Genome-Wide Association Study with SNP-Set Methods R package RAINBOWR version 0.1.38 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>. Software 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 Suggests: knitr, rmarkdown, plotly, haplotypes, adegenet, ggplot2, ggtree, scatterpie, phylobase, ggimage, furrr, future, progressr, foreach, doParallel, data.table Kosuke Hamazaki <hamazaki@ut-biomet.org> Comprehensive R Archive Network (CRAN) Kosuke Hamazaki [aut, cre], Hiroyoshi Iwata [aut, ctb] MIT + file LICENSE (https://CRAN.R-project.org/package=RAINBOWR/LICENSE) 2025-05-21 application/tgz https://CRAN.R-project.org/package=RAINBOWR doi:10.32614/CRAN.package.RAINBOWR