Genome-Wide Association Study with SNP-Set Methods


[Up] [Top]

Documentation for package ‘RAINBOWR’ version 0.1.14

Help Pages

RAINBOWR-package RAINBOWR: Perform Genome-Wide Asscoiation Study (GWAS) By Kernel-Based Methods
CalcThreshold Function to calculate threshold for GWAS
cumsumPos Function to calculate cumulative position (beyond chromosome)
design.Z Function to generate design matrix (Z)
EM3.cpp Equation of mixed model for multi-kernel (slow, general version)
EM3.linker.cpp Equation of mixed model for multi-kernel (fast, for limited cases)
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 (inplemented by Rcpp)
EMM2.cpp Equation of mixed model for one kernel, EMMA-based method (inplemented by Rcpp)
genesetmap Function to generate map for gene set
genetrait Generate pseudo phenotypic values
MAF.cut Function to remove the minor alleles
make.full Change a matrix to full-rank matrix
manhattan Draw manhattan plot
manhattan.plus Add points of -log10(p) corrected by kernel methods to 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
qq Draw qq plot
RAINBOWR RAINBOWR: Perform Genome-Wide Asscoiation Study (GWAS) By Kernel-Based Methods
RGWAS.epistasis Check epistatic effects by kernel-based GWAS (genome-wide association studies)
RGWAS.menu Print the R code which you should perform for RAINBOWR GWAS
RGWAS.multisnp Testing multiple SNPs simultaneously for GWAS
RGWAS.normal Perform normal GWAS (test each single SNP)
RGWAS.twostep Perform normal GWAS (genome-wide association studies) first, then perform SNP-set GWAS for relatively significant markers
RGWAS.twostep.epi Perform normal GWAS (genome-wide association studies) first, then check epistatic effects for relatively significant markers
Rice_geno_map Physical map of rice genome
Rice_geno_score Marker genotype of rice genome
Rice_pheno Phenotype data of rice field trial
Rice_Zhao_etal Rice_Zhao_etal:
score.calc Calculate -log10(p) for single-SNP GWAS
score.calc.epistasis.LR Calculate -log10(p) of epistatic effects by LR test
score.calc.epistasis.score Calculate -log10(p) of epistatic effects with score test
score.calc.LR Calculate -log10(p) of each SNP-set by the LR test
score.calc.LR.MC Calculate -log10(p) of each SNP-set by the LR test (multi-cores)
score.calc.MC Calculate -log10(p) for single-SNP GWAS (multi-cores)
score.calc.score Calculate -log10(p) of each SNP-set by the score test
score.calc.score.MC Calculate -log10(p) of each SNP-set by the score test (multi-cores)
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 studies) for simulation study
welcome_to_RGWAS Function to greet to users