Description Usage Arguments Details Value See Also Examples
Several gene-based association tests methods are implemented.
1 2 3 |
x |
a vector of SNP-level P values. |
cor_G |
SNP-SNP correlation matrix. |
vegas.pct |
a numeric vector, specifying the fraction of the top SNPs to be used in the VEGAS method. |
max.simulation |
maximum number of simulations to be performed. Must be at least 1e6. |
pca_cut_perc |
cutoff for percentage of sum of eigen values. |
Function gates
implements the GATES method (Li et al 2011, American Journal of Human Genetics 88:283-293), vegas
implements VEGAS with different proportion tests (Liu et al 2010, American Journal of Human Genetics 87:139-145), and simpleM
is the simpleM method (Gao et al 2008, Genetic Epidemiology 32:361-369).
P value(s).
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | # read SNP P values
file1 <- paste(path.package("COMBAT"),"extdata","SNP_info.txt.gz",sep="/")
snp.info <- read.table(file1, header = TRUE, as.is=TRUE)
snp.pvals <- as.matrix(snp.info[,2])
# read reference genotype
file2 <- paste(path.package("COMBAT"),"extdata","SNP_ref.txt.gz",sep="/")
snp.ref <- read.table(file2, header = TRUE)
snp.ref <- as.matrix(snp.ref)
#compute correlation among SNPs
cor_G <- ld.Rsquare(snp.ref)
#call gates
(pval_gates <- gates(x=snp.pvals, cor_G=cor_G))
#call vegas
(pval_vegas <- vegas(x=snp.pvals, cor_G=cor_G))
#call simpleM
(pval_simpleM <- simpleM(x=snp.pvals, cor_G=cor_G))
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