PanoView is an iterative PCA-based method that integrates with a novel density-based clustering, ordering local maximum by convex hull (OLMC) algorithm, to identify cell subpopulations for single-cell RNA-sequencing. For details of the method, please see our paper at PLOS Computational Biology (https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007040).
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PanoView is a python module that uses other common python libraries such as numpy, scipy, pandas, scikit-learn, etc., to realize the proposed algorithm. Prior to installing PanoView from Github repository, please make sure that Git is properly installed or go to https://git-scm.com/ for the installation of Git. To install PanoView at your local computer, open your command prompt and type the following
pip install git+https://github.com/mhu10/scPanoView.git#egg=scPanoView
It will install all the required python libraries for executing PanoView. To test the installation of PanoView, open the python interpreter or your preferred IDE (Spyder, PyCharm, Jupyter, etc. ) and type the following
from PanoramicView import scPanoView
There should not be any error message popping out.
Note: PanoView was implement and tested by python3.6.
Plese refer to the manuaul ( "PanoViewManual.pdf" ) for details of executing PanoView algorithm in python.
For running tutorial in the manual, please download the example dataset ("ExamplePollen.zip" ) and upzip it into your python working directory.