recipe bioconductor-gage

Generally Applicable Gene-set Enrichment for Pathway Analysis

Homepage:

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

License:

GPL (>=2.0)

Recipe:

/bioconductor-gage/meta.yaml

Links:

biotools: gage

GAGE is a published method for gene set (enrichment or GSEA) or pathway analysis. GAGE is generally applicable independent of microarray or RNA-Seq data attributes including sample sizes, experimental designs, assay platforms, and other types of heterogeneity, and consistently achieves superior performance over other frequently used methods. In gage package, we provide functions for basic GAGE analysis, result processing and presentation. We have also built pipeline routines for of multiple GAGE analyses in a batch, comparison between parallel analyses, and combined analysis of heterogeneous data from different sources/studies. In addition, we provide demo microarray data and commonly used gene set data based on KEGG pathways and GO terms. These funtions and data are also useful for gene set analysis using other methods.

package bioconductor-gage

versions:

2.52.0-0,  2.50.0-0,  2.48.0-0,  2.44.0-0,  2.42.0-0,  2.40.1-0,  2.40.0-0,  2.37.0-0,  2.36.0-0, 

2.52.0-0,  2.50.0-0,  2.48.0-0,  2.44.0-0,  2.42.0-0,  2.40.1-0,  2.40.0-0,  2.37.0-0,  2.36.0-0,  2.34.0-1,  2.32.0-0,  2.30.0-0,  2.28.0-0,  2.26.3-0,  2.21.1-0

depends bioconductor-annotationdbi:

>=1.64.0,<1.65.0

depends bioconductor-go.db:

>=3.18.0,<3.19.0

depends bioconductor-graph:

>=1.80.0,<1.81.0

depends bioconductor-keggrest:

>=1.42.0,<1.43.0

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-gage

and update with::

   mamba update bioconductor-gage

To create a new environment, run:

mamba create --name myenvname bioconductor-gage

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-gage:<tag>

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

Download stats

Link to this page

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