recipe bioconductor-consensusov

Gene expression-based subtype classification for high-grade serous ovarian cancer






This package implements four major subtype classifiers for high-grade serous (HGS) ovarian cancer as described by Helland et al. (PLoS One, 2011), Bentink et al. (PLoS One, 2012), Verhaak et al. (J Clin Invest, 2013), and Konecny et al. (J Natl Cancer Inst, 2014). In addition, the package implements a consensus classifier, which consolidates and improves on the robustness of the proposed subtype classifiers, thereby providing reliable stratification of patients with HGS ovarian tumors of clearly defined subtype.

package bioconductor-consensusov

(downloads) docker_bioconductor-consensusov



depends bioconductor-biobase:


depends bioconductor-genefu:


depends bioconductor-gsva:


depends bioconductor-limma:


depends r-base:


depends r-gdata:

depends r-matrixstats:

depends r-randomforest:



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-consensusov

and update with::

   mamba update bioconductor-consensusov

To create a new environment, run:

mamba create --name myenvname bioconductor-consensusov

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

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