Metadata-Version: 2.1
Name: scTOP
Version: 0.0.2
Summary: A package for identifying cell phenotype from single-cell RNA-sequencing data.
Home-page: https://github.com/Emergent-Behaviors-in-Biology/scTOP
Author: Maria Yampolskaya
Author-email: mariay@bu.edu
License: UNKNOWN
Project-URL: Docs, https://readthedocs.org/projects/sctop/
Project-URL: Bug Tracker, https://github.com/Emergent-Behaviors-in-Biology/scTOP/issues
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License (GPL)
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
License-File: LICENSE.txt

=========================================================================================
scTOP: Single-cell Type Order Parameters
=========================================================================================

`Documentation available via Read the Docs <https://sctop.readthedocs.io/>`_

A package for finding projections onto known cell phenotyes, given matrices of raw RNA count data. 
The theoretical background for this project can be found in `Epigenetic Landscapes Explain Partially Reprogrammed Cells and Identify Key Reprogramming Genes <https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003734>`_ by Alex H. Lang, Hu Li, James J. Collins, and Pankaj Mehta. 

A manuscript containing the technical details of applying our method to single-cell RNA-seq is in progress, hopefully to be completed Summer 2022.

Installation
=============

To install with PyPi:

``pip install scTOP``

Dependencies
-------------
* NumPy
* Pandas
* SciPy

Sources for reference databases
=================================
* `Mouse Cell Atlas <http://bis.zju.edu.cn/MCA/>`_
* `Atlas of Mouse Lung Developmen <https://journals.biologists.com/dev/article-abstract/148/24/dev199512/273783/A-single-cell-atlas-of-mouse-lung-development?redirectedFrom=fulltext>`_



