popcom

PopCom is a new method for the identification of sub-populations of cells present within individual single cell experiments and mapping of these sub-populations across the experiments.


License
GPL-3.0
Install
pip install popcom==0.1.0

Documentation

popcom

A python tool to do comparative analysis of mulitple single cell datasets.

Install

$ pip install popcom

Input File Format

popcom needs multiple single cell RNA-seq dataset as inputs. Bascially, the format look like the following. Example data file can be found in the data folder.

Cell1ID Cell2ID Cell3ID Cell4ID Cell5ID ...
Gene1 12 0 0 0 ...
Gene2 125 0 298 0 ...
Gene3 0 0 0 0 ...
... ... ... ... ... ...

How to use

import popcom package

from popcom import MergeSingleCell
from popcom import SingleCellData

read in RNA-seq data

File1 = "../../Data/Human&Mouse_Kidney/GSE107585_Mouse_kidney_single_cell_seurat_data1.txt"
Test1 = SingleCellData()
Test1.ReadData_SeuratFormat(File1)


File2 = "../../Data/Human&Mouse_Kidney/GSE107585_Mouse_kidney_single_cell_seurat_data2.txt"
Test2 = SingleCellData()
Test2.ReadData_SeuratFormat(File2)

File3 = "../../Data/Human&Mouse_Kidney/GSE107585_Mouse_kidney_single_cell_seurat_data3.txt"
Test3 = SingleCellData()
Test3.ReadData_SeuratFormat(File3)


File4 = "../../Data/Human&Mouse_Kidney/GSE107585_Mouse_kidney_single_cell_seurat_data4.txt"
Test4 = SingleCellData()
Test4.ReadData_SeuratFormat(File4)

Normlize counts data, find highly vaiable genes, and natural logarithm of one plus of the counts data

Test1.Normalized_per_Cell()
Test1.FindHVG()
Test1.Log1P()

Test2.Normalized_per_Cell()
Test2.FindHVG()
Test2.Log1P()

Test3.Normalized_per_Cell()
Test3.FindHVG()
Test3.Log1P()

Test4.Normalized_per_Cell()
Test4.FindHVG()
Test4.Log1P()

Combine data

MSingle = MergeSingleCell(Test1, Test2, Test3, Test4)

Define supercells for each data sets(in this example, we define 200 supercells for each dataset)

MSingle.MultiDefineSuperCell(200,200,200,200)

Find