% Generated by roxygen2: do not edit by hand

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

\docType{methods}

\name{Clustexp}

\alias{Clustexp}

\alias{Clustexp,DISCBIO-method}

\title{Clustering of single-cell transcriptome data}

\usage{

Clustexp(

  object,

  clustnr = 3,

  bootnr = 50,

  metric = "pearson",

  do.gap = TRUE,

  SE.method = "Tibs2001SEmax",

  SE.factor = 0.25,

  B.gap = 50,

  cln = 0,

  rseed = NULL,

  quiet = FALSE

)

\S4method{Clustexp}{DISCBIO}(

  object,

  clustnr = 3,

  bootnr = 50,

  metric = "pearson",

  do.gap = TRUE,

  SE.method = "Tibs2001SEmax",

  SE.factor = 0.25,

  B.gap = 50,

  cln = 0,

  rseed = NULL,

  quiet = FALSE

)

}

\arguments{

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

\item{clustnr}{Maximum number of clusters for the derivation of the cluster

number by the saturation of mean within-cluster-dispersion. Default is 20.}

\item{bootnr}{A numeric value of booststrapping runs for \code{clusterboot}.

Default is 50.}

\item{metric}{Is the method to transform the input data to a distance object.

Metric has to be one of the following: ["spearman", "pearson", "kendall",

"euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski"].}

\item{do.gap}{A logical vector that allows generating the number of clusters

based on the gap statistics. Default is TRUE.}

\item{SE.method}{The SE.method determines the first local maximum of the gap

statistics. The SE.method has to be one of the following:["firstSEmax",

"Tibs2001SEmax", "globalSEmax", "firstmax", "globalmax"]. Default is

"Tibs2001SEmax"}

\item{SE.factor}{A numeric value of the fraction of the standard deviation by

which the local maximum is required to differ from the neighboring points

it is compared to. Default is 0.25.}

\item{B.gap}{Number of bootstrap runs for the calculation of the gap

statistics. Default is 50}

\item{cln}{Number of clusters to be used. Default is \code{NULL} and the

cluster number is inferred by the saturation criterion.}

\item{rseed}{Random integer to enforce reproducible clustering results.}

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

}

\value{

The DISCBIO-class object input with the cpart slot filled.

}

\description{

This functions performs the initial clustering of the RaceID

  algorithm.

}

\examples{

sc <- DISCBIO(valuesG1msTest) # changes signature of data

sc <- Clustexp(sc, cln = 2)

}