MKmisc (version 1.9)

madPlot: Plot of similarity matrix based on MAD

Description

Plot of similarity matrix based on MAD between microarrays.

Usage

madPlot(x, new = FALSE, col, maxMAD = 3, labels = FALSE, 
        labcols = "black", title = "", protocol = FALSE, ...)

Arguments

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. If missing, the RdYlGn palette of RColorBrewer is used.

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).

Author

Matthias Kohl

Details

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.

References

Sandrine Dudoit, Yee Hwa (Jean) Yang, Benjamin Milo Bolstad and with contributions from Natalie Thorne, Ingrid Loennstedt and Jessica Mar. sma: Statistical Microarray Analysis.
http://www.stat.berkeley.edu/users/terry/zarray/Software/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

See Also

corPlot

Examples

## only a dummy example
set.seed(13)
x <- matrix(rnorm(1000), ncol = 10)
x[1:20,5] <- x[1:20,5] + 10
madPlot(x, new = TRUE, maxMAD = 2.5)
## in contrast
corPlot(x, new = TRUE, minCor = -0.5)