Journal
NATURE METHODS
Volume 12, Issue 11, Pages 1065-1071Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/NMETH.3579
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Funding
- Ministere de l'Enseignement Superieur et de la Recherche (ANR NanoDom, Labex BRAIN) [ANR-10-INBS-04]
- European Research Council (ERC)
- Centre National de la Recherche Scientifique
- Conseil Regional d'Aquitaine
- Institut National de la Sante et de la Recherche Medicale
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Localization-based super-resolution techniques open the door to unprecedented analysis of molecular organization. This task often involves complex image processing adapted to the specific topology and quality of the image to be analyzed. Here we present a segmentation framework based on Voronoi tessellation constructed from the coordinates of localized molecules, implemented in freely available and open-source SR-Tesseler software. This method allows precise, robust and automatic quantification of protein organization at different scales, from the cellular level down to clusters of a few fluorescent markers. We validated our method on simulated data and on various biological experimental data of proteins labeled with genetically encoded fluorescent proteins or organic fluorophores. In addition to providing insight into complex protein organization, this polygon-based method should serve as a reference for the development of new types of quantifications, as well as for the optimization of existing ones.
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