\Header{meanSdPlot}{Plot row standard deviations versus row means}
\keyword{hplot}{meanSdPlot}
\begin{Description}\relax
Plot row standard deviations versus row means
\end{Description}
\begin{Usage}
\begin{verbatim}
meanSdPlot(x, 
           ranks = TRUE,
           xlab  = ifelse(ranks, "rank(mean)", "mean"),
           ylab  = "sd",
           pch   = ".",
           col, ...)\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{x}] An object of class \code{\Link{matrix}} or
\code{\Link{exprSet}}
\item[\code{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.
\item[\code{xlab}] Character, label for the x-axis.
\item[\code{ylab}] Character, label for the y-axis.
\item[\code{pch}] Plot symbol.
\item[\code{col}] Color of plotted points. See details.
\item[\code{...}] Further arguments that get passed to plot.default.
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
Standard deviation and mean are calculated row-wise from the
matrix \code{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 \code{preprocessing} slot of the \code{description} slot of
\code{x} is a \code{\Link{list}} and contains an element named
\code{vsnTrimSelection}, then the coloring of the points reflects
the trimming that was used in the least trimmed sum of squares (LTS)
estimation (see \code{\Link{vsn}}). If the condition does not apply,
and \code{col} is \code{NULL}, the points are drawn in black. If
\code{col} is not \code{NULL}, its value is used for the coloring of
the points.
\end{Details}
\begin{Value}
The function is called for its side effect, creating a plot on the
active graphics device.
\end{Value}
\begin{Author}\relax
Wolfgang Huber \url{http://www.dkfz.de/abt0840/whuber}
\end{Author}
\begin{SeeAlso}\relax
\code{\Link{vsn}}
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
  data(kidney)
  exprs(kidney) = log.na(exprs(kidney))

  meanSdPlot(kidney)

  ## ...try this out with non-logged data, the lymphoma data, your data...
\end{ExampleCode}
\end{Examples}

