plot(x, y, ...)TssData, TssNorm, or
TssResult.signature(x="TssData")
plot(x, y, counts=TRUE, legend=TRUE, ...) signature(x="TssNorm")
plot(x, y, counts=TRUE, ratio=TRUE, fit=TRUE, legend=TRUE,
...) signature(x="TssResult")
plot(x, y, counts=TRUE, ratio=TRUE, fit=TRUE, expect=FALSE,
tss=TRUE, threshold=TRUE, rug=TRUE, legend=TRUE, ...) plot method, the raw, normalized, or final data can
easily be visualized. The plot method uses a special system in order to customize the
graphical elements of the figure. It allows to refer to the different
components with the name of the additional input argument; its value
is a list containing named graphical parameters for the underlying
plot function. The following list describes the available names and
their contribution.
plotplot function.
counts
countsArgspoints function.
ratio
ratioArgspoints function.
fit
fitArgspoints function.
expect
expectArgspoints function.
expect
tss
tssArgspoints function.
threshold
thresholdArgsabline function.
rug
rugArgsrug function.
baseline
baselineArgsabline function.
legend
legendArgslegend function.
Thus, for (a) omitting the ratio estimates, the threshold, and the
legend, (b) customizing the graphical parameters of the raw read
counts, (c) customizing the axis labels and the title, the following
code can be used:
plot(x, 1, ratio=FALSE, threshold=FALSE, legend=FALSE,
countsArgs=list(type="h", col="darkgray", pch=NA),
plotArgs=list(xlab="Genomic position", main="TSS for segment
's1_-_155'")
TssData, TssNorm,
TssResult
Methods:
segmentizeCounts, normalizeCounts,
identifyStartSites, get-methods,
plot-methods, asRangedData-methods Functions:
subtract-functions
Data set:
physcoCounts
Package:
TSSi-package
## preceding steps
example(identifyStartSites)
## plot
plot(yFit, 1)
## plot w/ some custom settings
plot(z, 1, ratio=FALSE, threshold=FALSE, countsArgs=list(type="h",
col="darkgray", pch=NA), plotArgs=list(xlab="Genomic position",
main="TSS for segment 's1_-_155'"))
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