plot-methods: Plot methods
In TSSi: Transcription Start Site Identification

Description Usage Arguments Details Methods Author(s) See Also Examples

Plot the data and results of the TSSi package.

1	plot(x, y, ...)

`x`	An object of class `TssData`, `TssNorm`, or `TssResult`.
`y`	A single integer or character string specifying which segment to plot. An integer is interpreted as the index of the segment while a character string is matched against the segment names.
`...`	Optional arguments used in order to customize the figure. See the ‘details’ section.

With the 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: Graphical parameters for the axes and the labeling, passed to the plot function.
counts: Logical indicating whether the raw counts should be plotted.
countsArgs: Graphical parameters for the ‘counts’ variable, passed to the points function.
ratio: Logical indicating whether the estimates based on the Poisson ratios should be plotted.
ratioArgs: Graphical parameters for the ‘ratio’ variable, passed to the points function.
fit: Logical indicating whether the estimates based on the fitting should be plotted.
fitArgs: Graphical parameters for the ‘fit’ variable, passed to the points function.
expect: Logical indicating whether the background estimates should be plotted.
expectArgs: Graphical parameters for the ‘expect’ variable, passed to the points function.
expect: Logical indicating whether the background estimates should be computed for all positions, rather than only for those with reads.
tss: Logical indicating whether the identified TSS should be plotted.
tssArgs: Graphical parameters for the ‘tss’ variable, passed to the points function.
threshold: Logical indicating whether the threshold parameter used in the identification step should be indicated.
thresholdArgs: Graphical parameters for the ‘threshold’ variable, passed to the abline function.
rug: Logical indicating whether the location of the identified TSS should be indicated.
rugArgs: Graphical parameters for the ‘rug’ variable, passed to the rug function.
baseline: Logical indicating whether a baseline indicating zero reads should be drawn.
baselineArgs: Graphical parameters for the ‘baseline’ variable, passed to the abline function.
legend: Logical indicating whether a legend should be plotted.
legendArgs: Graphical parameters for the ‘legend’ variable, passed to the 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'")

Visualize the raw data:

plot:: signature(x="TssData")

plot(x, y, counts=TRUE, legend=TRUE, ...)

Visualize the normalized data:

plot:: signature(x="TssNorm")

plot(x, y, counts=TRUE, ratio=TRUE, fit=TRUE, legend=TRUE, ...)

Visualize the normalized data along with the identified TSS:

plot:: signature(x="TssResult")

plot(x, y, counts=TRUE, ratio=TRUE, fit=TRUE, expect=FALSE, tss=TRUE, threshold=TRUE, rug=TRUE, legend=TRUE, ...)

Maintainer: Julian Gehring <julian.gehring@fdm.uni-freiburg.de>

Classes: 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'"))