Package: limpca
Type: Package
Title: An R package for the linear modeling of high-dimensional
        designed data based on ASCA/APCA family of methods
Version: 1.0.0
Authors@R: c(person("Bernadette", "Govaerts", role = c("aut", "ths"),
                     email = "bernadette.govaerts@uclouvain.be"),
              person("Sebastien","Franceschini", role = "ctb",
                    email="sfranceschini@uliege.be"),
              person("Robin","van Oirbeek", role = "ctb",
                    email="robin.vanoirbeek@gmail.com"),
              person("Michel","Thiel", role = "aut",
                    email="michel.thiel@uclouvain.be"),
              person("Pascal","de Tullio", role = "dtc",
                    email="pdetullio@uliege.be"),
              person("Manon","Martin", role = c("aut", "cre"),
                    email="manon.martin@uclouvain.be",
                    comment = c(ORCID = "0000-0003-4800-0942")),
              person("Nadia", "Benaiche", role = "ctb",
                     email = "nadia.benaiche@student.uclouvain.be"))
Description: 
 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.
License: Artistic-2.0
Encoding: UTF-8
LazyData: FALSE
VignetteBuilder: knitr
Imports: ggplot2, stringr, plyr, ggrepel, reshape2, grDevices,
        graphics, doParallel, parallel, dplyr, tibble, tidyr, ggsci,
        tidyverse, methods, stats, SummarizedExperiment, S4Vectors
Suggests: BiocStyle, pander, rmarkdown, car, gridExtra, knitr, testthat
        (>= 3.0.0)
biocViews: StatisticalMethod, PrincipalComponent, Regression,
        Visualization, ExperimentalDesign, MultipleComparison,
        GeneExpression, Metabolomics
RoxygenNote: 7.3.1
Roxygen: list(markdown=TRUE)
BugReports: https://github.com/ManonMartin/limpca/issues
URL: https://github.com/ManonMartin/limpca,
        https://manonmartin.github.io/limpca/
Config/testthat/edition: 3
git_url: https://git.bioconductor.org/packages/limpca
git_branch: RELEASE_3_19
git_last_commit: 9dcb770
git_last_commit_date: 2024-04-30
Repository: Bioconductor 3.19
Date/Publication: 2024-04-30
NeedsCompilation: no
Packaged: 2024-05-01 05:23:52 UTC; biocbuild
Author: Bernadette Govaerts [aut, ths],
  Sebastien Franceschini [ctb],
  Robin van Oirbeek [ctb],
  Michel Thiel [aut],
  Pascal de Tullio [dtc],
  Manon Martin [aut, cre] (<https://orcid.org/0000-0003-4800-0942>),
  Nadia Benaiche [ctb]
Maintainer: Manon Martin <manon.martin@uclouvain.be>
Depends: R (>= 3.5.0)
Built: R 4.4.0; ; 2024-05-01 13:47:57 UTC; unix
