ColiCoords: A Python package for the analysis of bacterial fluorescence microscopy data

dc.bibliographicCitation.firstPagee0217524eng
dc.bibliographicCitation.issue6eng
dc.bibliographicCitation.journalTitlePLOS ONEeng
dc.bibliographicCitation.volume14eng
dc.contributor.authorSmit, Jochem H.
dc.contributor.authorLi, Yichen
dc.contributor.authorWarszawik, Eliza M.
dc.contributor.authorHerrmann, Andreas
dc.contributor.authorCordes, Thorben
dc.contributor.editorGilestro, Giorgio F
dc.date.accessioned2022-04-12T05:10:16Z
dc.date.available2022-04-12T05:10:16Z
dc.date.issued2019
dc.description.abstractSingle-molecule fluorescence microscopy studies of bacteria provide unique insights into the mechanisms of cellular processes and protein machineries in ways that are unrivalled by any other technique. With the cost of microscopes dropping and the availability of fully automated microscopes, the volume of microscopy data produced has increased tremendously. These developments have moved the bottleneck of throughput from image acquisition and sample preparation to data analysis. Furthermore, requirements for analysis procedures have become more stringent given the demand of various journals to make data and analysis procedures available. To address these issues we have developed a new data analysis package for analysis of fluorescence microscopy data from rod-like cells. Our software ColiCoords structures microscopy data at the single-cell level and implements a coordinate system describing each cell. This allows for the transformation of Cartesian coordinates from transmission light and fluorescence images and single-molecule localization microscopy (SMLM) data to cellular coordinates. Using this transformation, many cells can be combined to increase the statistical power of fluorescence microscopy datasets of any kind. ColiCoords is open source, implemented in the programming language Python, and is extensively documented. This allows for modifications for specific needs or to inspect and publish data analysis procedures. By providing a format that allows for easy sharing of code and associated data, we intend to promote open and reproducible research. The source code and documentation can be found via the project’s GitHub page.eng
dc.description.versionpublishedVersioneng
dc.identifier.urihttps://oa.tib.eu/renate/handle/123456789/8632
dc.identifier.urihttps://doi.org/10.34657/7670
dc.language.isoengeng
dc.publisherSan Francisco, California, US : PLOSeng
dc.relation.doihttps://doi.org/10.1371/journal.pone.0217524
dc.relation.essn1932-6203
dc.rights.licenseCC BY 4.0 Unportedeng
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/eng
dc.subject.ddc500eng
dc.subject.ddc610eng
dc.subject.otherarticleeng
dc.subject.othercell leveleng
dc.subject.othercomputer languageeng
dc.subject.otherdata analysiseng
dc.subject.otherdocumentationeng
dc.subject.otherfluorescence microscopyeng
dc.subject.otherhumaneng
dc.subject.otherhuman experimenteng
dc.subject.othersoftwareeng
dc.subject.otherbacteriumeng
dc.subject.othercomputer languageeng
dc.subject.othercytologyeng
dc.subject.otherfluorescence microscopyeng
dc.subject.otherimage processingeng
dc.subject.otherBacteriaeng
dc.subject.otherImage Processing, Computer-Assistedeng
dc.subject.otherMicroscopy, Fluorescenceeng
dc.subject.otherProgramming Languageseng
dc.titleColiCoords: A Python package for the analysis of bacterial fluorescence microscopy dataeng
dc.typeArticleeng
dc.typeTexteng
tib.accessRightsopenAccesseng
wgl.contributorDWIeng
wgl.subjectMedizin, Gesundheiteng
wgl.typeZeitschriftenartikeleng
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