VisuStatR: Visualizing motility and morphology statistics on images in R

Harmel C, Ahmed SS, Koch R, Tunnermann J, Distler T, Imle A, Giorgetti L, Bahn E, Fackler OT, Graw F (2022)

Publication Type: Journal article

Publication year: 2022

Journal

Bioinformatics Oxford University Press (OUP): Policy B - Oxford Open Option B

Book Volume: 38

Pages Range: 2970-2972

Journal Issue: 10

DOI: 10.1093/bioinformatics/btac191

Abstract

Motivation: 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. Results: 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.

Authors with CRIS profile

Frederik Graw

Involved external institutions

Ruprecht-Karls-Universität Heidelberg

Germany (DE) Universitätsklinikum Heidelberg

Germany (DE) Friedrich Miescher Institute for Biomedical Research (FMI)

Switzerland (CH)

How to cite

APA:

Harmel, C., Ahmed, S.S., Koch, R., Tunnermann, J., Distler, T., Imle, A.,... Graw, F. (2022). VisuStatR: Visualizing motility and morphology statistics on images in R. Bioinformatics, 38(10), 2970-2972. https://doi.org/10.1093/bioinformatics/btac191

MLA:

Harmel, Christoph, et al. "VisuStatR: Visualizing motility and morphology statistics on images in R." Bioinformatics 38.10 (2022): 2970-2972.

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