vissE

This package is for version 3.14 of Bioconductor; for the stable, up-to-date release version, see vissE.

Visualising Set Enrichment Analysis Results

Bioconductor version: 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 (!require("BiocManager", quietly = TRUE))
 install.packages("BiocManager")
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")

vissE HTML R Script

Reference Manual PDF

NEWS Text

Need some help? Ask on the Bioconductor Support site!

Details

biocViews GeneExpression, GeneSetEnrichment, Network, NetworkEnrichment, Software

Version 1.2.2

In Bioconductor since BioC 3.13 (R-4.1) (3 years)

License GPL-3

Depends R (>= 4.1)

Imports igraph, methods, plyr, ggplot2, scico, RColorBrewer, tm, ggwordcloud, GSEABase, reshape2, grDevices, ggforce, msigdb, ggrepel, textstem, tidygraph, stats, scales, ggraph

System Requirements

URL https://davislaboratory.github.io/vissE

Bug Reports https://github.com/DavisLaboratory/vissE/issues

Suggests testthat, org.Hs.eg.db, org.Mm.eg.db, patchwork, singscore, knitr, rmarkdown, prettydoc, BiocStyle, pkgdown, covr

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