imageplot {limma} | R Documentation |
Creates an image of shades of gray or colours, that represents the values of a statistic for each spot on the array. The statistic can be a log intensity ratio, quality information such as spot size or shape, or a t-statistic. This function can be used to explore whether there are any spatial effects in the data.
imageplot(z, layout, low = NULL, high = NULL, ncolors = 123, zerocenter = NULL, zlim = NULL, mar=rep(1,4), ...)
z |
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. |
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 . |
... |
any other arguments will be passed to the function image |
The image follows the layout of an actual microarray slide with the bottom left corner representing the spot (1,1,1,1).
This function is very similar to the sma
function plot.spatial
but is intended
to display spatial patterns and artefacts rather than to highlight extreme
values. The function 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.
An image is created on the current graphics device.
Gordon Smyth
An overview of diagnostic functions available in LIMMA is given in 7.Diagnostics.
M <- rnorm(8*4*16*16) imageplot(M,layout=list(ngrid.r=8,ngrid.c=4,nspot.r=16,nspot.c=16))