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

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.