ColorDendrogram: Color the leaves in a hierarchical clustering dendrogram

In PoiClaClu: Classification and Clustering of Sequencing Data Based on a Poisson Model

Description

Pass in the output of "hclust" and a class label for each observation. A colored dendrogram will result, with the leaf colors indicating the classes.

Usage

ColorDendrogram(hc, y, main = "", branchlength = 0.7, labels = NULL,
xlab = NULL, sub = NULL, ylab = "", cex.main = NULL)

Arguments

hc	The output of running "hclust" on a nxn dissimilarity matrix
y	A vector of n class labels for the observations that were clustered using "hclust". If labels are numeric from 1 to K, then colors will be determine automatically. Otherwise the labels can take the form of colors (e.g. c("red", "red", "orange", "orange")).
main	The main title for the dendrogram.
branchlength	How long to make the colored part of the branches. Adjustment will be needed for each dissimilarity matrix
labels	The labels for the n observations.
xlab	X-axis label.
sub	Sub-x-axis label.
ylab	Y-axis label.
cex.main	The amount by which to enlarge the main title for the figure.

Author(s)

Daniela Witten

Examples

set.seed(1)
dat <- CountDataSet(n=20,p=100,sdsignal=2,K=4,param=10)
dd <- PoissonDistance(dat$x,type="mle")
ColorDendrogram(hclust(dd$dd), y=dat$y, branchlength=10)

PoiClaClu documentation built on May 2, 2019, 8:29 a.m.