scPDA: denoising protein expression in droplet-based single-cell data

This folder contains the scPDA package and all the code needed to reproduce the results and figures in the scPDA manuscript. Folder Explanation: data: Four datasets (in .rds format) used in the Results section of the manuscript. code: Scripts that apply various protein‐count denoising methods (GMM, DSB, scAR, DecontPro, scPDA) to each dataset. Results are saved under the “results” folder. results: Denoised count outputs for each dataset and each method. fig_reprod: Scripts to regenerate figures in the manuscript and supplementary materials. scPDA: The development version of the scPDA Python package (installable via “pip install -e scPDA”)