% Generated by roxygen2: do not edit by hand

% Please edit documentation in R/DIscBIO-generic-clustheatmap.R

\name{clustheatmap}

\alias{clustheatmap}

\alias{clustheatmap,DISCBIO-method}

\title{Plotting clusters in a heatmap representation of the cell distances}

\usage{

clustheatmap(

  object,

  clustering_method = "k-means",

  hmethod = "single",

  rseed = NULL,

  quiet = FALSE,

  plot = TRUE

)

\S4method{clustheatmap}{DISCBIO}(

  object,

  clustering_method = "k-means",

  hmethod = "single",

  rseed = NULL,

  quiet = FALSE,

  plot = TRUE

)

}

\arguments{

\item{object}{\code{DISCBIO} class object.}

\item{clustering_method}{either "k-means" or "model-based" ("k" and "mb" are

also accepted)}

\item{hmethod}{Agglomeration method used for determining the cluster order

from hierarchical clustering of the cluster medoids. This should be one of

"ward.D", "ward.D2", "single", "complete", "average". Default is "single".}

\item{rseed}{Random integer to fix random results.}

\item{quiet}{if `TRUE`, intermediary output is suppressed}

\item{plot}{if `TRUE`, plots the heatmap; otherwise, just prints cclmo}

}

\value{

Unless otherwise specified, a heatmap and a vector of the underlying

  cluster order.

}

\description{

This functions plots a heatmap of the distance matrix grouped

  by clusters. Individual clusters are highlighted with rainbow colors along

  the x and y-axes.

}