meanSdPlot {vsn} | R Documentation |
Methods for objects of classes
matrix
,
ExpressionSet
and
vsn
to plot row standard deviations versus row means.
meanSdPlot(x, ranks = TRUE, xlab = ifelse(ranks, "rank(mean)", "mean"), ylab = "sd", pch = ".", plot = TRUE, ...)
x |
An object of class
matrix ,
ExpressionSet , or
vsn . |
ranks |
Logical, indicating whether the x-axis (means) should be plotted
on the original scale (FALSE ) or on the rank scale (TRUE ). The latter
distributes the data more evenly along the x-axis and allows a
better visual assessment of the standard deviation as a function of
the mean. |
xlab |
Character, label for the x-axis. |
ylab |
Character, label for the y-axis. |
pch |
Plot symbol. |
plot |
Logical. If TRUE (default), a plot is produced.
Calling the function with plot=FALSE can be useful if only
its return value is of interest. |
... |
Further arguments that get passed to plot.default. |
Standard deviation and mean are calculated row-wise from the
expression matrix (in) x
. The scatterplot of these versus each other
allows to visually verify whether there is a dependence of the standard
deviation (or variance) on the mean.
The red dots depict the running median estimator (window-width 10%).
If there is no variance-mean dependence, then the line formed by the
red dots should be approximately horizontal.
A named list with two components, containing x-positions and values of the running median estimator (the red dots in the plot). The methods can also have a side effect, which is to create a plot on the active graphics device.
Wolfgang Huber http://www.ebi.ac.uk/huber
data(kidney) log.na = function(x) log(ifelse(x>0, x, NA)) exprs(kidney) = log.na(exprs(kidney)) meanSdPlot(kidney) ## ...try this out with non-logged data, the lymphoma data, your data...