recipe bioconductor-flowmap

Mapping cell populations in flow cytometry data for cross-sample comparisons using the Friedman-Rafsky Test



GPL (>=2)




biotools: flowmap, doi: 10.1002/cyto.a.22735

flowMap quantifies the similarity of cell populations across multiple flow cytometry samples using a nonparametric multivariate statistical test. The method is able to map cell populations of different size, shape, and proportion across multiple flow cytometry samples. The algorithm can be incorporate in any flow cytometry work flow that requires accurat quantification of similarity between cell populations.

package bioconductor-flowmap

(downloads) docker_bioconductor-flowmap



depends r-abind:


depends r-ade4:


depends r-base:


depends r-doparallel:


depends r-matrix:


depends r-reshape2:


depends r-scales:




You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

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-flowmap

and update with::

   mamba update bioconductor-flowmap

To create a new environment, run:

mamba create --name myenvname bioconductor-flowmap

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull<tag>

(see `bioconductor-flowmap/tags`_ for valid values for ``<tag>``)

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