Package: limpca 1.1.0

Manon Martin

limpca: An R package for the linear modeling of high-dimensional designed data based on ASCA/APCA family of methods

This package has for objectives to provide a method to make Linear Models for high-dimensional designed data. limpca applies a GLM (General Linear Model) version of ASCA and APCA to analyse multivariate sample profiles generated by an experimental design. ASCA/APCA provide powerful visualization tools for multivariate structures in the space of each effect of the statistical model linked to the experimental design and contrarily to MANOVA, it can deal with mutlivariate datasets having more variables than observations. This method can handle unbalanced design.

Authors:Bernadette Govaerts [aut, ths], Sebastien Franceschini [ctb], Robin van Oirbeek [ctb], Michel Thiel [aut], Pascal de Tullio [dtc], Manon Martin [aut, cre], Nadia Benaiche [ctb]

limpca_1.1.0.tar.gz
limpca_1.1.0.zip(r-4.5)limpca_1.1.0.zip(r-4.4)limpca_1.1.0.zip(r-4.3)
limpca_1.1.0.tgz(r-4.4-any)limpca_1.1.0.tgz(r-4.3-any)
limpca_1.1.0.tar.gz(r-4.5-noble)limpca_1.1.0.tar.gz(r-4.4-noble)
limpca_1.1.0.tgz(r-4.4-emscripten)limpca_1.1.0.tgz(r-4.3-emscripten)
limpca.pdf |limpca.html
limpca/json (API)
NEWS

# Install 'limpca' in R:
install.packages('limpca', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/manonmartin/limpca/issues

Datasets:
  • UCH - UCH: the Urine Citrate-Hippurate metabolomic dataset
  • trout - Trout: the Rainbow trouts transcriptomic dataset

On BioConductor:limpca-1.1.0(bioc 3.20)limpca-1.0.0(bioc 3.19)

bioconductor-package

22 exports 1.64 score 132 dependencies

Last updated 2 months agofrom:d7869a9d1a

Exports:data2LmpDataListlmpBootstrapTestslmpContributionslmpEffectMatriceslmpEffectPlotlmpLoading1dPlotlmpLoading2dPlotlmpModelMatrixlmpPcaEffectslmpScorePlotlmpScoreScatterPlotMlmpScreePlotpcaBySvdpcaLoading1dPlotpcaLoading2dPlotpcaScorePlotpcaScreePlotplotDesignplotLineplotMeansplotScatterplotScatterM

Dependencies:abindaskpassbackportsbase64encBiobaseBiocGenericsbitbit64blobbroombslibcachemcallrcellrangerclicliprcodetoolscolorspaceconflictedcpp11crayoncurldata.tableDBIdbplyrDelayedArraydigestdoParalleldplyrdtplyrevaluatefansifarverfastmapfontawesomeforcatsforeachfsgarglegenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2ggrepelggscigluegoogledrivegooglesheets4gtablehavenhighrhmshtmltoolshttridsIRangesisobanditeratorsjquerylibjsonliteknitrlabelinglatticelifecyclelubridatemagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimemodelrmunsellnlmeopensslpillarpkgconfigplyrprettyunitsprocessxprogresspspurrrR6raggrappdirsRColorBrewerRcppreadrreadxlrematchrematch2reprexreshape2rlangrmarkdownrstudioapirvestS4ArraysS4VectorssassscalesselectrSparseArraystringistringrSummarizedExperimentsyssystemfontstextshapingtibbletidyrtidyselecttidyversetimechangetinytextzdbUCSC.utilsutf8uuidvctrsviridisLitevroomwithrxfunxml2XVectoryamlzlibbioc

Application of limpca on the Trout transcriptomic dataset.

Rendered fromTrout.Rmdusingknitr::rmarkdownon Jun 30 2024.

Last update: 2024-04-26
Started: 2022-12-07

Application of limpca on the UCH metabolomics dataset.

Rendered fromUCH.Rmdusingknitr::rmarkdownon Jun 30 2024.

Last update: 2024-04-26
Started: 2022-09-20

Get started with limpca.

Rendered fromlimpca.Rmdusingknitr::rmarkdownon Jun 30 2024.

Last update: 2024-04-26
Started: 2022-12-06