Package: vsclust 1.14.0

Veit Schwammle

vsclust: Feature-based variance-sensitive quantitative clustering

Feature-based variance-sensitive clustering of omics data. Optimizes cluster assignment by taking into account individual feature variance. Includes several modules for statistical testing, clustering and enrichment analysis.

Authors:Veit Schwammle [aut, cre]

vsclust_1.14.0.tar.gz
vsclust_1.14.0.zip(r-4.7-x86_64)vsclust_1.14.0.zip(r-4.7-arm64)vsclust_1.14.0.zip(r-4.6-x86_64)vsclust_1.14.0.zip(r-4.6-arm64)vsclust_1.14.0.zip(r-4.5-x86_64)
vsclust_1.14.0.tgz(r-4.6-x86_64)vsclust_1.14.0.tgz(r-4.6-arm64)vsclust_1.14.0.tgz(r-4.5-x86_64)vsclust_1.14.0.tgz(r-4.5-arm64)
vsclust_1.14.0.tar.gz(r-4.7-arm64)vsclust_1.14.0.tar.gz(r-4.7-x86_64)vsclust_1.14.0.tar.gz(r-4.6-arm64)vsclust_1.14.0.tar.gz(r-4.6-x86_64)
vsclust_1.14.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
vsclust/json (API)

# Install 'vsclust' in R:
install.packages('vsclust', repos = c('https://bioc-release.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On BioConductor:vsclust-1.15.9(bioc 3.24)vsclust-1.14.0(bioc 3.23)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

clusteringannotationprincipalcomponentdifferentialexpressionvisualizationproteomicsmetabolomicscpp

4.81 score 13 scripts 414 downloads 20 exports 140 dependencies

Last updated from:6357d6c7d2 (on RELEASE_3_23). Checks:14 NOTE, 2 OK. Indexed: no.

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bioc-checksNOTE273
linux-devel-arm64NOTE394
linux-devel-x86_64NOTE579
source / vignettesOK477
linux-release-arm64NOTE402
linux-release-x86_64NOTE577
macos-release-arm64NOTE378
macos-release-x86_64NOTE586
macos-oldrel-arm64NOTE419
macos-oldrel-x86_64NOTE673
windows-devel-arm64NOTE456
windows-devel-x86_64NOTE474
windows-release-arm64NOTE501
windows-release-x86_64NOTE428
windows-oldrel-x86_64NOTE528
wasm-releaseOK186

Exports:averageCondcalcBHIClustCompcvalidate.xiebenidetermine_fuzzenrichSTRING_APIestimClust.plotestimClustNummfuzz.plotoptimalClustNumpcaWithVarPrepareForVSClustPrepareSEForVSClustrunClustWrapperrunFuncEnrichrunVSClustAppSignAnalysisSignAnalysisPairedSwitchOrdervsclust_algorithm

Dependencies:abindaisdkAnnotationDbiapeaplotaskpassbase64encBiobaseBiocBaseUtilsBiocGenericsBiostringsbitbit64blobbslibcachemcallrcliclusterclusterProfilercommonmarkcpp11crayoncurlDBIDelayedArraydigestDOSEdplyrenrichitenrichplotevaluatefarverfastmapfontawesomefontBitstreamVerafontLiberationfontquiverfsgdtoolsgenericsGenomicRangesggforceggfunggiraphggnewscaleggplot2ggplotifyggrepelggtangleggtreeglueGO.dbGOSemSimgridGraphicsgsongtablehighrhtmltoolshtmlwidgetshttpuvhttrhttr2igraphIRangesisobandjquerylibjsonliteKEGGRESTknitrlabelinglaterlatticelazyevallifecyclelimmamagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemimeMultiAssayExperimentnlmeopensslotelpatchworkpillarpkgconfigplyrpngpolyclipprocessxpromisespspurrrqvalueR6rappdirsRColorBrewerRcppRcppEigenreshape2rlangrmarkdownRSQLiteS4ArraysS4VectorsS7sassscalesscatterpieSeqinfoshinysourcetoolsSparseArraystatmodstringistringrSummarizedExperimentsyssystemfontstibbletidydrtidyrtidyselecttidytreetinytextreeiotweenrutf8vctrsviridisLitewithrxfunxtableXVectoryamlyulab.utils

VSClust workflow
Introduction | Installation and additional packages | Initialization | Statistics and data preprocessing | Estimation of cluster number | Run final clustering
Rendered fromRun_VSClust_Workflow.Rmdusingknitr::rmarkdown

Last update: 2026-03-26
Started: 2022-03-23

VSClust with Bioconductor objects
Introduction | Installation and additional packages | Initialization | Statistics and data preprocessing | Estimation of cluster number | Run final clustering
Rendered fromIntegrate_With_Bioconductor_Objects.Rmdusingknitr::rmarkdown

Last update: 2024-11-13
Started: 2022-09-23