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dc.rights.licenseopenen_US
dc.contributor.authorAMBROSET, Melodie
hal.structure.identifierInstitut de Neurosciences cognitives et intégratives d'Aquitaine [INCIA]
dc.contributor.authorBONTEMPI, Bruno
IDREF: 119124459
hal.structure.identifierInstitut de Neurosciences cognitives et intégratives d'Aquitaine [INCIA]
dc.contributor.authorMOREL, Jean-Luc
dc.date.accessioned2024-11-04T11:07:34Z
dc.date.available2024-11-04T11:07:34Z
dc.date.issued2024-01-03
dc.identifier.issn2046-1402en_US
dc.identifier.otherhttps://doi.org/10.5281/zenodo.10205178en_US
dc.identifier.urioai:crossref.org:10.12688/f1000research.143062.1
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/203113
dc.description.abstractEnWith the increasing complexity and throughput of microscopy experiments, it has become essential for biologists to navigate computational means of analysis to produce automated and reproducible workflows. Bioimage analysis workflows being largely underreported in method sections of articles, it is however quite difficult to find practical examples of documented scripts to support beginner programmers in biology. Here, we introduce COverlap, a Fiji toolset composed of four macros, for the 3D segmentation and colocalization of fluorescent nuclear markers in confocal images. The toolset accepts batches of multichannel z-stack images, segments objects in two channels of interest, and outputs object counts and labels, as well as co-localization results based on the physical overlap of objects. The first macro is a preparatory step that produces maximum intensity projections of images for visualization purposes. The second macro assists users in selecting batch-suitable segmentation parameters by testing them on small portions of the images. The third macro performs automated segmentation and colocalization analysis, and saves the parameters used, the results table, the 3D regions of interest (ROIs) of co-localizing objects, and two types of verification images with segmentation and co-localization masks for each image of the batch. The fourth macro allows users to review the verification images displaying segmentation masks and the location of co-localization events, and to perform corrections such as ROI adjustment, z-stack reslicing, and volume estimation correction in an automatically documented manner. To illustrate how COverlap operates, we present an experiment in which we identified rare endothelial proliferation events in adult rat brain slices on more than 350 large tiled z-stacks. We conclude by discussing the reproducibility and generalizability of the toolset, its limitations for different datasets, and its potential use as a template that is adaptable to other types of analyses.
dc.description.sponsorshipDynamiques des interactions hippocampo-corticales au cours de la formation des souvenirs récents et anciens: bases comportementales, cellulaires, moléculaires et fonctionnelles - ANR-14-CE13-0017en_US
dc.description.sponsorshipUniversity of Bordeaux Neurocampus Graduate School - ANR-17-EURE-0028en_US
dc.language.isoENen_US
dc.rightsAttribution 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.sourcecrossref
dc.subject.en3D segmentation
dc.subject.enCo-localization
dc.subject.enConfocal microscopy
dc.subject.enAngiogenesis
dc.subject.enBioimage analysis
dc.subject.enEndothelial cell proliferation
dc.subject.enImageJ
dc.subject.enFiji toolset
dc.title.enCOverlap: a Fiji toolset for the 3D co-localization of two fluorescent nuclear markers in confocal images
dc.title.alternativeF1000Resen_US
dc.typeArticle de revueen_US
dc.identifier.doi10.12688/f1000research.143062.1en_US
dc.subject.halSciences du Vivant [q-bio]/Neurosciences [q-bio.NC]en_US
bordeaux.journalF1000Researchen_US
bordeaux.hal.laboratoriesInstitut de neurosciences cognitives et intégratives d'Aquitaine (INCIA) - UMR 5287en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionCNRSen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
bordeaux.identifier.funderIDCentre National d’Etudes Spatialesen_US
bordeaux.import.sourcedissemin
hal.identifierhal-04764991
hal.version1
hal.date.transferred2024-11-04T11:07:37Z
hal.popularnonen_US
hal.audienceInternationaleen_US
hal.exporttrue
workflow.import.sourcedissemin
dc.rights.ccCC BYen_US
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=F1000Research&rft.date=2024-01-03&rft.eissn=2046-1402&rft.issn=2046-1402&rft.au=AMBROSET,%20Melodie&BONTEMPI,%20Bruno&MOREL,%20Jean-Luc&rft.genre=article


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