fuzzPlot {ClueR} | R Documentation |
Visualize fuzzy clustering results
Description
Takes in a time-course matrix and its clustering results as a cmeans clustering object. Produce a plot to visualize the clustering results.
Usage
fuzzPlot(
Tc,
clustObj,
mfrow = c(1, 1),
cols,
min.mem = 0,
new.window = FALSE,
llwd = 3
)
Arguments
Tc |
a numeric matrix to be clustered. The columns correspond to the time-course and the rows correspond to phosphorylation sites. |
clustObj |
the clustering of Tc generated from cmeans or kmeans clustering. |
mfrow |
control the subplots in graphic window. |
cols |
color palette to be used for plotting. If the color argument remains empty, the default palette is used. |
min.mem |
phosphorylation sites with membership values below min.mem will not be displayed. |
new.window |
should a new window be opened for graphics. |
llwd |
line width. Default is 3. |
Examples
# load the human ES phosphoprotoemics data (Rigbolt et al. Sci Signal. 4(164):rs3, 2011)
data(hES)
# apply cmeans clustering to partition the data into 11 clusters
clustObj <- e1071::cmeans(hES, centers=11, iter.max=50, m=1.25)
# visualize clustering reuslts
fuzzPlot(hES, clustObj, mfrow = c(3,4))
[Package ClueR version 1.4.2 Index]