--- a
+++ b/man/DISCBIO.Rd
@@ -0,0 +1,91 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/DIscBIO-classes.R
+\docType{class}
+\name{DISCBIO}
+\alias{DISCBIO}
+\alias{DISCBIO-class,}
+\alias{DISCBIO-class}
+\title{The DISCBIO Class}
+\arguments{
+\item{object}{An DISCBIO object.}
+}
+\description{
+The DISCBIO class is the central object storing all information
+  generated throughout the pipeline.
+}
+\details{
+DISCBIO
+}
+\section{Slots}{
+
+\describe{
+\item{\code{SingleCellExperiment}}{Representation of the single cell input data,
+including both cells from regular and ERCC spike-in samples. Data are
+stored in a SingleCellExperiment object.}
+
+\item{\code{expdata}}{The raw expression data matrix with cells as columns and
+genes as rows in sparse matrix format. It does not contain ERCC spike-ins.}
+
+\item{\code{expdataAll}}{The raw expression data matrix with cells as columns
+and genes as rows in sparse matrix format. It can contain ERCC spike-ins.}
+
+\item{\code{ndata}}{Data with expression normalized to one for each cell.}
+
+\item{\code{fdata}}{Filtered data with expression normalized to one for each
+cell.}
+
+\item{\code{distances}}{A distance matrix.}
+
+\item{\code{tsne}}{A data.frame with coordinates of two-dimensional tsne layout
+for the K-means clustering.}
+
+\item{\code{background}}{A list storing the polynomial fit for the background
+model of gene expression variability. It is used for outlier
+identification.}
+
+\item{\code{out}}{A list storing information on outlier cells used for the
+prediction of rare cell types.}
+
+\item{\code{cpart}}{A vector containing the final clustering partition computed
+by K-means.}
+
+\item{\code{fcol}}{A vector contaning the colour scheme for the clusters.}
+
+\item{\code{filterpar}}{A list containing the parameters used for cell and gene
+filtering based on expression.}
+
+\item{\code{clusterpar}}{A list containing the parameters used for the K-means
+clustering.}
+
+\item{\code{outlierpar}}{A list containing the parameters used for outlier
+identification.}
+
+\item{\code{kmeans}}{A list containing the results of running the Clustexp()
+function.}
+
+\item{\code{MBclusters}}{A vector containing the final clustering partition
+computed by Model-based clustering.}
+
+\item{\code{kordering}}{A vector containing the Pseudo-time ordering based on
+k-means clusters.}
+
+\item{\code{MBordering}}{A vector containing the Pseudo-time ordering based on
+Model-based clusters.}
+
+\item{\code{MBtsne}}{A data.frame with coordinates of two-dimensional tsne
+layout for the Model-based clustering.}
+
+\item{\code{noiseF}}{A vector containing the gene list resulted from running the
+noise filtering.}
+
+\item{\code{FinalGeneList}}{A vector containing the final gene list resulted
+from running the noise filtering or/and the expression filtering.}
+}}
+
+\examples{
+class(valuesG1msTest)
+G1_reclassified <- DISCBIO(valuesG1msTest)
+class(G1_reclassified)
+str(G1_reclassified, max.level = 2)
+identical(G1_reclassified@expdataAll, valuesG1msTest)
+}