Polarity-JaM: an image analysis toolbox for cell polarity, junction and morphology quantification

Area of Science:

• Cell Biology
• Bioimage Analysis
• Computational Biology

Background:

• Cell polarity, the asymmetric distribution of cellular components, is crucial for cell function and development.
• Advanced microscopy and deep learning generate complex image data, necessitating sophisticated analysis tools.
• Existing workflows struggle to provide comprehensible and interpretable analysis for cell polarity studies.

Purpose of the Study:

• To introduce Polarity-JaM, an open-source software package for reproducible exploratory image analysis of cell polarity.
• To provide versatile methods for single-cell segmentation, feature extraction, and statistical analysis.
• To enable accessible and comprehensive image data analysis for bench scientists.

Main Methods:

• Development of an open-source software package, Polarity-JaM.
• Implementation of single-cell segmentation, feature extraction, and statistical analysis methods.
• Creation of a web application and Napari plug-in with graphical user interfaces.

Main Results:

• Demonstration of Polarity-JaM using fluorescence image data of endothelial cells and their collective behavior.
• Successful application of the software to analyze cell polarity in vascular development and disease contexts.
• Validation of the software's general architecture for diverse cell types and imaging modalities.

Conclusions:

• Polarity-JaM provides a holistic and accessible image analysis workflow for cell polarity research.
• The software facilitates reproducible exploratory analysis, bridging the gap between complex data and bench science.
• Polarity-JaM enhances the exploitation of advanced imaging and deep learning for cell polarity studies.