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MosaicIA: an ImageJ/Fiji plugin for spatial pattern and interaction analysis.

Arun Shivanandan1, Aleksandra Radenovic, Ivo F Sbalzarini

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Summary

This study introduces a new ImageJ/Fiji plugin for spatial interaction analysis, simplifying the study of object arrangements in biological images and revealing potential interactions.

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Area of Science:

  • Biological imaging
  • Quantitative biology
  • Spatial statistics

Background:

  • Analyzing spatial distributions of objects in images is crucial for understanding biological interactions.
  • Spatial correlations in object distributions can indicate interactions, extending co-localization analysis.
  • User-friendly software for spatial interaction analysis was previously lacking.

Purpose of the Study:

  • To develop and present a user-friendly ImageJ/Fiji plugin for comprehensive spatial pattern and interaction analysis.
  • To enable the generalization of co-localization analysis to spatial interaction analysis.
  • To provide tools for inferring interaction potentials and assessing their statistical significance.

Main Methods:

  • Development of an ImageJ/Fiji plugin for automated object detection and spatial analysis.
  • Implementation of algorithms to infer interaction potentials between sets of objects.
  • Integration of statistical tests to evaluate the significance of observed spatial interactions.

Main Results:

  • The plugin successfully detects spot-like objects and analyzes their spatial patterns.
  • It infers interaction potentials that explain observed spatial arrangements.
  • Statistical tests validate the significance of inferred interactions, demonstrated with microscopy data.

Conclusions:

  • The new plugin significantly simplifies spatial interaction analysis for point patterns.
  • It makes advanced spatial analysis accessible to the broad ImageJ and Fiji user community.
  • Demonstrations confirm the software's utility in biological imaging studies.