recipe bioconductor-desousa2013

Poor prognosis colon cancer is defined by a molecularly distinct subtype and precursor lesion






This package reproduces the main pipeline to analyze the AMC-AJCCII-90 microarray data set in De Sousa et al. accepted by Nature Medicine in 2013.

package bioconductor-desousa2013

(downloads) docker_bioconductor-desousa2013



depends bioconductor-affy:


depends bioconductor-annotationdbi:


depends bioconductor-biobase:


depends bioconductor-consensusclusterplus:


depends bioconductor-data-packages:


depends bioconductor-frma:


depends bioconductor-frmatools:


depends bioconductor-hgu133plus2.db:


depends bioconductor-hgu133plus2frmavecs:


depends bioconductor-siggenes:


depends bioconductor-sva:


depends curl:

depends r-base:


depends r-cluster:

depends r-gplots:

depends r-pamr:

depends r-rgl:

depends r-rocr:

depends r-survival:



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-desousa2013

and update with::

   mamba update bioconductor-desousa2013

To create a new environment, run:

mamba create --name myenvname bioconductor-desousa2013

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-desousa2013/tags`_ for valid values for ``<tag>``)

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