fuzzPlot: Visualize fuzzy clustering results

In ClueR: Cluster Evaluation

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))

ClueR documentation built on Nov. 16, 2023, 5:08 p.m.