Package: pcadapt
Type: Package
Title: Fast Principal Component Analysis for Outlier Detection
Version: 4.1.0
Date: 2019-02-26
Authors@R: c(person("Keurcien", "Luu", role = c("aut"), email = "keurcien.luu@univ-grenoble-alpes.fr"), 
          person("Michael", "Blum", role = c("aut", "cre"), email = "michael.blum@univ-grenoble-alpes.fr"),
          person("Florian", "Privé", role = c("aut"), email = "florian.prive.21@gmail.com"),
          person("Eric", "Bazin", role = c("ctb"), email = "eric.bazin@univ-grenoble-alpes.fr"),
          person("Nicolas", "Duforet-Frebourg", role = c("ctb")))
Description: Methods to detect genetic markers involved in biological
    adaptation. 'pcadapt' provides statistical tools for outlier detection based on
    Principal Component Analysis. Implements the method described in (Luu, 2016)
    <DOI:10.1111/1755-0998.12592>.
License: GPL (>= 2)
Imports: data.table, ggplot2, magrittr, mmapcharr (>= 0.3), plotly,
        Rcpp (>= 0.12.8), robust, RSpectra, vcfR
LinkingTo: Rcpp, rmio, mmapcharr
LazyData: TRUE
Suggests: knitr, rmarkdown, testthat, shiny, covr
RoxygenNote: 6.1.0
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2019-02-26 12:41:08 UTC; privef
Author: Keurcien Luu [aut],
  Michael Blum [aut, cre],
  Florian Privé [aut],
  Eric Bazin [ctb],
  Nicolas Duforet-Frebourg [ctb]
Maintainer: Michael Blum <michael.blum@univ-grenoble-alpes.fr>
Repository: CRAN
Date/Publication: 2019-02-27 13:20:03 UTC
Built: R 3.4.4; x86_64-w64-mingw32; 2019-04-25 22:45:31 UTC; windows
Archs: i386, x64
