data2intelligence / CytoSig_prediction

Example of run CytoSig and reproduce prediction results on bulk and single-cell cohorts

Example code of run CytoSig analysis and reproduce prediction results on bulk and single-cell cohorts

Please CD into the src folder for the following steps.

Stage 1: download datasets

run "./download.py"

The starting data will be available in the folder data, named with bulk, single_cell, and output

Stage 2: convert single-cell data to CytoSig input format

This step is optional if you are only interested in bulk data analysis in Figure 4. Just jump to Stage 3.

run "./convert_sc_data.py"
Note: This step needs a CPU with large memory of 64G as the dataset EGAS00001004571 contains many single cells.

We included two single-cell datasets that are neither in CytoSig input format or CellRanger format. GSE145926 is released as H5 files. EGAS00001004571 is released as Seurat object.
This program will convert both datasets to python pickles of dense matrices as CytoSig input.

Stage 3: predict CytoSig signaling activity and generate figures

run "./run.py"
If you converted single-cell data in step 2, this step will need a CPU with large memory of 64G as the dataset EGAS00001004571 contains many single cells.
The relevant figure numbers are labeled above each function.

Task 1: bulk data from tumor and inflammatory disease studies

Task 2: single-cell data from COVID19 studies (only triggered if you have run the optional stage 2)