| madPlot {SLmisc} | R Documentation |
Plot of similarity matrix based on MAD between microarrays.
madPlot(x, new = FALSE, col = grey(50:0/50), maxMAD = 3, labels = FALSE,
labcols = "black", title = "", protocol = FALSE, ...)
x |
data or correlation matrix, respectively |
new |
If new=FALSE, x must already be a matrix with MAD
values. If new=TRUE, the MAD matrix for the columns of
x is computed and displayed in the image. |
col |
colors palette for image |
maxMAD |
maximum MAD value displayed |
labels |
vector of character strings to be placed at the tickpoints,
labels for the columns of x. |
labcols |
colors to be used for the labels of the columns of x.
labcols can have either length 1, in which case all
the labels are displayed using the same color, or the same
length as labels, in which case a color is specified
for the label of each column of x. |
title |
character string, overall title for the plot. |
protocol |
logical, display color bar without numbers |
... |
graphical parameters may also be supplied as arguments to the
function (see par). For comparison purposes,
it is good to set zlim=c(-1,1). |
This functions generates the so called similarity matrix (based on MAD) for
a microarray experiment; cf. Buness et. al. (2004). The function is similar
to corPlot and plot.cor, respectively.
Dr. Matthias Kohl (SIRS-Lab GmbH) kohl@sirs-lab.com
Sandrine Dudoit, Yee Hwa (Jean) Yang, Benjamin Milo Bolstad and with
contributions from Natalie Thorne, Ingrid Lönnstedt and Jessica Mar.
sma: Statistical Microarray Analysis.
http://www.stat.berkeley.edu/users/terry/zarray/Html/smacode.html
Andreas Buness, Wolfgang Huber, Klaus Steiner, Holger Sueltmann, and Annemarie Poustka. arrayMagic: two-colour cDNA microarray quality control and preprocessing. Bioinformatics Advance Access published on September 28, 2004. doi:10.1093/bioinformatics/bti052
plot.cor, corPlot
## only a dummy example M <- madMatrix(matrix(rnorm(1000), ncol = 10)) madPlot(M)