RAINBOWR0.1.38 package

Genome-Wide Association Study with SNP-Set Methods

adjustGRM

Function to adjust genomic relationship matrix (GRM) with subpopulatio...

calcGRM

Function to calculate genomic relationship matrix (GRM)

CalcThreshold

Function to calculate threshold for GWAS

convertBlockList

Function to convert haplotype block list from PLINK to RAINBOWR format

cumsumPos

Function to calculate cumulative position (beyond chromosome)

design.Z

Function to generate design matrix (Z)

EM3.cov

Equation of mixed model for multi-kernel considering covariance struct...

EM3.cpp

Equation of mixed model for multi-kernel (slow, general version)

EM3.general

Equation of mixed model for multi-kernel including using other package...

EM3.linker.cpp

Equation of mixed model for multi-kernel (fast, for limited cases)

EM3.op

Equation of mixed model for multi-kernel using other packages (much fa...

EMM.cpp

Equation of mixed model for one kernel, a wrapper of two methods

EMM1.cpp

Equation of mixed model for one kernel, GEMMA-based method (inplemente...

EMM2.cpp

Equation of mixed model for one kernel, EMMA-based method (inplemented...

estNetwork

Function to estimate & plot haplotype network

estPhylo

Function to estimate & plot phylogenetic tree

genesetmap

Function to generate map for gene set

genetrait

Generate pseudo phenotypic values

is.diag

Function to judge the square matrix whether it is diagonal matrix or n...

MAF.cut

Function to remove the minor alleles

make.full

Change a matrix to full-rank matrix

manhattan.plus

Add points of -log10(p) corrected by kernel methods to manhattan plot

manhattan

Draw manhattan plot

manhattan2

Draw manhattan plot (another method)

manhattan3

Draw the effects of epistasis (3d plot and 2d plot)

modify.data

Function to modify genotype and phenotype data to match

parallel.compute

Function to parallelize computation with various methods

plotHaploNetwork

Function to plot haplotype network from the estimated results

plotPhyloTree

Function to plot phylogenetic tree from the estimated results

qq

Draw qq plot

RAINBOWR

RAINBOWR: Perform Genome-Wide Asscoiation Study (GWAS) By Kernel-Based...

RGWAS.epistasis

Check epistatic effects by kernel-based GWAS (genome-wide association ...

RGWAS.menu

Print the R code which you should perform for RAINBOWR GWAS

RGWAS.multisnp.interaction

Testing multiple SNPs and their interaction with some kernel simultane...

RGWAS.multisnp

Testing multiple SNPs simultaneously for GWAS

RGWAS.normal.interaction

Perform normal GWAS including interaction (test each single SNP)

RGWAS.normal

Perform normal GWAS (test each single SNP)

RGWAS.twostep.epi

Perform normal GWAS (genome-wide association studies) first, then chec...

RGWAS.twostep

Perform normal GWAS (genome-wide association studies) first, then perf...

Rice_geno_map

Physical map of rice genome

Rice_geno_score

Marker genotype of rice genome

Rice_haplo_block

Physical map of rice genome

Rice_pheno

Phenotype data of rice field trial

score.calc.epistasis.LR.MC

Calculate -log10(p) of epistatic effects by LR test (multi-cores)

score.calc.epistasis.LR

Calculate -log10(p) of epistatic effects by LR test

score.calc.epistasis.score.MC

Calculate -log10(p) of epistatic effects with score test (multi-cores)

score.calc.epistasis.score

Calculate -log10(p) of epistatic effects with score test

score.calc.int.MC

Calculate -log10(p) for single-SNP GWAS with interaction (multi-cores)

score.calc.int

Calculate -log10(p) for single-SNP GWAS with interaction

score.calc.LR.int.MC

Calculate -log10(p) of each SNP-set and its interaction with kernels b...

score.calc.LR.int

Calculate -log10(p) of each SNP-set and its interaction with kernels b...

score.calc.LR.MC

Calculate -log10(p) of each SNP-set by the LR test (multi-cores)

score.calc.LR

Calculate -log10(p) of each SNP-set by the LR test

score.calc.MC

Calculate -log10(p) for single-SNP GWAS (multi-cores)

score.calc

Calculate -log10(p) for single-SNP GWAS

score.calc.score.MC

Calculate -log10(p) of each SNP-set by the score test (multi-cores)

score.calc.score

Calculate -log10(p) of each SNP-set by the score test

score.cpp

Calculte -log10(p) by score test (slow, for general cases)

score.linker.cpp

Calculte -log10(p) by score test (fast, for limited cases)

See

Function to view the first part of data (like head(), tail())

spectralG.cpp

Perform spectral decomposition (inplemented by Rcpp)

SS_gwas

Calculate some summary statistics of GWAS (genome-wide association stu...

welcome_to_RGWAS

Function to greet to users

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>.

  • Maintainer: Kosuke Hamazaki
  • License: MIT + file LICENSE
  • Last published: 2025-05-21