Package: limpca 1.3.0

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]

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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

Pkgdown:https://manonmartin.github.io

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

On BioConductor:limpca-1.3.0(bioc 3.21)limpca-1.2.0(bioc 3.20)

statisticalmethodprincipalcomponentregressionvisualizationexperimentaldesignmultiplecomparisongeneexpressionmetabolomics

5.56 score 1 stars 2 scripts 98 downloads 22 exports 132 dependencies

Last updated 2 months agofrom:8e4f4cef0d. Checks:OK: 5 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 04 2024
R-4.5-winNOTEDec 04 2024
R-4.5-linuxNOTEDec 04 2024
R-4.4-winOKDec 04 2024
R-4.4-macOKDec 04 2024
R-4.3-winOKDec 04 2024
R-4.3-macOKDec 04 2024

Exports:data2LmpDataListlmpBootstrapTestslmpContributionslmpEffectMatriceslmpEffectPlotlmpLoading1dPlotlmpLoading2dPlotlmpModelMatrixlmpPcaEffectslmpScorePlotlmpScoreScatterPlotMlmpScreePlotpcaBySvdpcaLoading1dPlotpcaLoading2dPlotpcaScorePlotpcaScreePlotplotDesignplotLineplotMeansplotScatterplotScatterM

Dependencies:abindaskpassbackportsbase64encBiobaseBiocGenericsbitbit64blobbroombslibcachemcallrcellrangerclicliprcodetoolscolorspaceconflictedcpp11crayoncurldata.tableDBIdbplyrDelayedArraydigestdoParalleldplyrdtplyrevaluatefansifarverfastmapfontawesomeforcatsforeachfsgarglegenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2ggrepelggscigluegoogledrivegooglesheets4gtablehavenhighrhmshtmltoolshttridsIRangesisobanditeratorsjquerylibjsonliteknitrlabelinglatticelifecyclelubridatemagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimemodelrmunsellnlmeopensslpillarpkgconfigplyrprettyunitsprocessxprogresspspurrrR6raggrappdirsRColorBrewerRcppreadrreadxlrematchrematch2reprexreshape2rlangrmarkdownrstudioapirvestS4ArraysS4VectorssassscalesselectrSparseArraystringistringrSummarizedExperimentsyssystemfontstextshapingtibbletidyrtidyselecttidyversetimechangetinytextzdbUCSC.utilsutf8uuidvctrsviridisLitevroomwithrxfunxml2XVectoryamlzlibbioc

Application of limpca on the Trout transcriptomic dataset.

Benaiche Nadia, Bernadette Govaerts

Rendered fromTrout.Rmdusingknitr::rmarkdownon Dec 04 2024.

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

Application of limpca on the UCH metabolomics dataset.

Benaiche Nadia, Sébastien Franceschini, Martin Manon, Thiel Michel, Govaerts Bernadette

Rendered fromUCH.Rmdusingknitr::rmarkdownon Dec 04 2024.

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

Get started with limpca.

Benaiche Nadia, Sébastien Franceschini, Martin Manon, Thiel Michel, Govaerts Bernadette

Rendered fromlimpca.Rmdusingknitr::rmarkdownon Dec 04 2024.

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