recipe bioconductor-cadra

Candidate Driver Analysis



GPL-3 + file LICENSE



Performs both stepwise and backward heuristic search for candidate (epi)genetic drivers based on a binary multi-omics dataset. CaDrA's main objective is to identify features which, together, are significantly skewed or enriched pertaining to a given vector of continuous scores (e.g. sample-specific scores representing a phenotypic readout of interest, such as protein expression, pathway activity, etc.), based on the union occurence (i.e. logical OR) of the events.

package bioconductor-cadra

(downloads) docker_bioconductor-cadra



depends bioconductor-summarizedexperiment:


depends bioconductor-summarizedexperiment:


depends libblas:


depends libgcc-ng:


depends liblapack:


depends r-base:


depends r-doparallel:

depends r-ggplot2:

depends r-gplots:

depends r-gtable:

depends r-mass:

depends r-misc3d:

depends r-plyr:

depends r-ppcor:

depends r-r.cache:

depends r-reshape2:



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-cadra

and update with::

   mamba update bioconductor-cadra

To create a new environment, run:

mamba create --name myenvname bioconductor-cadra

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

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