Package Recipe 'bioconductor-rgreat'

recipe bioconductor-rgreat

GREAT Analysis - Functional Enrichment on Genomic Regions

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/rGREAT.html
License:: MIT + file LICENSE
Recipe:: /bioconductor-rgreat/meta.yaml
Links:: biotools: rgreat, doi: 10.1038/nmeth.3252

GREAT (Genomic Regions Enrichment of Annotations Tool) is a type of functional enrichment analysis directly performed on genomic regions. This package implements the GREAT algorithm (the local GREAT analysis), also it supports directly interacting with the GREAT web service (the online GREAT analysis). Both analysis can be viewed by a Shiny application. rGREAT by default supports more than 600 organisms and a large number of gene set collections, as well as self-provided gene sets and organisms from users. Additionally, it implements a general method for dealing with background regions.

package bioconductor-rgreat¶

Versions:

2.12.2-0, 2.8.0-0, 2.4.0-0, 2.2.0-0, 2.0.0-1, 2.0.0-0, 1.26.0-0, 1.24.0-0, 1.22.0-1,

2.12.2-0, 2.8.0-0, 2.4.0-0, 2.2.0-0, 2.0.0-1, 2.0.0-0, 1.26.0-0, 1.24.0-0, 1.22.0-1, 1.22.0-0, 1.20.0-0, 1.18.0-0, 1.16.0-1, 1.14.0-0, 1.12.1-0, 1.11.1-0, 1.8.0-0

Depends:

on bioconductor-annotationdbi >=1.72.0,<1.73.0
on bioconductor-annotationdbi >=1.72.0,<1.73.0a0
on bioconductor-genomeinfodb >=1.46.0,<1.47.0
on bioconductor-genomeinfodb >=1.46.2,<1.47.0a0
on bioconductor-genomicfeatures >=1.62.0,<1.63.0
on bioconductor-genomicfeatures >=1.62.0,<1.63.0a0
on bioconductor-genomicranges >=1.62.0,<1.63.0
on bioconductor-genomicranges >=1.62.1,<1.63.0a0
on bioconductor-go.db >=3.22.0,<3.23.0
on bioconductor-go.db >=3.22.0,<3.23.0a0
on bioconductor-iranges >=2.44.0,<2.45.0
on bioconductor-iranges >=2.44.0,<2.45.0a0
on bioconductor-org.hs.eg.db >=3.22.0,<3.23.0
on bioconductor-org.hs.eg.db >=3.22.0,<3.23.0a0
on bioconductor-s4vectors >=0.48.0,<0.49.0
on bioconductor-s4vectors >=0.48.0,<0.49.0a0
on bioconductor-txdb.hsapiens.ucsc.hg19.knowngene >=3.22.0,<3.23.0
on bioconductor-txdb.hsapiens.ucsc.hg19.knowngene >=3.22.1,<3.23.0a0
on bioconductor-txdb.hsapiens.ucsc.hg38.knowngene >=3.22.0,<3.23.0
on bioconductor-txdb.hsapiens.ucsc.hg38.knowngene >=3.22.0,<3.23.0a0
on libblas >=3.9.0,<4.0a0
on libgcc >=14
on liblapack >=3.9.0,<4.0a0
on liblzma >=5.8.2,<6.0a0
on libstdcxx >=14
on libzlib >=1.3.1,<2.0a0
on r-base >=4.5,<4.6.0a0
on r-circlize
on r-digest
on r-doparallel
on r-dt
on r-foreach
on r-getoptlong >=0.0.9
on r-globaloptions
on r-progress
on r-rcolorbrewer
on r-rcpp
on r-rcurl
on r-rjson
on r-shiny

Additional platforms:

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install bioconductor-rgreat

to add into an existing workspace instead, run:

pixi add bioconductor-rgreat

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install bioconductor-rgreat

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-rgreat

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

docker pull quay.io/biocontainers/bioconductor-rgreat:<tag>

(see bioconductor-rgreat/tags for valid values for <tag>).

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

Download stats¶

Link to this page¶

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-rgreat/README.html)