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

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)
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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'))

Peer review:

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

Datasets:
  • hgsc - The Hallmark collection from the MSigDB

On BioConductor:vissE-1.15.0(bioc 3.21)vissE-1.14.0(bioc 3.20)

softwaregeneexpressiongenesetenrichmentnetworkenrichmentnetworkbioinformatics

6.02 score 13 stars 18 scripts 218 downloads 11 exports 133 dependencies

Last updated 23 days agofrom:090cdb9993. Checks:OK: 1 NOTE: 4 ERROR: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 19 2024
R-4.5-winNOTENov 19 2024
R-4.5-linuxNOTENov 19 2024
R-4.4-winNOTENov 19 2024
R-4.4-macERRORNov 19 2024
R-4.3-winNOTENov 19 2024
R-4.3-macERRORNov 19 2024

Exports:bhuvad_themecharacteriseGenesetcomputeMsigNetworkcomputeMsigOverlapcomputeMsigWordFreqfindMsigClustersgetMsigExclusionListplotGeneStatsplotMsigNetworkplotMsigPPIplotMsigWordcloud

Dependencies:annotateAnnotationDbiAnnotationHubaskpassBHBiobaseBiocFileCacheBiocGenericsBiocManagerBiocVersionBiostringsbitbit64blobcachemclicolorspacecommonmarkcpp11crayoncurldata.tableDBIdbplyrdigestdplyrdttenglishExperimentHubfansifarverfastmapfastmatchfilelockgenericsGenomeInfoDbGenomeInfoDbDataggforceggplot2ggraphggrepelggwordcloudgluegraphgraphlayoutsgridExtragridtextGSEABasegtablehttrhunspelligraphIRangesisobandISOcodesjpegjsonliteKEGGRESTkoRpuskoRpus.lang.enlabelinglatticelexiconlifecyclemagrittrmarkdownMASSMatrixmemoisemgcvmgsubmimemsigdbmunsellnlmeNLPopensslorg.Hs.eg.dborg.Mm.eg.dbpillarpkgconfigplogrplyrpngpolyclippurrrqdapRegexquantedaR6rappdirsRColorBrewerRcppRcppArmadilloRcppEigenreshape2rlangRSQLiteS4VectorsscalesscicoslamSnowballCstopwordsstringistringrsyllysylly.ensyssystemfontssyuzhettextcleantextshapetextstemtibbletidygraphtidyrtidyselecttmtweenrUCSC.utilsutf8vctrsviridisviridisLitewithrxfunXMLxml2xtableXVectoryamlzlibbioczoo

vissE: Visualising Set Enrichment Analysis Results.

Rendered fromvissE.Rmdusingknitr::rmarkdownon Nov 19 2024.

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