
Shows the peak profiles of samples in a
TRAMPsamples
object, showing
the locations and heights of peaks for individual enzyme/primer
combinations. This is the same information that is displayed in the
bottom portion of a plot.TRAMP
plot, but may be useful
where a TRAMP
fit has not been performed yet
(e.g. before a knowns database has been constructed).
# S3 method for TRAMPsamples
plot(x, sample.fk, ...)
TRAMPsamples.plotone(x, sample.fk, all.samples.global=FALSE, col=1:10,
xmax=NULL, mar.default=.5, mar.labels=8, cex=1)
A TRAMPsamples
object, containing profiles to
plot.
The sample.fk
to plot. If omitted, then all
samples are plotted, one after the other (this is useful for
generating a summary of all fits for printing out: see Example).
Logical: Should plots be set up for all
enzyme/primer combinations present in x
, even if the
combinations are not present for all individual cases? Analagous to
the same argument in plot.TRAMP
. (This is useful for
keeping combinations in the same place, and plotted with the same
colours.)
Vector of colours to plot the different enzyme/primer combinations. There must be at least as many colours as there are different combinations.
Maximum size (in base pairs) for the plots to cover.
NULL
(the default) uses the range of all data found in the
TRAMPsamples
object (rounded up to the nearest 100).
NA
will use the range of all data in the current sample.
Margin size (in lines of text) to surround the plot.
Number of lines of text to be used for labels to the left of the plots. Increase this if labels are being truncated.
Scaling factor for text.
Additional arguments (ignored).
plot.TRAMP
, the plotting method for TRAMP
objects, and plot.TRAMPknowns
, for
TRAMPknowns
objects.
# NOT RUN {
data(demo.samples)
plot(demo.samples, 101)
plot(demo.samples, 117)
# }
# NOT RUN {
# Create a PDF file with all profiles:
pdf("all_profiles.pdf")
plot(demo.samples)
dev.off()
# }
Run the code above in your browser using DataLab