1.process_data

Merge single cells and normalize using pycytominer

In this module, we perform two preprocessing steps on the SQLite files using pycytominer:

1. Merge and annotate single cells from the SQLite file using the pycytominer SingleCell class
2. Normalize the single cells using the negative controls (e.g., DMSO for compound treatment, no-target or target intergenic region sgRNAs for crispr treatment, and genes with weak signatures in orf treatment) as reference for the standard scalar method.

Run merging and normalization notebook

To process the data, run the process_data.sh file which will convert the notebook into a python file and run it from terminal.

# Make sure you are in the 1.process_data directory
cd 1.process_data
# Run the notebook as a python script
source process_data.sh