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) .


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install.packages("RAINBOWR")

0.1.21 by Kosuke Hamazaki, 5 days ago


Browse source code at https://github.com/cran/RAINBOWR


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


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports Rcpp, rgl, tcltk, Matrix, cluster, MASS, pbmcapply, optimx, methods, ape, stringr, pegas, ggplot2, ggtree, scatterpie, phylobase, haplotypes, ggimage, rrBLUP, expm, parallel, pbapply

Suggests knitr, rmarkdown

Linking to Rcpp, RcppEigen


See at CRAN