- recipe bioconductor-flowcatchr
Tools to analyze in vivo microscopy imaging data focused on tracking flowing blood cells
BSD_3_clause + file LICENSE
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.
- package bioconductor-flowcatchr¶
- depends bioconductor-biocparallel:
- depends bioconductor-ebimage:
- depends imagemagick:
- depends r-abind:
- depends r-base:
- depends r-colorramps:
- depends r-plotly:
- depends r-shiny:
While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.
Given that you already have a conda environment in which you want to have this package, install with:
mamba install bioconductor-flowcatchr and update with:: mamba update bioconductor-flowcatchr
To create a new environment, run:
mamba create --name myenvname bioconductor-flowcatchr
myenvnamebeing a reasonable name for the environment (see e.g. the mamba docs for details and further options).
Alternatively, use the docker container:
docker pull quay.io/biocontainers/bioconductor-flowcatchr:<tag> (see `bioconductor-flowcatchr/tags`_ for valid values for ``<tag>``)