vissE
This package is for version 3.19 of Bioconductor; for the stable, up-to-date release version, see vissE.
Visualising Set Enrichment Analysis Results
Bioconductor version: 3.19
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] , Ahmed Mohamed [ctb]
Maintainer: Dharmesh D. Bhuva <bhuva.d at wehi.edu.au>
citation("vissE")
):
Installation
To install this package, start R (version "4.4") 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 | ||
NEWS | Text |
Details
biocViews | GeneExpression, GeneSetEnrichment, Network, NetworkEnrichment, Software |
Version | 1.12.0 |
In Bioconductor since | BioC 3.13 (R-4.1) (3.5 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 |
See More
Suggests | testthat, org.Hs.eg.db, org.Mm.eg.db, patchwork, singscore, knitr, rmarkdown, prettydoc, BiocStyle, pkgdown, covr |
Linking To | |
Enhances | |
Depends On Me | |
Imports Me | |
Suggests Me | msigdb |
Links To Me | |
Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | vissE_1.12.0.tar.gz |
Windows Binary (x86_64) | vissE_1.12.0.zip |
macOS Binary (x86_64) | vissE_1.12.0.tgz |
macOS Binary (arm64) | vissE_1.12.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/vissE |
Source Repository (Developer Access) | git clone [email protected]:packages/vissE |
Bioc Package Browser | https://code.bioconductor.org/browse/vissE/ |
Package Short Url | https://bioconductor.org/packages/vissE/ |
Package Downloads Report | Download Stats |