plotMA.CD {baySeq} | R Documentation |
This function creates an MA-plot from two sets of samples. For those data where the log-ratio is infinite (because in one set of sample data all observed counts are zero), we plot instead the log-values of the other group.
plotMA.CD(cD, samplesA, samplesB, normaliseData = TRUE, scale = NULL, xlab = "A", ylab = "M", ...)
cD |
A |
samplesA |
Either a character vector, identifying sample set A by either
replicate name or sample name, or a numerical vector giving the columns of data in the
|
samplesB |
Either a character vector, identifying sample set B by either
replicate name or sample name, or a numerical vector giving the columns of data in the
|
normaliseData |
Should the data be normalised by library size before computing log-ratios? Defaults to TRUE. |
scale |
If given, defines the scale on which the log-ratios will be plotted. Defaults to NULL, implying that the scale will be calculated by the function. |
xlab |
Label for the X-axis. Defaults to "A". |
ylab |
Label for the Y-axis. Defaults to "M". |
... |
Any other parameters to be passed to the |
The samples sets can be identified either by a numeric vector which
specifies the columns of data from the countData
object 'cD',
or by a character vector. If a character vector is used, the members
of the character vector will first be searched for in the
@replicates
slot of the 'cD' object. Any members of the vector not found
in the replicates slot, will be searched for in the column names of the
@data
slot of the 'cD' object. Different classes of vector can
be used for 'samplesA' and 'samplesB', as shown in the example below.
Plotting function.
Thomas J. Hardcastle
data(simData) replicates <- c("simA", "simA", "simA", "simA", "simA", "simB", "simB", "simB", "simB", "simB") groups <- list(NDE = c(1,1,1,1,1,1,1,1,1,1), DE = c(1,1,1,1,1,2,2,2,2,2)) CD <- new("countData", data = simData, replicates = replicates, groups = groups) #estimate library sizes for countData object libsizes(CD) <- getLibsizes(CD) #MA-plot comparing replicate groups plotMA.CD(CD, samplesA = "simA", samplesB = 6:10)