meanSdPlot {vsn} | R Documentation |
Plot row standard deviations versus row means
meanSdPlot(x, ranks = TRUE, xlab = ifelse(ranks, "rank(mean)", "mean"), ylab = "sd", pch = ".", col, ...)
x |
An object of class matrix or
exprSet |
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. |
col |
Color of plotted points. See details. |
... |
Further arguments that get passed to plot.default. |
Standard deviation and mean are calculated row-wise from the
matrix exprs(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.
If the preprocessing
slot of the description
slot of
x
is a list
and contains an element named
vsnTrimSelection
, then the coloring of the points reflects
the trimming that was used in the least trimmed sum of squares (LTS)
estimation (see vsn
). If the condition does not apply,
and col
is NULL
, the points are drawn in black. If
col
is not NULL
, its value is used for the coloring of
the points.
The function is called for its side effect, creating a plot on the active graphics device.
Wolfgang Huber http://www.dkfz.de/abt0840/whuber
data(kidney) exprs(kidney) = log.na(exprs(kidney)) meanSdPlot(kidney) ## ...try this out with non-logged data, the lymphoma data, your data...