Journal Article DKFZ-2022-00782

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VisuStatR-Visualizing Motility and Morphology Statistics on Images in R.

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2022
Oxford Univ. Press Oxford

Bioinformatics 38(10), 2970-2972 () [10.1093/bioinformatics/btac191]
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Abstract: 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.Examples and additional information are available online and on the project's webpage.

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Note: Bioinformatics, 38(10), pp. 2970-2972, 2022

Contributing Institute(s):
  1. E050 KKE Strahlentherapie (E050)
Research Program(s):
  1. 315 - Bildgebung und Radioonkologie (POF4-315) (POF4-315)

Appears in the scientific report 2022
Database coverage:
Medline ; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; Current Contents - Life Sciences ; Ebsco Academic Search ; Essential Science Indicators ; IF >= 5 ; JCR ; NationallizenzNationallizenz ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection
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 Record created 2022-04-22, last modified 2024-02-29



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