Metadata-Version: 2.1
Name: sciRED
Version: 1.2.1
Summary: single cell interpretable Residual Decomposition
Home-page: https://github.com/delipouya/sciRED.git
Author: Delaram Pouyabahar
Author-email: d.pouyabahar@mail.utoronto.ca
License: MIT
Keywords: sciRED,single cell RNA-seq,interpretability,factor decomposition
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Description-Content-Type: text/plain
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: scanpy
Requires-Dist: statsmodels
Requires-Dist: seaborn
Requires-Dist: umap-learn
Requires-Dist: matplotlib
Requires-Dist: scikit-learn
Requires-Dist: scipy
Requires-Dist: xgboost
Requires-Dist: scikit-image
Requires-Dist: diptest==0.2.0
Provides-Extra: dev
Requires-Dist: pytest; extra == "dev"
Requires-Dist: twine; extra == "dev"

sciRED is a Python package designed to improve the interpretation of single-cell RNA sequencing data, specifically focusing on signal extraction via factor decomposition. It simplifies the process by removing confounding effects, mapping factors to covariates, identifying unexplained factors, and annotating genes and biological processes. Applying sciRED to various scRNA-seq datasets can unveil diverse biological signals, such as health/disease variation, cell-type identity, sex/age differences, stimulation signals, and rare cell type signatures.
