Description Usage Arguments Details Value Author(s) References See Also
Creates a mean-difference plot (aka MA plot) with color coding for highlighted points.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ## S3 method for class 'DGEList'
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, ...)
## S3 method for class 'SummarizedExperiment'
plotMD(object, column=1, xlab="Average log CPM (this sample and others)",
ylab="log-ratio (this sample vs others)", zero.weights=FALSE, prior.count=3, ...)
## S3 method for class 'DGEGLM'
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, ...)
## S3 method for class 'DGELRT'
plotMD(object, xlab="Average log CPM", ylab="log-fold-change",
main=object$comparison, status=object$genes$Status, contrast=1,
adjust.method="BH", p.value=0.05, ...)
## S3 method for class 'DGEExact'
plotMD(object, xlab="Average log CPM", ylab="log-fold-change",
main=NULL, status=object$genes$Status,
adjust.method="BH", p.value=0.05, ...)
|
object |
an object of class |
column |
integer, column of |
coef |
alternative to |
xlab |
character string, label for x-axis |
ylab |
character string, label for y-axis |
main |
character string, title for plot |
status |
vector giving the control status of each spot on the array, of same length as the number of rows of |
zero.weights |
logical, should spots with zero or negative weights be plotted? |
prior.count |
the average prior count to be added to each observation. Larger values produce more shrinkage. |
contrast |
integer specifying which log-fold-change to be plotted in the case of testing multiple contrasts. Only used for the |
adjust.method |
character string passed to |
p.value |
numeric value between 0 and 1 giving the desired size of the test. Only used and passed to |
... |
other arguments are passed to |
A mean-difference plot (MD-plot) is a plot of log fold changes (differences) versus average log values (means). The history of mean-difference plots and MA-plots is reviewed in Ritchie et al (2015).
For DGEList
and SummarizedExperiment
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.
A plot is created on the current graphics device.
Gordon Smyth
Ritchie, ME, Phipson, B, Wu, D, Hu, Y, Law, CW, Shi, W, and Smyth, GK (2015). limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Research Volume 43, e47. https://doi.org/10.1093/nar/gkv007
The driver function for plotMD
is plotWithHighlights
.
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