Creates an image of colors or shades of gray that represent the values of a
statistic for each spot on a spotted microarray.
This function can be used to explore any spatial effects across the microarray.
numeric vector or array. This vector can contain any spot
statistics, such
as log intensity ratios, spot sizes or shapes, or t-statistics. Missing values
are allowed and will result in blank spots on the image.
Infinite values are not allowed.
layout
a list specifying the dimensions of the spot matrix
and the grid matrix.
low
color associated with low values of z. May be specified as a character string
such as "green", "white" etc, or as a rgb vector in which c(1,0,0) is red,
c(0,1,0) is green and c(0,0,1) is blue. The default value is "green" if zerocenter=T or "white" if zerocenter=F.
high
color associated with high values of z. The default value is "red" if zerocenter=T or "blue" if zerocenter=F.
ncolors
number of color shades used in the image including low and high.
zerocenter
should zero values of z correspond to a shade exactly halfway between the colors
low and high? The default is TRUE if z takes positive and negative values,
otherwise FALSE.
zlim
numerical vector of length 2 giving the extreme values of z to associate with
colors low and high. By default zlim is the range of z. Any values of z outside
the interval zlim will be truncated to the relevant limit.
mar
numeric vector of length 4 specifying the width of the margin around the plot.
This argument is passed to par.
legend
logical, if TRUE the range of z and zlim is shown in the bottom margin
...
any other arguments will be passed to the function image
Details
This function may be used to plot the values of any spot-specific statistic, such as the log intensity ratio, background intensity or a quality
measure such as spot size or shape.
The image follows the layout of an actual microarray slide with the bottom left corner representing the spot (1,1,1,1).
The color range is used to represent the range of values for the statistic.
When this function is used to plot the red/green log-ratios, it is intended to be an in silico version of the classic false-colored red-yellow-green image of a scanned two-color microarray.
This function is related to the earlier plot.spatial function in the sma package and to the later maImage function in the marray package.
It differs from plot.spatial most noticeably in that all the spots are plotted and the image is plotted from bottom left rather than from top left.
It is intended to display spatial patterns and artefacts rather than to highlight only the extreme values as does plot.spatial.
It differs from maImage in that any statistic may be plotted and in its use of a red-yellow-green color scheme for log-ratios, similar to the classic false-colored jpeg image, rather than the red-black-green color scheme associated with heat maps.
Value
An plot is created on the current graphics device.
Author(s)
Gordon Smyth
See Also
maImage in the marray package, image in the graphics package.
An overview of diagnostic functions available in LIMMA is given in 09.Diagnostics.
Examples
M <- rnorm(8*4*16*16)
imageplot(M,layout=list(ngrid.r=8,ngrid.c=4,nspot.r=16,nspot.c=16))
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(limma)
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/limma/imageplot.Rd_%03d_medium.png", width=480, height=480)
> ### Name: imageplot
> ### Title: Image Plot of Microarray Statistics
> ### Aliases: imageplot
> ### Keywords: hplot
>
> ### ** Examples
>
> M <- rnorm(8*4*16*16)
> imageplot(M,layout=list(ngrid.r=8,ngrid.c=4,nspot.r=16,nspot.c=16))
>
>
>
>
>
> dev.off()
null device
1
>