Metadata-Version: 2.1
Name: MetaQ_sc
Version: 1.0.6
Summary: The implementation of the paper 'MetaQ: fast, scalable and accurate metacell inference via deep single-cell quantization'. Please refer to the paper and code repository (https://github.com/XLearning-SCU/MetaQ) for more details.
Home-page: https://github.com/XLearning-SCU/MetaQ
Author: Yunfan Li
Author-email: yunfanli.gm@gmail.com
License: MIT
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Requires-Python: >=3.6.0
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: torch==2.1.1
Requires-Dist: numpy==1.26.0
Requires-Dist: alive-progress==3.1.5
Requires-Dist: scanpy==1.9.6
Requires-Dist: scipy==1.11.3
Requires-Dist: scikit-learn==1.1.3
Requires-Dist: einops==0.7.0
Provides-Extra: for-kmeans-codebook-initialization
Requires-Dist: faiss-gpu==1.7.4; extra == "for-kmeans-codebook-initialization"
Provides-Extra: for-geometric-codebook-initialization
Requires-Dist: geosketch==1.2; extra == "for-geometric-codebook-initialization"

The implementation of the paper 'MetaQ: fast, scalable and accurate metacell inference via deep single-cell quantization'. Please refer to the paper and code repository (https://github.com/XLearning-SCU/MetaQ) for more details.
