recipe bioconductor-awfisher

An R package for fast computing for adaptively weighted fisher's method






Implementation of the adaptively weighted fisher's method, including fast p-value computing, variability index, and meta-pattern.

package bioconductor-awfisher

(downloads) docker_bioconductor-awfisher



depends bioconductor-edger:


depends bioconductor-edger:


depends bioconductor-limma:


depends bioconductor-limma:


depends libblas:


depends libgcc-ng:


depends liblapack:


depends libstdcxx-ng:


depends r-base:




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-awfisher

and update with::

   mamba update bioconductor-awfisher

To create a new environment, run:

mamba create --name myenvname bioconductor-awfisher

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

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