Genome-Wide Association Study with SNP-Set Methods

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) .


Reference manual

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0.1.29 by Kosuke Hamazaki, 21 days ago

Browse source code at

Authors: Kosuke Hamazaki [aut, cre] , Hiroyoshi Iwata [aut, ctb]

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports Rcpp, Matrix, cluster, MASS, pbmcapply, optimx, methods, ape, stringr, pegas, rrBLUP, expm, here, htmlwidgets, Rfast, gaston, MM4LMM

Suggests knitr, rmarkdown, plotly, haplotypes, adegenet, ggplot2, ggtree, scatterpie, phylobase, furrr, future, progressr, foreach, doParallel

Linking to Rcpp, RcppEigen

See at CRAN