runHclust {CytoTree}R Documentation

runHclust

Description

Hierarchical cluster analysis on a set of dissimilarities and methods for analyzing it.

Usage

runHclust(
  object,
  k = 25,
  hclust.method = "complete",
  dist.method = "euclidean",
  verbose = FALSE
)

Arguments

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 function(x) hclust(x,method = 'ward.D2').

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 function(x) as.dist((1-cor(t(x)))/2).

verbose

logical. Whether to print calculation progress.

Value

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)

See Also

hclust, dist


[Package CytoTree version 1.4.0 Index]