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: |
0.1.29 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
Rcpp, Matrix, cluster, MASS, pbmcapply, optimx, methods, ape, stringr, pegas, rrBLUP, expm, here, htmlwidgets, Rfast, gaston, MM4LMM |
| LinkingTo: |
Rcpp, RcppEigen |
| Suggests: |
knitr, rmarkdown, plotly, haplotypes, adegenet, ggplot2, ggtree, scatterpie, phylobase, furrr, future, progressr, foreach, doParallel |
| Published: |
2022-01-07 |
| 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 |