Package: vissE 1.21.0

Dharmesh D. Bhuva

vissE: Visualising Set Enrichment Analysis Results

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.

Authors:Dharmesh D. Bhuva [aut, cre], Ahmed Mohamed [ctb]

vissE_1.21.0.tar.gz
vissE_1.21.0.zip(r-4.7)vissE_1.21.0.zip(r-4.6)vissE_1.21.0.zip(r-4.5)
vissE_1.21.0.tgz(r-4.6-any)vissE_1.21.0.tgz(r-4.5-any)
vissE_1.21.0.tar.gz(r-4.7-any)vissE_1.21.0.tar.gz(r-4.6-any)
vissE_1.21.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
vissE/json (API)
NEWS

# Install 'vissE' in R:

install.packages('vissE', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/davislaboratory/visse/issues

Pkgdown/docs site:https://davislaboratory.github.io

Datasets:

hgsc - The Hallmark collection from the MSigDB

On BioConductor:vissE-1.21.0(bioc 3.24)vissE-1.20.0(bioc 3.23)

software geneexpression genesetenrichment networkenrichment network bioinformatics

6.10 score 19 stars 22 scripts 400 downloads 11 exports 129 dependencies

Last updated from:faf767d8c4. Checks:8 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	NOTE	236
linux-devel-x86_64	NOTE	336
source / vignettes	OK	548
linux-release-x86_64	NOTE	358
macos-release-arm64	NOTE	221
macos-oldrel-arm64	NOTE	192
windows-devel	NOTE	265
windows-release	NOTE	241
windows-oldrel	NOTE	291
wasm-release	OK	214

Exports:bhuvad_theme characteriseGeneset computeMsigNetwork computeMsigOverlap computeMsigWordFreq findMsigClusters getMsigExclusionList plotGeneStats plotMsigNetwork plotMsigPPI plotMsigWordcloud

Dependencies:annotate AnnotationDbi AnnotationHub askpass base64enc BH Biobase BiocBaseUtils BiocFileCache BiocGenerics BiocManager BiocVersion Biostrings bit bit64 blob cachem cli colorspace commonmark cpp11 crayon curl data.table DBI dbplyr digest dplyr dtt english ExperimentHub farver fastmap fastmatch filelock generics ggforce ggplot2 ggraph ggrepel ggwordcloud glue graph graphlayouts gridExtra gridtext GSEABase gtable httr httr2 hunspell igraph IRanges isoband ISOcodes jpeg jsonlite KEGGREST koRpus koRpus.lang.en labeling lattice lexicon lifecycle litedown magrittr markdown MASS Matrix memoise mgsub mime msigdb NLP openssl org.Hs.eg.db org.Mm.eg.db pillar pkgconfig plyr png polyclip purrr qdapRegex quanteda R6 rappdirs RColorBrewer Rcpp RcppArmadillo reshape2 rlang RSQLite S4Vectors S7 scales scico Seqinfo slam SnowballC stopwords stringi stringr sylly sylly.en sys systemfonts syuzhet textclean textshape textstem tibble tidygraph tidyr tidyselect tm tweenr utf8 vctrs viridis viridisLite withr xfun XML xml2 xtable XVector yaml zoo

vissE: Visualising Set Enrichment Analysis Results.

Dharmesh D. Bhuva

Rendered fromvissE.Rmdusingknitr::rmarkdownon May 18 2026.

Last update: 2022-03-17
Started: 2021-01-21

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Custom theme	bhuvad_theme
Functionally characterise a list of genes	characteriseGeneset
Compute a network using computed gene set overlap	computeMsigNetwork
Compute gene set overlap	computeMsigOverlap
Compute word frequencies for a single MSigDB collection	computeMsigWordFreq
Identify gene-set clusters from a gene-set overlap network	findMsigClusters
Exclusion list of words for MSigDB gene set text mining	getMsigExclusionList
The Hallmark collection from the MSigDB	hgsc
Plot gene statistics for clusters of gene sets	plotGeneStats
Plot a gene set overlap network	plotMsigNetwork
Plot PPI network for gene-set clusters identified using vissE	plotMsigPPI
Compute and plot word frequencies for multiple MSigDB collections	plotMsigWordcloud