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VisuStatR: visualizing motility and morphology statistics on images in R

Live-cell microscopy has become an essential tool for analyzing dynamic processes in various biological applications. Thereby, high-throughput and automated tracking analyses allow the simultaneous evaluation of large numbers of objects. However, to critically assess the influence of individual obje...

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Hauptverfasser: Harmel, Christoph (VerfasserIn) , Sid Ahmed, Samy (VerfasserIn) , Koch, Robin (VerfasserIn) , Tünnermann, Jana (VerfasserIn) , Distler, Tania (VerfasserIn) , Imle, Andrea (VerfasserIn) , Giorgetti, Luca (VerfasserIn) , Bahn, Emanuel (VerfasserIn) , Fackler, Oliver Till (VerfasserIn) , Graw, Frederik (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: May 2022
In: Bioinformatics
Year: 2022, Jahrgang: 38, Heft: 10, Pages: 2970-2972
ISSN:1367-4811
DOI:10.1093/bioinformatics/btac191
Online-Zugang:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1093/bioinformatics/btac191
Verlag, lizenzpflichtig, Volltext: https://academic.oup.com/bioinformatics/article/38/10/2970/6571805
Volltext
Verfasserangaben:Christoph Harmel, Samy Sid Ahmed, Robin Koch, Jana Tünnermann, Tania Distler, Andrea Imle, Luca Giorgetti, Emanuel Bahn, Oliver T Fackler and Frederik Graw
Beschreibung
Zusammenfassung:Live-cell microscopy has become an essential tool for analyzing dynamic processes in various biological applications. Thereby, high-throughput and automated tracking analyses allow the simultaneous evaluation of large numbers of objects. However, to critically assess the influence of individual objects on calculated summary statistics, and to detect heterogeneous dynamics or possible artifacts, such as misclassified or -tracked objects, a direct mapping of gained statistical information onto the actual image data would be necessary.We present VisuStatR as a platform independent software package that allows the direct visualization of time-resolved summary statistics of morphological characteristics or motility dynamics onto raw images. The software contains several display modes to compare user-defined summary statistics and the underlying image data in various levels of detail.VisuStatR is a free and open-source R-package, containing a user-friendly graphical-user interface and is available via GitHub at https://github.com/grrchrr/VisuStatR/ under the MIT+ license.Supplementary data are available at Bioinformatics online.
Beschreibung:Online veröffentlicht am 21. April 2022
Gesehen am 07.12.2023
Beschreibung:Online Resource
ISSN:1367-4811
DOI:10.1093/bioinformatics/btac191

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