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Streamlining Multiplexed Tissue Image Analysis with PIPΣX: An Integrated Automated Pipeline for Image Processing and

Mariya Mardamshina1, Frederic Ballllosera Navarro1, Anna Martinez Casals1

  • 1Department of Bioengineering, Stanford University, Stanford, CA, USA.

Biorxiv : the Preprint Server for Biology
|July 14, 2025
PubMed
Summary

We developed PIPΣX (Pipeline for Image Processing and EXploration), an open-source software simplifying spatial proteomics image analysis. This tool empowers researchers to extract biological insights from complex multiplexed tissue imaging data more easily and robustly.

Keywords:
Graphical user interfaceImage segmentationInteractive data visualizationLaser microdissectionMultiplexed tissue imagingOpen-source bioimage analysisSingle-cell image analysisSpatial proteomics

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Area of Science:

  • Spatial biology
  • Proteomics
  • Bioinformatics

Background:

  • Multiplexed tissue imaging allows high-content analysis of cellular behavior in native environments.
  • Data analysis remains a significant bottleneck in spatial proteomics research.
  • Existing tools often require advanced programming skills, limiting accessibility.

Purpose of the Study:

  • To develop a user-friendly, open-source software solution for end-to-end spatial proteomics image analysis.
  • To make complex image analysis approachable for researchers with limited programming experience.
  • To streamline the process from image preprocessing to spatial data exploration.

Main Methods:

  • Developed PIPΣX (Pipeline for Image Processing and EXploration), an integrated software with a graphical user interface.
  • Implemented automated workflows for image preprocessing, cell segmentation, and signal quantification.
  • Incorporated quality control features and guided user assistance throughout the analysis pipeline.

Main Results:

  • PIPΣX provides a robust and intuitive platform for analyzing multiplexed tissue imaging data.
  • The software facilitates seamless integration with visualization tools like TissUUmaps and QuPath.
  • Enables direct export of cell coordinates for downstream applications like laser microdissection.

Conclusions:

  • PIPΣX significantly lowers the barrier to entry for spatial proteomics data analysis.
  • The software enhances the ability of researchers to extract meaningful biological insights from complex imaging datasets.
  • Facilitates precise isolation of specific cell populations for further molecular profiling.