Metadata-Version: 2.1
Name: hto-dnd
Version: 0.1.1a0
Summary: A method to demultiplex hashtagged single-cell data by first applying a denoising and normalizing step adapted from DSB (Denoised and Scaled by Background).
Author-email: Hussen Mohammed Ibrahim <ibrahih3@mskcc.org>, Tobias Krause <krauset@mskcc.org>
License: MIT
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas>=1.5.0
Requires-Dist: numpy>=1.21.0
Requires-Dist: matplotlib>=3.5.0
Requires-Dist: seaborn>=0.12.0
Requires-Dist: scipy>=1.8.0
Requires-Dist: scikit-learn>=1.2.0
Requires-Dist: anndata>=0.8.0
Requires-Dist: pyyaml>=6.0

# hto_dnd
Package for demultiplexing single-cell data after normalizing the data using an adaptation of the DSB algorithm
