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+++ b/man/Clustexp.Rd
@@ -0,0 +1,82 @@
+% 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)
+}