"plotMD"(object, column = 1, xlab = "Average log CPM (this sample and others)", ylab = "log-ratio (this sample vs others)", main = colnames(object)[column], status=object$genes$Status, zero.weights = FALSE, prior.count = 3, ...)
"plotMD"(object, column = ncol(object), coef = NULL, xlab = "Average log CPM", ylab = "log-fold-change", main = colnames(object)[column], status=object$genes$Status, zero.weights = FALSE, ...)
"plotMD"(object, xlab = "Average log CPM", ylab = "log-fold-change", main = object$comparison, status=object$genes$Status, ...)DGEList, DGEGLM, DGEGLM or DGEExact.object to be plotted.column for fitted model objects. If specified, then column is ignored.object.
If NULL, then all points are plotted in the default color, symbol and size.plotWithHighlights.For DGEList objects, a between-sample MD-plot is produced.
Counts are first converted to log2-CPM values.
An articifial array is produced by averaging all the samples other than the sample specified.
A mean-difference plot is then producing from the specified sample and the artificial sample.
This procedure reduces to an ordinary mean-difference plot when there are just two arrays total.
If object is an DGEGLM object, then the plot is an fitted model MD-plot in which the estimated coefficient is on the y-axis and the average logCPM value is on the x-axis.
If object is an DGEExact or DGELRT object, then the MD-plot displays the logFC vs the logCPM values from the results table.
The status vector can correspond to any grouping of the probes that is of interest.
If object is a fitted model object, then status vector is often used to indicate statistically significance, so that differentially expressed points are highlighted.
The status can be included as the component object$genes$Status instead of being passed as an argument to plotMD.
See plotWithHighlights for how to set colors and graphics parameters for the highlighted and non-highlighted points.
plotSmearThe driver function for plotMD is plotWithHighlights.