recipe bioconductor-m3c

Monte Carlo Reference-based Consensus Clustering






M3C is a consensus clustering algorithm that uses a Monte Carlo simulation to eliminate overestimation of K and can reject the null hypothesis K=1.

package bioconductor-m3c

(downloads) docker_bioconductor-m3c



depends r-base:


depends r-cluster:

depends r-corpcor:

depends r-doparallel:

depends r-dosnow:

depends r-foreach:

depends r-ggplot2:

depends r-matrix:

depends r-matrixcalc:

depends r-rtsne:

depends r-umap:



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-m3c

and update with::

   mamba update bioconductor-m3c

To create a new environment, run:

mamba create --name myenvname bioconductor-m3c

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-m3c/tags`_ for valid values for ``<tag>``)

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