DESCRIPTION

Package: PCAworkshop
Title: An introduction to matrix factorization and principal component analysis in R
Version: 0.2.1
Authors@R: 
    c(person(given = "Aedin", family = "Culhane",
             role = c("aut", "cre"),
             email = "aedin@ds.dfci.harvard.edu",
             comment = c(ORCID = "0000-0002-1395-9734")),
    person(given = "Lauren", family = "Hsu",
             role = c("aut"),
             email = "lrnshoe@gmail.com",
             comment = c(ORCID = "0000-0002-6035-7381")))
Description: A short workshop that explains how to compute PCA from basics, and the different implementations of PCA in R.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.1.0
Depends: 
    Biobase
Suggests: 
    knitr,
    rmarkdown,
    pkgdown,
    BiocStyle,
    magick
Imports:
    ggplot2, 
    ggfortify,
    factoextra, 
    FactoMineR, 
    ade4, 
    irlba,
    explor,
    dplyr,
    magrittr,
    reshape2,
    tibble,
    corral,
    glmpca,
    scatterD3,
    ComplexHeatmap,
    uwot,
    SingleCellExperiment,
    DuoClustering2018
URL: https://aedin.github.io/PCAworkshop/
BugReports: https://github.com/aedin/PCAworkshop/issues/new/choose
DockerImage: aculhane/pcabiocworkshop2020:latest
VignetteBuilder: knitr