MKmisc (version 1.9)

simPlot: Plot of a similarity matrix.

Description

Plot of similarity matrix.

Usage

simPlot(x, col, minVal, labels = FALSE, lab.both.axes = FALSE, 
          labcols = "black", title = "", cex.title = 1.2, 
          protocol = FALSE, cex.axis = 0.8, 
          cex.axis.bar = 1, signifBar = 2, ...)

Value

invisible()

Arguments

x

quadratic data matrix.

col

colors palette for image. If missing, the RdYlGn palette of RColorBrewer is used.

minVal

numeric, minimum value which is display by a color; used to adjust col

labels

vector of character strings to be placed at the tickpoints, labels for the columns of x.

lab.both.axes

logical, display labels on both axes

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.

cex.title

A numerical value giving the amount by which plotting text and symbols should be magnified relative to the default; cf. par, cex.main.

protocol

logical, display color bar without numbers

cex.axis

The magnification to be used for axis annotation relative to the current setting of 'cex'; cf. par.

cex.axis.bar

The magnification to be used for axis annotation of the color bar relative to the current setting of 'cex'; cf. par.

signifBar

integer indicating the precision to be used for the bar.

...

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 a so called similarity matrix.

If min(x) is smaller than minVal, the colors in col are adjusted such that the minimum value which is color coded is equal to minVal.

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

Examples

## only a dummy example
M <- matrix(rnorm(1000), ncol = 20)
colnames(M) <- paste("Sample", 1:20)
M.cor <- cor(M)

simPlot(M.cor, minVal = min(M.cor))
simPlot(M.cor, minVal = min(M.cor), lab.both.axes = TRUE)
simPlot(M.cor, minVal = min(M.cor), protocol = TRUE)
simPlot(M.cor, minVal = min(M.cor), signifBar = 1)