessibility data
Home-page: https://github.com/BioX-NKU/ASTER
Author: BioX-NKU
License: MIT Licence
Keywords: pip,aster,single-cell
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.6
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX :: Linux
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.6.0
License-File: LICENSE
Requires-Dist: numpy (<1.22,>=1.21.6)
Requires-Dist: scipy (>=1.8.0)
Requires-Dist: scikit-learn (>=1.1.0)
Requires-Dist: kneed (>=0.7.0)
Requires-Dist: scanpy (>=1.9.1)
Requires-Dist: episcanpy (>=0.3.2)
Requires-Dist: igraph (>=0.9.10)
Requires-Dist: louvain (>=0.7.1)
Requires-Dist: leidenalg (>=0.8.10)

ASTER provides an accurate and efficient way to estimate the number of cell types in single-cell chromatin accessibility data. We provide documentation in the form of functional application programming interface documentation, tutorials and example workflows at https://aster.readthedocs.io/en/latest/index.html. All ASTER wheels distributed on PyPI are MIT licensed.
