Metadata-Version: 2.1
Name: sc_var
Version: 0.2.2
Summary: An approch for interpreting disease-associated human variants using single-cell epigenomics
Author: Gefei Z
Author-email: gefeizhao@163.com
Requires-Python: >=3.11,<4.0
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Dist: matplotlib (>=3.8.2,<4.0.0)
Requires-Dist: mygene (>=3.2.2,<4.0.0)
Requires-Dist: scanpy (>=1.9.6,<2.0.0)
Requires-Dist: scdrs (>=1.0.2,<2.0.0)
Requires-Dist: scipy (>=1.11.4,<2.0.0)
Requires-Dist: seaborn (>=0.13.1,<0.14.0)
Description-Content-Type: text/markdown

An approach to interpreting disease-associated human variants using single-cell epigenomics

What can sv_var do?

Identify risk genes, gene sets, and cells related to different stages and diseases.

Infer cell types involved in complex traits and diseases using single-cell epigenomes AND does not rely on any other annotations and other Omics data.
