recipe bioconductor-drugvsdisease

Comparison of disease and drug profiles using Gene set Enrichment Analysis

Homepage:

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

License:

GPL-3

Recipe:

/bioconductor-drugvsdisease/meta.yaml

Links:

biotools: drugvsdisease, doi: 10.1038/nmeth.3252

This package generates ranked lists of differential gene expression for either disease or drug profiles. Input data can be downloaded from Array Express or GEO, or from local CEL files. Ranked lists of differential expression and associated p-values are calculated using Limma. Enrichment scores (Subramanian et al. PNAS 2005) are calculated to a reference set of default drug or disease profiles, or a set of custom data supplied by the user. Network visualisation of significant scores are output in Cytoscape format.

package bioconductor-drugvsdisease

versions:

2.44.0-0,  2.42.0-0,  2.40.0-0,  2.36.0-0,  2.34.0-0,  2.32.0-1,  2.32.0-0,  2.30.0-0,  2.28.0-1, 

2.44.0-0,  2.42.0-0,  2.40.0-0,  2.36.0-0,  2.34.0-0,  2.32.0-1,  2.32.0-0,  2.30.0-0,  2.28.0-1,  2.26.0-1,  2.24.2-0,  2.22.0-0,  2.20.1-0

depends bioconductor-affy:

>=1.80.0,<1.81.0

depends bioconductor-annotate:

>=1.80.0,<1.81.0

depends bioconductor-arrayexpress:

>=1.62.0,<1.63.0

depends bioconductor-biocgenerics:

>=0.48.0,<0.49.0

depends bioconductor-biomart:

>=2.58.0,<2.59.0

depends bioconductor-cmap2data:

>=1.38.0,<1.39.0

depends bioconductor-drugvsdiseasedata:

>=1.38.0,<1.39.0

depends bioconductor-geoquery:

>=2.70.0,<2.71.0

depends bioconductor-hgu133a.db:

>=3.13.0,<3.14.0

depends bioconductor-hgu133a2.db:

>=3.13.0,<3.14.0

depends bioconductor-hgu133plus2.db:

>=3.13.0,<3.14.0

depends bioconductor-limma:

>=3.58.0,<3.59.0

depends bioconductor-qvalue:

>=2.34.0,<2.35.0

depends r-base:

>=4.3,<4.4.0a0

depends r-runit:

depends r-xtable:

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-drugvsdisease

and update with::

   mamba update bioconductor-drugvsdisease

To create a new environment, run:

mamba create --name myenvname bioconductor-drugvsdisease

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-drugvsdisease:<tag>

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

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