simPlot | R Documentation |
Plot of similarity matrix.
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, ...)
x |
quadratic data matrix. |
col |
colors palette for image. If missing, the |
minVal |
numeric, minimum value which is display by a color; used to adjust |
labels |
vector of character strings to be placed at the tickpoints,
labels for the columns of |
lab.both.axes |
logical, display labels on both axes |
labcols |
colors to be used for the labels of the columns of |
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. |
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. |
cex.axis.bar |
The magnification to be used for axis annotation of the color
bar relative to the current setting of 'cex'; cf.
|
signifBar |
integer indicating the precision to be used for the bar. |
... |
graphical parameters may also be supplied as arguments to the
function (see |
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
.
invisible()
The function is a slight modification of function corPlot
of package MKmisc.
Matthias Kohl Matthias.Kohl@stamats.de
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
## 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)
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