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 + fileLICENSE |
| NeedsCompilation: | yes |
| Citation: | RAINBOWR citation info |
| Materials: | README,NEWS |
| CRAN checks: | RAINBOWR results |