ScatterJ: An ImageJ plugin for the evaluation of analytical microscopy datasets

Area of Science:

• Microscopy and Materials Science
• Biogeochemistry
• Data Analysis

Background:

• Analytical microscopy generates large, complex datasets with spatially resolved chemical information.
• Existing methods may not fully extract all available correlation and colocalization data.
• Understanding complex interactions in samples requires advanced data analysis tools.

Purpose of the Study:

• To introduce ScatterJ, an ImageJ plugin designed for extracting qualitative and quantitative information from analytical microscopy datasets.
• To enable the extraction of correlation and colocalization data from pairs of species- or element-specific maps.
• To demonstrate the utility of ScatterJ in advancing the understanding of biogeochemical processes.

Main Methods:

• Development of ScatterJ as an ImageJ plugin.
• Application of ScatterJ to analyze various 2D and 3D analytical microscopy datasets.
• Utilizing species-specific or element-specific maps for correlation and colocalization analysis.

Main Results:

• ScatterJ successfully extracts detailed correlation and colocalization information from complex microscopy datasets.
• The plugin facilitates the analysis of datasets from energy-dispersive X-ray spectroscopy, confocal laser scanning microscopy, and scanning transmission X-ray microscopy.
• Extracted information aided in a deeper understanding of biogeochemical processes like mineral formation and heavy metal sorption.

Conclusions:

• ScatterJ is a versatile tool for enhancing the analysis of analytical microscopy data.
• The plugin provides valuable insights into sample composition and interactions, applicable across various research fields.
• ScatterJ complements existing techniques, enabling more comprehensive data interpretation in scientific studies.