 
  
 
   
   This package is for version 3.13 of Bioconductor; for the stable, up-to-date release version, see vissE.
Bioconductor version: 3.13
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")):
To install this package, start R (version "4.1") and enter:
if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("vissE")
    For older versions of R, please refer to the appropriate Bioconductor release.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("vissE")
    
| HTML | R Script | vissE | 
| Reference Manual | ||
| Text | NEWS | 
| biocViews | GeneExpression, GeneSetEnrichment, Network, NetworkEnrichment, Software | 
| Version | 1.0.0 | 
| 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 | 
Follow Installation instructions to use this package in your R session.
| Source Package | vissE_1.0.0.tar.gz | 
| Windows Binary | vissE_1.0.0.zip | 
| macOS 10.13 (High Sierra) | vissE_1.0.0.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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