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:
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✨
DESCRIPTION |NEWS
card.svg |card.png
vissE/json (API)
| # 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
- hgsc - The Hallmark collection from the MSigDB
On BioConductor:vissE-1.21.0(bioc 3.24)vissE-1.20.0(bioc 3.23)
softwaregeneexpressiongenesetenrichmentnetworkenrichmentnetworkbioinformatics
Last updated from:faf767d8c4. Checks:1 FAILURE, 8 ERROR, 1 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | FAILURE | 282 | ||
| linux-devel-x86_64 | ERROR | 300 | ||
| source / vignettes | ERROR | 394 | ||
| linux-release-x86_64 | ERROR | 330 | ||
| macos-release-arm64 | ERROR | 128 | ||
| macos-oldrel-arm64 | ERROR | 150 | ||
| windows-devel | ERROR | 256 | ||
| windows-release | ERROR | 245 | ||
| windows-oldrel | ERROR | 227 | ||
| wasm-release | OK | 212 |
Exports:bhuvad_themecharacteriseGenesetcomputeMsigNetworkcomputeMsigOverlapcomputeMsigWordFreqfindMsigClustersgetMsigExclusionListplotGeneStatsplotMsigNetworkplotMsigPPIplotMsigWordcloud
Dependencies:annotateAnnotationDbiAnnotationHubaskpassbase64encBHBiobaseBiocBaseUtilsBiocFileCacheBiocGenericsBiocManagerBiocVersionBiostringsbitbit64blobcachemclicolorspacecommonmarkcpp11crayoncurldata.tableDBIdbplyrdigestdplyrdttenglishExperimentHubfarverfastmapfastmatchfilelockgenericsggforceggplot2ggraphggrepelggwordcloudgluegraphgraphlayoutsgridExtragridtextGSEABasegtablehttrhttr2hunspelligraphIRangesisobandISOcodesjpegjsonliteKEGGRESTkoRpuskoRpus.lang.enlabelinglatticelexiconlifecyclelitedownmagrittrmarkdownMASSMatrixmemoisemgsubmimemsigdbNLPopensslorg.Hs.eg.dborg.Mm.eg.dbpillarpkgconfigplyrpngpolyclippurrrqdapRegexquantedaR6rappdirsRColorBrewerRcppRcppArmadilloreshape2rlangRSQLiteS4VectorsS7scalesscicoSeqinfoslamSnowballCstopwordsstringistringrsyllysylly.ensyssystemfontssyuzhettextcleantextshapetextstemtibbletidygraphtidyrtidyselecttmtweenrutf8vctrsviridisviridisLitewithrxfunXMLxml2xtableXVectoryamlzoo
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 |