recipe bioconductor-gseabenchmarker

Reproducible GSEA Benchmarking

Homepage:

https://bioconductor.org/packages/3.18/bioc/html/GSEABenchmarkeR.html

License:

Artistic-2.0

Recipe:

/bioconductor-gseabenchmarker/meta.yaml

The GSEABenchmarkeR package implements an extendable framework for reproducible evaluation of set- and network-based methods for enrichment analysis of gene expression data. This includes support for the efficient execution of these methods on comprehensive real data compendia (microarray and RNA-seq) using parallel computation on standard workstations and institutional computer grids. Methods can then be assessed with respect to runtime, statistical significance, and relevance of the results for the phenotypes investigated.

package bioconductor-gseabenchmarker

versions:

1.22.0-0,  1.20.0-0,  1.18.0-0,  1.14.0-0,  1.12.0-0,  1.10.1-0,  1.10.0-0,  1.8.0-0,  1.6.0-1, 

1.22.0-0,  1.20.0-0,  1.18.0-0,  1.14.0-0,  1.12.0-0,  1.10.1-0,  1.10.0-0,  1.8.0-0,  1.6.0-1,  1.4.0-1,  1.2.0-0

depends bioconductor-annotationdbi:

>=1.64.0,<1.65.0

depends bioconductor-annotationhub:

>=3.10.0,<3.11.0

depends bioconductor-biobase:

>=2.62.0,<2.63.0

depends bioconductor-biocfilecache:

>=2.10.0,<2.11.0

depends bioconductor-biocparallel:

>=1.36.0,<1.37.0

depends bioconductor-edger:

>=4.0.0,<4.1.0

depends bioconductor-enrichmentbrowser:

>=2.32.0,<2.33.0

depends bioconductor-experimenthub:

>=2.10.0,<2.11.0

depends bioconductor-keggandmetacoredzpathwaysgeo:

>=1.22.0,<1.23.0

depends bioconductor-keggdzpathwaysgeo:

>=1.40.0,<1.41.0

depends bioconductor-s4vectors:

>=0.40.0,<0.41.0

depends bioconductor-summarizedexperiment:

>=1.32.0,<1.33.0

depends r-base:

>=4.3,<4.4.0a0

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 bioconductor-gseabenchmarker

and update with::

   mamba update bioconductor-gseabenchmarker

To create a new environment, run:

mamba create --name myenvname bioconductor-gseabenchmarker

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/bioconductor-gseabenchmarker:<tag>

(see `bioconductor-gseabenchmarker/tags`_ for valid values for ``<tag>``)

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