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.
plot
plot
function.
counts
countsArgs
points
function.
ratio
ratioArgs
points
function.
fit
fitArgs
points
function.
expect
expectArgs
points
function.
expect
tss
tssArgs
points
function.
threshold
thresholdArgs
abline
function.
rug
rugArgs
rug
function.
baseline
baselineArgs
abline
function.
legend
legendArgs
legend
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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