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

Arun Shivanandan23, Aleksandra Radenovic3 and Ivo F Sbalzarini12*

Author Affiliations

1 MOSAIC Group, Center of Systems Biology Dresden (CSBD), Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstr 108, 01307 Dresden, Germany

2 Previously: MOSAIC Group, Department of Computer Science, ETH Zurich, 8092 Zurich, Switzerland

3 Laboratory of Nanoscale Biology, Institute of Bioengineering, School of Engineering, EPFL, 1015 Lausanne, Switzerland

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BMC Bioinformatics 2013, 14:349  doi:10.1186/1471-2105-14-349

Published: 3 December 2013

Abstract

Background

Analyzing spatial distributions of objects in images is a fundamental task in many biological studies. The relative arrangement of a set of objects with respect to another set of objects contains information about potential interactions between the two sets of objects. If they do not “feel” each other’s presence, their spatial distributions are expected to be independent of one another. Spatial correlations in their distributions are indicative of interactions and can be modeled by an effective interaction potential acting between the points of the two sets. This can be used to generalize co-localization analysis to spatial interaction analysis. However, no user-friendly software for this type of analysis was available so far.

Results

We present an ImageJ/Fiji plugin that implements the complete workflow of spatial pattern and interaction analysis for spot-like objects. The plugin detects objects in images, infers the interaction potential that is most likely to explain the observed pattern, and provides statistical tests for whether an inferred interaction is significant given the number of objects detected in the images and the size of the space within which they can distribute. We benchmark and demonstrate the present software using examples from confocal and PALM single-molecule microscopy.

Conclusions

The present software greatly simplifies spatial interaction analysis for point patterns, and makes it available to the large user community of ImageJ and Fiji. The presented showcases illustrate the usage of the software.

Keywords:
Spatial pattern analysis; Microscopy; Co-localization analysis; Interaction analysis; PALM; ImageJ; Fiji; Image analysis