Man pages for RAINBOWR
Genome-Wide Association Study with SNP-Set Methods

adjustGRMFunction to adjust genomic relationship matrix (GRM) with...
calcGRMFunction to calculate genomic relationship matrix (GRM)
CalcThresholdFunction to calculate threshold for GWAS
convertBlockListFunction to convert haplotype block list from PLINK to...
cumsumPosFunction to calculate cumulative position (beyond chromosome)
design.ZFunction to generate design matrix (Z)
EM3.cppEquation of mixed model for multi-kernel (slow, general...
EM3.generalEquation of mixed model for multi-kernel including using...
EM3.linker.cppEquation of mixed model for multi-kernel (fast, for limited...
EM3.opEquation of mixed model for multi-kernel using other packages...
EMM1.cppEquation of mixed model for one kernel, GEMMA-based method...
EMM2.cppEquation of mixed model for one kernel, EMMA-based method...
EMM.cppEquation of mixed model for one kernel, a wrapper of two...
estNetworkFunction to estimate & plot haplotype network
estPhyloFunction to estimate & plot phylogenetic tree
genesetmapFunction to generate map for gene set
genetraitGenerate pseudo phenotypic values
is.diagFunction to judge the square matrix whether it is diagonal...
MAF.cutFunction to remove the minor alleles
make.fullChange a matrix to full-rank matrix
manhattanDraw manhattan plot
manhattan2Draw manhattan plot (another method)
manhattan3Draw the effects of epistasis (3d plot and 2d plot)
manhattan.plusAdd points of -log10(p) corrected by kernel methods to...
modify.dataFunction to modify genotype and phenotype data to match
parallel.computeFunction to parallelize computation with various methods
plotHaploNetworkFunction to plot haplotype network from the estimated results
plotPhyloTreeFunction to plot phylogenetic tree from the estimated results
qqDraw qq plot
RAINBOWRRAINBOWR: Perform Genome-Wide Asscoiation Study (GWAS) By...
RGWAS.epistasisCheck epistatic effects by kernel-based GWAS (genome-wide...
RGWAS.menuPrint the R code which you should perform for RAINBOWR GWAS
RGWAS.multisnpTesting multiple SNPs simultaneously for GWAS
RGWAS.multisnp.interactionTesting multiple SNPs and their interaction with some kernel...
RGWAS.normalPerform normal GWAS (test each single SNP)
RGWAS.normal.interactionPerform normal GWAS including interaction (test each single...
RGWAS.twostepPerform normal GWAS (genome-wide association studies) first,...
RGWAS.twostep.epiPerform normal GWAS (genome-wide association studies) first,...
Rice_geno_mapPhysical map of rice genome
Rice_geno_scoreMarker genotype of rice genome
Rice_haplo_blockPhysical map of rice genome
Rice_phenoPhenotype data of rice field trial
Rice_Zhao_etalRice_Zhao_etal:
score.calcCalculate -log10(p) for single-SNP GWAS
score.calc.epistasis.LRCalculate -log10(p) of epistatic effects by LR test
score.calc.epistasis.LR.MCCalculate -log10(p) of epistatic effects by LR test...
score.calc.epistasis.scoreCalculate -log10(p) of epistatic effects with score test
score.calc.epistasis.score.MCCalculate -log10(p) of epistatic effects with score test...
score.calc.intCalculate -log10(p) for single-SNP GWAS with interaction
score.calc.int.MCCalculate -log10(p) for single-SNP GWAS with interaction...
score.calc.LRCalculate -log10(p) of each SNP-set by the LR test
score.calc.LR.intCalculate -log10(p) of each SNP-set and its interaction with...
score.calc.LR.int.MCCalculate -log10(p) of each SNP-set and its interaction with...
score.calc.LR.MCCalculate -log10(p) of each SNP-set by the LR test...
score.calc.MCCalculate -log10(p) for single-SNP GWAS (multi-cores)
score.calc.scoreCalculate -log10(p) of each SNP-set by the score test
score.calc.score.MCCalculate -log10(p) of each SNP-set by the score test...
score.cppCalculte -log10(p) by score test (slow, for general cases)
score.linker.cppCalculte -log10(p) by score test (fast, for limited cases)
SeeFunction to view the first part of data (like head(), tail())
spectralG.cppPerform spectral decomposition (inplemented by Rcpp)
SS_gwasCalculate some summary statistics of GWAS (genome-wide...
welcome_to_RGWASFunction to greet to users
RAINBOWR documentation built on Sept. 12, 2023, 9:08 a.m.