Metadata-Version: 2.1
Name: scrainbow
Version: 0.0.2
Summary: RAINBOW: accurate cell type annotation method via contrastive learning and reference guidance for scCAS data
Home-page: https://github.com/BioX-NKU/RAINBOW
Author: Siyu Li
License: MIT License
Keywords: pip,RAINBOW,single-sell
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.10
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 (>=1.22.4)
Requires-Dist: pandas (>=1.4.3)
Requires-Dist: scipy (>=1.9.0)
Requires-Dist: scikit-learn (>=1.1.2)
Requires-Dist: numba (>=0.55.2)
Requires-Dist: scanpy (>=1.9.1)
Requires-Dist: matplotlib (==3.5.3)
Requires-Dist: anndata (>=0.8.0)
Requires-Dist: episcanpy (>=0.3.2)
Requires-Dist: torch (>=1.11.0)

RAINBOW provides an accurate and efficient way to automatically annotate celltypes in scCAS datasets. All RAINBOW wheels distributed on PyPI are MIT licensed.

