recipe r-mgsz

Performs gene set analysis based on GSZ scoring function and asymptotic p-value. It is different from GSZ in that it implements asymptotic p-values instead of empirical p-values. Asymptotic p-values are calculated by fitting suitable distribution model to the null distribution. Unlike empirical p-values, resolution of asymptotic p-values are independent of the number of permutations and hence requires considerably fewer permutations. In addition, this package allows gene set analysis with seven other popular gene set analysis methods.

Homepage:

https://CRAN.R-project.org/package=mGSZ

License:

GPL3 / GPL (>= 2)

Recipe:

/r-mgsz/meta.yaml

package r-mgsz

(downloads) docker_r-mgsz

versions:

1.0-5,  1.0-4,  1.0-3,  1.0-2,  1.0-1,  1.0-0

depends bioconductor-biobase:

depends bioconductor-limma:

depends r-base:

>=4.3,<4.4.0a0

depends r-gsa:

depends r-ismev:

depends r-mass:

requirements:

Installation

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 r-mgsz

and update with::

   mamba update r-mgsz

To create a new environment, run:

mamba create --name myenvname r-mgsz

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 quay.io/biocontainers/r-mgsz:<tag>

(see `r-mgsz/tags`_ for valid values for ``<tag>``)

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Link to this page

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