Package: vissE 1.15.0
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_1.15.0.tar.gz
vissE_1.15.0.zip(r-4.5)vissE_1.15.0.zip(r-4.4)vissE_1.15.0.zip(r-4.3)
vissE_1.15.0.tgz(r-4.4-any)vissE_1.15.0.tgz(r-4.3-any)
vissE_1.15.0.tar.gz(r-4.5-noble)vissE_1.15.0.tar.gz(r-4.4-noble)
vissE_1.15.0.tgz(r-4.4-emscripten)vissE_1.15.0.tgz(r-4.3-emscripten)
vissE.pdf |vissE.html✨
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:https://davislaboratory.github.io
- hgsc - The Hallmark collection from the MSigDB
On BioConductor:vissE-1.15.0(bioc 3.21)vissE-1.14.0(bioc 3.20)
softwaregeneexpressiongenesetenrichmentnetworkenrichmentnetworkbioinformatics
Last updated 2 months agofrom:090cdb9993. Checks:OK: 1 NOTE: 4 ERROR: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 19 2024 |
| R-4.5-win | NOTE | Dec 19 2024 |
| R-4.5-linux | NOTE | Dec 19 2024 |
| R-4.4-win | NOTE | Dec 19 2024 |
| R-4.4-mac | ERROR | Dec 19 2024 |
| R-4.3-win | NOTE | Dec 19 2024 |
| R-4.3-mac | ERROR | Dec 19 2024 |
Exports:bhuvad_themecharacteriseGenesetcomputeMsigNetworkcomputeMsigOverlapcomputeMsigWordFreqfindMsigClustersgetMsigExclusionListplotGeneStatsplotMsigNetworkplotMsigPPIplotMsigWordcloud
Dependencies:annotateAnnotationDbiAnnotationHubaskpassBHBiobaseBiocFileCacheBiocGenericsBiocManagerBiocVersionBiostringsbitbit64blobcachemclicolorspacecommonmarkcpp11crayoncurldata.tableDBIdbplyrdigestdplyrdttenglishExperimentHubfansifarverfastmapfastmatchfilelockgenericsGenomeInfoDbGenomeInfoDbDataggforceggplot2ggraphggrepelggwordcloudgluegraphgraphlayoutsgridExtragridtextGSEABasegtablehttrhunspelligraphIRangesisobandISOcodesjpegjsonliteKEGGRESTkoRpuskoRpus.lang.enlabelinglatticelexiconlifecyclemagrittrmarkdownMASSMatrixmemoisemgcvmgsubmimemsigdbmunsellnlmeNLPopensslorg.Hs.eg.dborg.Mm.eg.dbpillarpkgconfigplogrplyrpngpolyclippurrrqdapRegexquantedaR6rappdirsRColorBrewerRcppRcppArmadilloRcppEigenreshape2rlangRSQLiteS4VectorsscalesscicoslamSnowballCstopwordsstringistringrsyllysylly.ensyssystemfontssyuzhettextcleantextshapetextstemtibbletidygraphtidyrtidyselecttmtweenrUCSC.utilsutf8vctrsviridisviridisLitewithrxfunXMLxml2xtableXVectoryamlzlibbioczoo
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 |
