GMD (version 0.3.3)

plot.gmdm: S3 method for class `gmdm'

Description

S3 method for class gmdm

Usage

"plot"(x, labels, colors, type = NULL, main, ylab = "Fraction", xlab = "Position", label.length.max = 8, label.line.max = 3, cex.text = 1, cex.tickmark = 0.75, if.plot.new = TRUE, ...)

Arguments

x

an object of class gmdm.

labels

a string vector of the same length as x$data, giving the names of the numeric vectors in x$data.

colors

the colors of the discrete distributions; the default is "Dark2" colors in ColorBrewer palettes if not specified.

type

type of plot, as in help("plot", package="graphics").

main

an overall title for the plot. See help("title", package="graphics"); the default title is used if not specified.

ylab

a title for the y axis. See help("title", package="graphics").

xlab

a title for the x axis. See help("title", package="graphics").

label.length.max

numeric, giving the maximum string width allowed in diagonal labels.

label.line.max

numeric, giving the maximum number of lines allowed in diagonal labels.

cex.text

a numerical value giving the amount by which plot text should be magnified relative to the default.

cex.tickmark

a numerical value giving the amount by which tickmarks should be magnified relative to the default.

if.plot.new

logical, indicating whether to start a new plot device.

...

arguments to be passed to methods, see gmdp.

Details

S3 method for class gmdm

References

See help(GMD)

See Also

gmdm, gmdp

Examples

## ------------------------------------------------------------------------
## Example1: CAGE
## ------------------------------------------------------------------------
require("GMD") # load library
data(cage)     # load data

## construct a distance matrix and visualize it
short.labels <- gsub("(.+) \\(.+","\\1",names(cage)) # get short labels
x <- gmdm(cage[1:6],labels=short.labels[1:6])
plot(x)

## Not run: 
# ## ------------------------------------------------------------------------
# ## Example2: ChIP-seq
# ## ------------------------------------------------------------------------
# data(chipseq_mES)   # load data
# data(chipseq_hCD4T) # load data
# 
# ## pairwise distance and alignment based on GMD metric
# plot(gmdm(chipseq_mES,sliding=FALSE))
# 
# ## clustering on spatial distributions of histone modifications
# x <- gmdm(chipseq_hCD4T,sliding=FALSE,resolution=10)
# heatmap.3(x,revC=TRUE)
# ## End(Not run)