vissE

DOI: 10.18129/B9.bioc.vissE    

This is the development version of vissE; for the stable release version, see vissE.

Visualising Set Enrichment Analysis Results

Bioconductor version: Development (3.14)

This package enables the interpretation and analysis of results from a gene set enrichment analysis using network-based and text-mining approaches. Most enrichment analyses result in large lists of significant gene sets that are difficult to interpret. Tools in this package help build a similarity-based network of significant gene sets from a gene set enrichment analysis that can then be investigated for their biological function using text-mining approaches.

Author: Dharmesh D. Bhuva [aut, cre]

Maintainer: Dharmesh D. Bhuva <bhuva.d at wehi.edu.au>

Citation (from within R, enter citation("vissE")):

Installation

To install this package, start R (version "4.1") and enter:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("vissE")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("vissE")

 

HTML R Script vissE
PDF   Reference Manual
Text   NEWS

Details

biocViews GeneExpression, GeneSetEnrichment, Network, NetworkEnrichment, Software
Version 1.1.0
In Bioconductor since BioC 3.13 (R-4.1) (< 6 months)
License GPL-3
Depends R (>= 4.1)
Imports igraph, methods, plyr, ggplot2, ggnewscale, scico, RColorBrewer, tm, ggwordcloud, GSEABase, reshape2, grDevices, ggforce, msigdb, Matrix, ggrepel, textstem
LinkingTo
Suggests testthat, org.Hs.eg.db, org.Mm.eg.db, ggpubr, singscore, knitr, rmarkdown, prettydoc, BiocStyle
SystemRequirements
Enhances
URL https://davislaboratory.github.io/vissE
BugReports https://github.com/DavisLaboratory/vissE/issues
Depends On Me
Imports Me
Suggests Me msigdb
Links To Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package vissE_1.1.0.tar.gz
Windows Binary vissE_1.1.0.zip
macOS 10.13 (High Sierra) vissE_1.1.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/vissE
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/vissE
Package Short Url https://bioconductor.org/packages/vissE/
Package Downloads Report Download Stats

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