plotDistributions {arrayMagic} | R Documentation |
Boxplot like visualisation of distributions, only the boxes,
i.e. the median and the second and third quartile are plotted
(cf. boxplot.stats
for the details on the calculation).
The plots may help to identify shortcomings of the raw data
or normalised data. The argument quantiles
can be used
to visualize two or three arbitrary quantiles with boxes.
plotDistributions(dataMatrix, transFunc, quantiles, main, labels, xlab, ylab, colourVector, width=8, height=6, fileName="plotDistributionsOutput", savePath, plotOutput="standard")
dataMatrix |
numeric data matrix, where columns represent distributions, e.g. raw array data or normalised data; required; default missing |
transFunc |
unary function; optional; default missing. Data transformation function, e.g. log |
quantiles |
missing by default; a vector of two or three increasing quantiles used to determine the boxes to be drawn |
main |
plot title; type character string; optional; default missing |
labels |
vector of names, may substitute column names
of dataMatrix ; optional; default missing |
xlab |
label for x axis; type character string; optional; default missing |
ylab |
label for y axis; type character string; optional; default missing |
colourVector |
vector of colours; optional; default missing |
width |
graphics window width; required; default: 8 |
height |
graphics window height; required; default: 6 |
fileName |
optional; default: "plotDistributionsOutput" |
savePath |
optional; default: missing |
plotOutput |
character string specifying either "standard", "screen", "pdf", "win.metafile"; default: "standard" |
Default of transFunc
is no transformation, i.e. identity.
If labels
are supplied at first the column names or
secondly a numbering are used instead.
By default the colourVector
is defined as alternating
"darkred" and "darkgreen".
The function is called for its side effect.
Andreas Buness <a.buness@dkfz.de>
boxplot.stats
plotDistributions(cbind(rnorm(100),rnorm(100)), main="Random Gaussians", labels = c("N1","N2"), ylab="scale") plotDistributions(as.matrix(1:100), quantiles=c(0.25,0.85), main = "Random Gaussians", labels = c("N1"), ylab = "scale")