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flowcatchR

Tools to analyze in vivo microscopy imaging data focused on tracking flowing blood cells

Bioconductor version: 3.23 · Package version: 1.46.0

flowcatchR is a set of tools to analyze in vivo microscopy imaging data, focused on tracking flowing blood cells. It guides the steps from segmentation to calculation of features, filtering out particles not of interest, providing also a set of utilities to help checking the quality of the performed operations (e.g. how good the segmentation was). It allows investigating the issue of tracking flowing cells such as in blood vessels, to categorize the particles in flowing, rolling and adherent. This classification is applied in the study of phenomena such as hemostasis and study of thrombosis development. Moreover, flowcatchR presents an integrated workflow solution, based on the integration with a Shiny App and Jupyter notebooks, which is delivered alongside the package, and can enable fully reproducible bioimage analysis in the R environment.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("flowcatchR")

Details

MaintainerFederico Marini <marinif@uni-mainz.de>
AuthorFederico Marini [aut, cre] (ORCID: <https://orcid.org/0000-0003-3252-7758>)
LicenseBSD_3_clause + file LICENSE
URLhttps://github.com/federicomarini/flowcatchR, https://federicomarini.github.io/flowcatchR/
Bug Reportshttps://github.com/federicomarini/flowcatchR/issues
System RequirementsImageMagick
Downloads rank401
Source branchRELEASE_3_23
biocViewsCellBiology, Classification, GUI, Infrastructure, ShinyApps, Software, Visualization

Documentation

Download

Dependencies

Depends: R (>= 2.10), methods, EBImage

Imports: colorRamps, abind, BiocParallel, graphics, stats, utils, plotly, shiny

Suggests: BiocStyle, knitr, rmarkdown