CelltrackR: An R package for fast and flexible analysis of immune cell migration data

• Published in: ImmunoInformatics Vol. 1-2; p. 100003
• Main Authors: Wortel, Inge M.N., Liu, Annie Y., Dannenberg, Katharina, Berry, Jeffrey C., Miller, Mark J., Textor, Johannes
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.10.2021
• Subjects: Cell track analysis; Immune cell migration; Modeling; Motion statistics; Two-photon imaging; Immune cell migration; Cell track analysis; Modeling; Two-photon imaging; Motion statistics
• ISSN: 2667-1190; 2667-1190
• DOI: 10.1016/j.immuno.2021.100003

[Display omitted] Visualization of cell migration via time-lapse microscopy has greatly advanced our understanding of the immune system. However, subtle differences in migration dynamics are easily obscured by biases and imaging artifacts. While several analysis methods have been suggested to address these issues, an integrated tool implementing them is currently lacking. Here, we present celltrackR, an R package containing a diverse set of state-of-the-art analysis methods for (immune) cell tracks. CelltrackR supports the complete pipeline for track analysis by providing methods for data management, quality control, extracting and visualizing migration statistics, clustering tracks, and simulating cell migration. CelltrackR supports the analysis of both 2D and 3D cell tracks. CelltrackR is an open-source package released under the GPL-2 license, and is freely available on both GitHub and CRAN. Although the package was designed specifically for immune cell migration data, many of its methods will also be of use in other research areas dealing with moving objects.