ColocalizR: An open-source application for cell-based high-throughput colocalization analysis.
Cellular imaging
Co-distribution
Co-occurrence
Fluorescence microscopy
Systems biology
Journal
Computers in biology and medicine
ISSN: 1879-0534
Titre abrégé: Comput Biol Med
Pays: United States
ID NLM: 1250250
Informations de publication
Date de publication:
04 2019
04 2019
Historique:
received:
24
08
2018
revised:
20
02
2019
accepted:
26
02
2019
pubmed:
11
3
2019
medline:
25
6
2020
entrez:
11
3
2019
Statut:
ppublish
Résumé
The microscopic assessment of the colocalization of fluorescent signals has been widely used in cell biology. Although imaging techniques have drastically improved over the past decades, the quantification of colocalization by measures such as the Pearson correlation coefficient or Manders overlap coefficient, has not changed. Here, we report the development of an R-based application that allows to (i) automatically segment cells and subcellular compartments, (ii) measure morphology and texture features, and (iii) calculate the degree of colocalization within each cell. Colocalization can thus be studied on a cell-by-cell basis, permitting to perform statistical analyses of cellular populations and subpopulations. ColocalizR has been designed to parallelize tasks, making it applicable to the analysis of large data sets. Its graphical user interface makes it suitable for researchers without specific knowledge in image analysis. Moreover, results can be exported into a wide range of formats rendering post-analysis adaptable to statistical requirements. This application and its source code are freely available at https://github.com/kroemerlab/ColocalizR.
Identifiants
pubmed: 30852249
pii: S0010-4825(19)30071-X
doi: 10.1016/j.compbiomed.2019.02.024
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
227-234Informations de copyright
Copyright © 2019 Elsevier Ltd. All rights reserved.