recipe bioconductor-mcbiclust

Massive correlating biclusters for gene expression data and associated methods






Custom made algorithm and associated methods for finding, visualising and analysing biclusters in large gene expression data sets. Algorithm is based on with a supplied gene set of size n, finding the maximum strength correlation matrix containing m samples from the data set.

package bioconductor-mcbiclust

(downloads) docker_bioconductor-mcbiclust



depends bioconductor-annotationdbi:


depends bioconductor-biocparallel:


depends bioconductor-go.db:




depends r-base:


depends r-cluster:

depends r-ggally:

depends r-ggplot2:

depends r-scales:

depends r-wgcna:



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-mcbiclust

and update with::

   mamba update bioconductor-mcbiclust

To create a new environment, run:

mamba create --name myenvname bioconductor-mcbiclust

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

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