CSN

We provide two types, online CSN analysis (only supports files smaller than 5m) and local CSN command line running.

Get CSN Online

Please select your File, choose Normalize, Alpha and Boxsize.

True False

Parameter Description:
data: Gene expression matrix (TPM/RPKM/FPKM/count), rows = genes, columns = cells alpha: Significant level (eg. 0.001, 0.01, 0.05 ...), Default = 0.01 boxsize: Size of neighborhood, Default = 0.1 (nx(k) = ny(k) = 0.1*n) normalize: 1 result is normalized (Default); 0 result is not normalized
Example:
We provide an example file for you to test the CSN tools, click here and use this file have a try.

Get CSN Command Line

Please choose Normalize, Alpha and Boxsize.

True False

Parameter Description:
data: Gene expression matrix (TPM/RPKM/FPKM/count), rows = genes, columns = cells alpha: Significant level (eg. 0.001, 0.01, 0.05 ...), Default = 0.01 boxsize: Size of neighborhood, Default = 0.1 (nx(k) = ny(k) = 0.1*n) normalize: 1 result is normalized (Default); 0 result is not normalized
Help instructions:
1. Prepare input files (Gene expression matrix, must .csv file)
2. How to run (You should have Python environment:)
The program relies on Python extension packages (scipy, click, os, time, pandas, numpy, decimal). Users need to install the above extension packages using 'pip install package'.

Example: python cns.py yourfile