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)