runHclust: runHclust

In CytoTree: A Toolkit for Flow And Mass Cytometry Data

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	a 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

A 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

CytoTree documentation built on Nov. 10, 2020, 2 a.m.