% Generated by roxygen2: do not edit by hand

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

\name{Exprmclust}

\alias{Exprmclust}

\alias{Exprmclust,DISCBIO-method}

\alias{Exprmclust,data.frame-method}

\title{Performing Model-based clustering on expression values}

\usage{

Exprmclust(

  object,

  K = 3,

  modelNames = "VVV",

  reduce = TRUE,

  cluster = NULL,

  quiet = FALSE

)

\S4method{Exprmclust}{DISCBIO}(

  object,

  K = 3,

  modelNames = "VVV",

  reduce = TRUE,

  cluster = NULL,

  quiet = FALSE

)

\S4method{Exprmclust}{data.frame}(

  object,

  K = 3,

  modelNames = "VVV",

  reduce = TRUE,

  cluster = NULL,

  quiet = FALSE

)

}

\arguments{

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

\item{K}{An integer vector specifying all possible cluster numbers. Default

is 3.}

\item{modelNames}{model to be used in model-based clustering. By default

"ellipsoidal, varying volume, shape, and orientation" is used.}

\item{reduce}{A logical vector that allows performing the PCA on the

expression data. Default is TRUE.}

\item{cluster}{A vector showing the ID of cells in the clusters.}

\item{quiet}{if `TRUE`, suppresses intermediary output}

}

\value{

If `object` is of class DISCBIO, the output is the same object  with

  the MBclusters slot filled. If the `object` is a data frame, the function

  returns a named list containing the four objects that together correspond

  to the contents of the MBclusters slot.

}

\description{

this function first uses principal component analysis (PCA) to

  reduce dimensionality of original data. It then performs model-based

  clustering on the transformed expression values.

}