qqplot-methods: Quantile-Quantile Plots

Description Usage Arguments Details Value Author(s) References See Also Examples

Description

Functions for visualizing association test results by means of a quantile-quantile (Q-Q) plot

Usage

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## S4 method for signature 'AssocTestResultRanges,missing'
qqplot(x, y,
       xlab=deparse(substitute(x)), ylab=deparse(substitute(y)),
       common.scale=TRUE, preserveLabels=FALSE, lwd=1,
       lcol="red", ...)
## S4 method for signature 'AssocTestResultRanges,AssocTestResultRanges'
qqplot(x, y,
       xlab=deparse(substitute(x)), ylab=deparse(substitute(y)),
       common.scale=TRUE, preserveLabels=FALSE, lwd=1,
       lcol="red", ...)

Arguments

x,y

objects of class AssocTestResultRanges

xlab

if preserveLabels is TRUE, xlab is interpreted as axis label for the horizontal axis; if preserveLabels is FALSE, xlab can be a character string or expression that is interpreted as a name/label for the object x and is used for determining an appropriate axis label.

ylab

if preserveLabels is TRUE, ylab is interpreted as axis label for the vertical axis; if preserveLabels is FALSE, ylab can be a character string or expression that is interpreted as a name/label for the object y and is used for determining an appropriate axis label.

common.scale

if TRUE (default), the same plotting ranges are used for both axes; if FALSE, the two axes are scaled independently.

preserveLabels

if TRUE, xlab and ylab are used as axis labels without any change; if FALSE (default), the function interprets xlab and ylab as object labels for x and y and uses them for determining axis labels appropriately

lwd

line width for drawing the diagonal line which theoretically corresponds to the equality of the two distributions; if zero, no diagonal line is drawn.

lcol

color for drawing the diagonal line

...

all other arguments are passed to plot;

Details

If qqplot is called for an AssocTestResultRanges object without specifying the second argument y, a Q-Q plot of the raw p-values in x against a uniform distribution of expected p-values is created, where the theoretical p-values are computed using the ppoints function. In this case, the log-transformed observed p-values contained in x are plotted on the vertical axis and the log-transformed expected p-values are plotted on the horizontal axis. If preserveLabels is TRUE, xlab and ylab are used as axis labels as usual. However, if preserveLabels is FALSE, which is the default, xlab is interpreted as object label for x, i.e. the object whose p-values are plotted on the vertical axis.

If qqplot is called for two AssocTestResultRanges object x and y, the log-transformed raw p-values of x and y are plotted against each other, where the p-values of x are plotted on the horizontal axis and the p-values of x are plotted on the vertical axis.

Value

like the standard qqplot function from the stats package, qqplot returns an invisible list containing the two sorted vectors of p-values.

Author(s)

Ulrich Bodenhofer bodenhofer@bioinf.jku.at

References

http://www.bioinf.jku.at/software/podkat

See Also

AssocTestResultRanges

Examples

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## load genome description
data(hgA)

## partition genome into overlapping windows
windows <- partitionRegions(hgA)

## load genotype data from VCF file
vcfFile <- system.file("examples/example1.vcf.gz", package="podkat")
Z <- readGenotypeMatrix(vcfFile)

## read phenotype data from CSV file (continuous trait + covariates)
phenoFile <- system.file("examples/example1lin.csv", package="podkat")
pheno <-read.table(phenoFile, header=TRUE, sep=",")

## train null model with all covariates in data frame 'pheno'
nm.lin <- nullModel(y ~ ., pheno)

## perform association tests
res.p <- assocTest(Z, nm.lin, windows, kernel="linear.podkat")
res.s <- assocTest(Z, nm.lin, windows, kernel="linear.SKAT")

## plot results
qqplot(res.p)
qqplot(res.p, res.s, xlab="PODKAT results", ylab="SKAT results")
qqplot(res.p, res.s, xlab="PODKAT results", ylab="SKAT results",
       preserveLabels=TRUE)
qqplot(res.p, res.s, common.scale=FALSE)

podkat documentation built on Nov. 8, 2020, 6:55 p.m.