Package Recipe 'bioconductor-viseago'

recipe bioconductor-viseago

ViSEAGO: a Bioconductor package for clustering biological functions using Gene Ontology and semantic similarity

Homepage:: https://bioconductor.org/packages/3.18/bioc/html/ViSEAGO.html
License:: GPL-3
Recipe:: /bioconductor-viseago/meta.yaml

The main objective of ViSEAGO package is to carry out a data mining of biological functions and establish links between genes involved in the study. We developed ViSEAGO in R to facilitate functional Gene Ontology (GO) analysis of complex experimental design with multiple comparisons of interest. It allows to study large-scale datasets together and visualize GO profiles to capture biological knowledge. The acronym stands for three major concepts of the analysis: Visualization, Semantic similarity and Enrichment Analysis of Gene Ontology. It provides access to the last current GO annotations, which are retrieved from one of NCBI EntrezGene, Ensembl or Uniprot databases for several species. Using available R packages and novel developments, ViSEAGO extends classical functional GO analysis to focus on functional coherence by aggregating closely related biological themes while studying multiple datasets at once. It provides both a synthetic and detailed view using interactive functionalities respecting the GO graph structure and ensuring functional coherence supplied by semantic similarity. ViSEAGO has been successfully applied on several datasets from different species with a variety of biological questions. Results can be easily shared between bioinformaticians and biologists, enhancing reporting capabilities while maintaining reproducibility.

package bioconductor-viseago¶

Versions:

1.24.0-0, 1.16.0-0, 1.14.0-0, 1.12.0-0, 1.8.0-0, 1.6.0-0, 1.4.0-1, 1.4.0-0, 1.2.0-0,

1.24.0-0, 1.16.0-0, 1.14.0-0, 1.12.0-0, 1.8.0-0, 1.6.0-0, 1.4.0-1, 1.4.0-0, 1.2.0-0, 1.0.0-0

Depends:

on bioconductor-annotationdbi >=1.72.0,<1.73.0
on bioconductor-annotationforge >=1.52.0,<1.53.0
on bioconductor-biomart >=2.66.0,<2.67.0
on bioconductor-complexheatmap >=2.26.0,<2.27.0
on bioconductor-fgsea >=1.36.0,<1.37.0
on bioconductor-go.db >=3.22.0,<3.23.0
on bioconductor-gosemsim >=2.36.0,<2.37.0
on bioconductor-topgo >=2.62.0,<2.63.0
on r-base >=4.5,<4.6.0a0
on r-circlize
on r-data.table
on r-dendextend
on r-diagrammer
on r-dt
on r-dynamictreecut
on r-ggplot2
on r-heatmaply
on r-htmlwidgets
on r-igraph
on r-plotly
on r-r.utils
on r-rcolorbrewer
on r-scales
on r-upsetr

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-viseago

to add into an existing workspace instead, run:

pixi add bioconductor-viseago

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-viseago

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-viseago

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-viseago:<tag>

(see bioconductor-viseago/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-viseago/README.html)