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Track Cells, Analyze Cell Trajectories and Compute Migration Statistics

Bioconductor version: Release (3.18)

Import TIFF images of fluorescently labeled cells, and track cell movements over time. Parallelization is supported for image processing and for fast computation of cell trajectories. In-depth analysis of cell trajectories is enabled by 15 trajectory analysis functions.

Author: Salim Ghannoum [aut, cph], Damiano Fantini [aut, cph], Waldir Leoncio [cre, aut], Øystein Sørensen [aut]

Maintainer: Waldir Leoncio <w.l.netto at>

Citation (from within R, enter citation("cellmigRation")):


To install this package, start R (version "4.3") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

cellmigRation HTML R Script
Reference Manual PDF


biocViews CellBiology, DataImport, DataRepresentation, Software
Version 1.10.0
In Bioconductor since BioC 3.13 (R-4.1) (3 years)
License GPL-2
Depends R (>= 4.1), methods, foreach
Imports tiff, graphics, stats, utils, reshape2, parallel, doParallel, grDevices, matrixStats, FME, SpatialTools, sp, vioplot, FactoMineR, Hmisc
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Suggests knitr, rmarkdown, dplyr, ggplot2, RUnit, BiocGenerics, BiocManager, kableExtra, rgl
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Follow Installation instructions to use this package in your R session.

Source Package cellmigRation_1.10.0.tar.gz
Windows Binary (64-bit only)
macOS Binary (x86_64) cellmigRation_1.10.0.tgz
macOS Binary (arm64) cellmigRation_1.10.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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