Cargando…

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

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 “fe...

Descripción completa

Detalles Bibliográficos
Autores principales: Shivanandan, Arun, Radenovic, Aleksandra, Sbalzarini, Ivo F
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4219334/
https://www.ncbi.nlm.nih.gov/pubmed/24299066
http://dx.doi.org/10.1186/1471-2105-14-349
_version_ 1782342567297286144
author Shivanandan, Arun
Radenovic, Aleksandra
Sbalzarini, Ivo F
author_facet Shivanandan, Arun
Radenovic, Aleksandra
Sbalzarini, Ivo F
author_sort Shivanandan, Arun
collection PubMed
description 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.
format Online
Article
Text
id pubmed-4219334
institution National Center for Biotechnology Information
language English
publishDate 2013
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-42193342014-11-07 MosaicIA: an ImageJ/Fiji plugin for spatial pattern and interaction analysis Shivanandan, Arun Radenovic, Aleksandra Sbalzarini, Ivo F BMC Bioinformatics Software 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. BioMed Central 2013-12-03 /pmc/articles/PMC4219334/ /pubmed/24299066 http://dx.doi.org/10.1186/1471-2105-14-349 Text en Copyright © 2013 Shivanandan et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License(http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software
Shivanandan, Arun
Radenovic, Aleksandra
Sbalzarini, Ivo F
MosaicIA: an ImageJ/Fiji plugin for spatial pattern and interaction analysis
title MosaicIA: an ImageJ/Fiji plugin for spatial pattern and interaction analysis
title_full MosaicIA: an ImageJ/Fiji plugin for spatial pattern and interaction analysis
title_fullStr MosaicIA: an ImageJ/Fiji plugin for spatial pattern and interaction analysis
title_full_unstemmed MosaicIA: an ImageJ/Fiji plugin for spatial pattern and interaction analysis
title_short MosaicIA: an ImageJ/Fiji plugin for spatial pattern and interaction analysis
title_sort mosaicia: an imagej/fiji plugin for spatial pattern and interaction analysis
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4219334/
https://www.ncbi.nlm.nih.gov/pubmed/24299066
http://dx.doi.org/10.1186/1471-2105-14-349
work_keys_str_mv AT shivanandanarun mosaiciaanimagejfijipluginforspatialpatternandinteractionanalysis
AT radenovicaleksandra mosaiciaanimagejfijipluginforspatialpatternandinteractionanalysis
AT sbalzariniivof mosaiciaanimagejfijipluginforspatialpatternandinteractionanalysis