MigraR: An open-source, R-based application for analysis and quantification of cell migration parameters. (January 2022)

• Record Type: Journal Article
• Authors: Shaji, Nirbhaya; Nunes, Florbela; Ines Rocha, M.; Gomes, Elsa Ferreira; Castro, Helena
• Is Part Of: Computer methods and programs in biomedicine. Volume 213(2022)
• Publication Date: 2022-01
• Subjects: Shiny application -- Cell-tracking software -- Visualization -- R language; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2021.106529
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: An intuitive graphical user interface. Greatly simplifies the task of translating coordinate positions of moving cells into measurable parameters of cell migration (velocity, straightness, and direction of movement). Plots cell trajectories and migration metrics. Allows users to refine their data sets, both by limiting the scope of the data range to specific limits of time, velocity, and straightness. The source code is open and can be refined by expert users to best suit the needs of other researchers. Abstract: Background and objective: Cell migration is essential for many biological phenomena with direct impact on human health and disease. One conventional approach to study cell migration involves the quantitative analysis of individual cell trajectories recorded by time-lapse video microscopy. Dedicated software tools exist to assist the automated or semi-automated tracking of cells and translate these into coordinate positions along time. However, cell biologists usually bump into the difficulty of plotting and computing these data sets into biologically meaningful figures and metrics. Methods: This report describes MigraR, an intuitive graphical user interface executed from the RStudio TM (via the R package Shiny), which greatly simplifies the task of translating coordinate positions of moving cells into measurable parameters of cell migration (velocity, straightness, and direction of movement), as well as of plotting cell trajectories and migration metrics. One innovative function of this interface is that it allows users to refine their data sets by setting limits based on time, velocity and straightness. Results: MigraR was tested on different data to assess its applicability. Intended users of MigraR are cell biologists with no prior knowledge of data analysis, seeking to accelerate the quantification and visualization of cell migration data sets delivered in the format of Excel files by available cell-tracking software. Conclusions: Through the graphics it provides, MigraR is an useful tool for the analysis of migration parameters and cellular trajectories. Since its source code is open, it can be subject of refinement by expert users to best suit the needs of other researchers. It is available at GitHub and can be easily reproduced.