qtcatQtc: Summarize results of Hierarchical Inference Test

In QTCAT/qtcat: Quantitative Trait Cluster Association Test

Description

Summarizing the QTCs (significant cluster of SNPs) and their position at the genome.

Usage

qtcatQtc(object, alpha = 0.05, min.absCor = 0.05)

Arguments

object	an object of class qtcatHit.
alpha	an alpha level for significance estimation.
min.absCor	a minimum absolute value of correlation to be considered.

Examples

# If you want to run the examples, use:
# example(qtcatQtc, run.dontrun = TRUE)
## Not run: 
# files containing example data for SNP data and the phenotype
pfile <- system.file("extdata/phenodata.csv", package = "qtcat")
gfile <- system.file("extdata/snpdata.csv", package = "qtcat")
pdat <- read.csv(pfile, header = TRUE)
snp <- read.snpData(gfile, sep = ",")
clust <- qtcatClust(snp)
geno <- qtcatGeno(snp, clust)
pheno <- qtcatPheno(names = pdat[, 1],
                    pheno = pdat[, 2],
                    covariates = model.matrix(~ pdat[, 3]))
fitted <- qtcatHit(pheno, geno)

# Summarizing the QTCs (loci37, loci260, and loci367 are causal)
qtcatQtc(fitted)

## End(Not run)

QTCAT/qtcat documentation built on April 20, 2021, 11:20 p.m.