plotQtc: Plot resulting QTCs of the Hierarchical Inference Test

In QTCAT/qtcat: Quantitative Trait Cluster Association Test

Description

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

Usage

plotQtc(x, alpha = 0.05, xlab = "Chromosomes",
  ylab = expression(-log[10](italic(p))), col.axis = NULL, ...)

Arguments

x	an object of class qtcatHit.
alpha	an alpha level for significance estimation.
xlab	a title for the x axis.
ylab	a title for the y axis.
col.axis	colors for axis line, tick marks, and title respectively.
...	other graphical parameters may also be passed as arguments to this function.

Examples

# If you want to run the examples, use:
# example(plotQtc, 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)

# Plot the QTCs (loci37, loci260, and loci367 are causal)
plotQtc(fitted)

## End(Not run)

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