recipe bioconductor-immunoclust

immunoClust - Automated Pipeline for Population Detection in Flow Cytometry






immunoClust is a model based clustering approach for Flow Cytometry samples. The cell-events of single Flow Cytometry samples are modelled by a mixture of multinominal normal- or t-distributions. The cell-event clusters of several samples are modelled by a mixture of multinominal normal-distributions aiming stable co-clusters across these samples.

package bioconductor-immunoclust

(downloads) docker_bioconductor-immunoclust



depends bioconductor-flowcore:


depends bioconductor-flowcore:


depends gsl:


depends libblas:


depends libgcc-ng:


depends liblapack:


depends libstdcxx-ng:


depends r-base:


depends r-lattice:



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-immunoclust

and update with::

   mamba update bioconductor-immunoclust

To create a new environment, run:

mamba create --name myenvname bioconductor-immunoclust

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

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