recipe bioconductor-cytodx

Robust prediction of clinical outcomes using cytometry data without cell gating






This package provides functions that predict clinical outcomes using single cell data (such as flow cytometry data, RNA single cell sequencing data) without the requirement of cell gating or clustering.

package bioconductor-cytodx

(downloads) docker_bioconductor-cytodx



depends bioconductor-flowcore:


depends r-base:


depends r-doparallel:

depends r-dplyr:

depends r-glmnet:

depends r-rpart:

depends r-rpart.plot:



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-cytodx

and update with::

   mamba update bioconductor-cytodx

To create a new environment, run:

mamba create --name myenvname bioconductor-cytodx

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-cytodx/tags`_ for valid values for ``<tag>``)

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