runHclust {CytoTree} | R Documentation |
Hierarchical cluster analysis on a set of dissimilarities and methods for analyzing it.
runHclust( object, k = 25, hclust.method = "complete", dist.method = "euclidean", verbose = FALSE )
object |
an CYT object |
k |
numeric. The number of clusters. |
hclust.method |
character or a function. The agglomeration method to be used.
This should be one of "ward.D", "ward.D2", "single", "complete", "average",
"mcquitty", "median" or "centroid". Or you can specify an equation as input, for example
|
dist.method |
character or a function. The distance measure to be used.
This must be one of "euclidean", "maximum", "manhattan", "canberra", "binary"
or "minkowski". Or you can specify an equation as input, for example
|
verbose |
logical. Whether to print calculation progress. |
An CYT object with cluster
cyt.file <- system.file("extdata/cyt.rds", package = "CytoTree") cyt <- readRDS(file = cyt.file)
cyt <- runHclust(cyt, k = 9, verbose = TRUE)