Package: flowcatchR
Type: Package
Title: Tools to analyze in vivo microscopy imaging data focused on
        tracking flowing blood cells
Version: 1.14.0
Date: 2018-03-02
Authors@R: person("Federico", "Marini", email = "marinif@uni-mainz.de",
    role = c("aut", "cre"))
Maintainer: Federico Marini <marinif@uni-mainz.de>
Description: 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. 
License: BSD_3_clause + file LICENSE
VignetteBuilder: knitr
Suggests: BiocStyle, knitr, rmarkdown
Depends: R (>= 2.10), methods, EBImage
Imports: colorRamps, abind, BiocParallel, graphics, stats, utils,
        plotly, shiny
SystemRequirements: ImageMagick
LazyData: true
URL: https://github.com/federicomarini/flowcatchR
BugReports: https://github.com/federicomarini/flowcatchR/issues
biocViews: Software, Visualization, CellBiology, Classification,
        Infrastructure, GUI
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-05-01 02:43:06 UTC; biocbuild
Author: Federico Marini [aut, cre]
Built: R 3.5.0; ; 2018-05-01 12:01:35 UTC; windows
