DESCRIPTION

Package: RAINBOWR
Type: Package
Title: Genome-Wide Association Study with SNP-Set Methods
Version: 0.1.37
Authors@R: c(
  person("Kosuke", "Hamazaki", email = "hamazaki@ut-biomet.org", role = c("aut", "cre")),
  person("Hiroyoshi", "Iwata", email = "aiwata@mail.ecc.u-tokyo.ac.jp", role = c("aut", "ctb"))
  )
Maintainer: Kosuke Hamazaki <hamazaki@ut-biomet.org>
Description: By using 'RAINBOWR' (Reliable Association INference By Optimizing Weights with R), users can test multiple SNPs (Single Nucleotide Polymorphisms) simultaneously by kernel-based (SNP-set) methods. This package can also be applied to haplotype-based GWAS (Genome-Wide Association Study). Users can test not only additive effects but also dominance and epistatic effects. In detail, please check our paper on PLOS Computational Biology: Kosuke Hamazaki and Hiroyoshi Iwata (2020) <doi:10.1371/journal.pcbi.1007663>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: Rcpp,
         Matrix,
         cluster,
         MASS,
         pbmcapply,
         optimx,
         methods,
         ape,
         stringr,
         pegas,
         rrBLUP,
         expm,
         here,
         htmlwidgets,
         Rfast,
         gaston,
         MM4LMM,
         R.utils
LinkingTo: Rcpp, RcppEigen
RoxygenNote: 7.3.1
Suggests: 
    knitr,
    rmarkdown,
    plotly,
    haplotypes,
    adegenet,
    ggplot2,
    ggtree,
    scatterpie,
    phylobase,
    ggimage,
    furrr,
    future,
    progressr,
    foreach,
    doParallel,
    data.table
VignetteBuilder: knitr