PUPAID is a workflow written in R + ImageJ languages which is dedicated to the semi-automated processing and analysis of multi-channel immunofluorescence data. The workflow is designed to extract fluorescence signals within automatically-segmented cells, defined here as Areas of Interest (AOI), on whole multi-layer slides (or eventually cropped sections of them), defined here as Regions of Interest (ROI), in a simple and understandable yet thorough manner. The included (but facultative) R Shiny-based interactive application makes PUPAID also suitable for scientists who are not fluent with R programming. Furthermore, we show that PUPAID identifies significantly more cells, especially in high-density regions, as compared to already published state-of-the-art methods such as StarDist or Cellpose . For extended possibilities and downstream compatibility, single cell information is exported as FCS files (the standardized file format for single cell-based cytometry data) in order to be openable using any third-party cytometry analysis software or any analysis workflow which takes FCS files as input.
No takes yet. Share an insight, caveat, or question.
Régnier et al. (2024) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: