The colorhcplot
package is a convenient tool for plotting colorful dendrograms where
clusters, or sample groups, are highlighted by different colors. In
order to generate a colorful dendrogram, colorhcplot()
function requires 2 mandatory arguments: hc
and
fac
:
hc
is the result of a hclust()
call
fac
is a factor defining the grouping
The number of leaves of the dendrogram has to be identical to the
length of fac (i.e., length(hc$labels) == length(fac) has to be TRUE).
Also, the optional colors
argument (if supplied) has to
have a length of 1 (single color) or equal to the length of the levels
of fac
.
The first example is based on the USArrests dataset and compares the
results of the standard plot
method applied to a
hclust-class object and the output of colorhcplot()
. The
use of simple arguments is illustrated.
data(USArrests)
hc <- hclust(dist(USArrests), "ave")
fac <- as.factor(c(rep("group 1", 10),
rep("group 2", 10),
rep("unknown", 30)))
plot(hc)
The second example is based on the UScitiesD dataset. Here we show
how to specify custom colors for the colorhcplot()
call,
using the colors
argument.
The third example is based on a sample gene expression dataset, which
is included in the colorhcplot
package. This illustrate how
to use colorhcplot()
for exploration and analysis of
genomic data.
## R version 4.4.1 (2024-06-14)
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## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
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## other attached packages:
## [1] colorhcplot_1.3.1 rmarkdown_2.28
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