```
## S3 method for class 'AssocTestResultRanges,missing':
qqplot(x, y,
xlab=deparse(substitute(x)), ylab=deparse(substitute(y)),
common.scale=TRUE, preserveLabels=FALSE, lwd=1,
lcol="red", ...)
## S3 method for class 'AssocTestResultRanges,AssocTestResultRanges':
qqplot(x, y,
xlab=deparse(substitute(x)), ylab=deparse(substitute(y)),
common.scale=TRUE, preserveLabels=FALSE, lwd=1,
lcol="red", ...)
```

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
appropriatelylwd

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`

;- like the standard
`qqplot`

function from thestats package,`qqplot`

returns an invisible list containing the two sorted vectors of p-values.

`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

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.

AssocTestResultRanges

## 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)