--- a
+++ b/man/ClassVectoringDT.Rd
@@ -0,0 +1,53 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/DIscBIO-generic-ClassVectoringDT.R
+\name{ClassVectoringDT}
+\alias{ClassVectoringDT}
+\alias{ClassVectoringDT,DISCBIO-method}
+\title{Generating a class vector to be used for the decision tree analysis.}
+\usage{
+ClassVectoringDT(
+  object,
+  Clustering = "K-means",
+  K,
+  First = "CL1",
+  Second = "CL2",
+  sigDEG,
+  quiet = FALSE
+)
+
+\S4method{ClassVectoringDT}{DISCBIO}(
+  object,
+  Clustering = "K-means",
+  K,
+  First = "CL1",
+  Second = "CL2",
+  sigDEG,
+  quiet = FALSE
+)
+}
+\arguments{
+\item{object}{\code{DISCBIO} class object.}
+
+\item{Clustering}{Clustering has to be one of the following: ["K-means",
+"MB"]. Default is "K-means"}
+
+\item{K}{A numeric value of the number of clusters.}
+
+\item{First}{A string vector showing the first target cluster.  Default is
+"CL1"}
+
+\item{Second}{A string vector showing the second target cluster.  Default is
+"CL2"}
+
+\item{sigDEG}{A data frame of the differentially expressed genes (DEGs)
+generated by running "DEGanalysis()" or "DEGanalysisM()".}
+
+\item{quiet}{If `TRUE`, suppresses intermediary output}
+}
+\value{
+A data frame.
+}
+\description{
+This function generates a class vector for the input dataset so
+  the decision tree analysis can be implemented afterwards.
+}