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>.
Version: 0.1.38 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 Published: 2025-05-21 DOI: 10.32614/CRAN.package.RAINBOWR Author: Kosuke Hamazaki [aut, cre], Hiroyoshi Iwata [aut, ctb] Maintainer: Kosuke Hamazaki <hamazaki at ut-biomet.org> License: MIT + file LICENSE NeedsCompilation: yes Citation: RAINBOWR citation info Materials: README, NEWS CRAN checks: RAINBOWR results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=RAINBOWR to link to this page.
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