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+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/getConsensusClustering.R
+\name{getConsensusClustering}
+\alias{getConsensusClustering}
+\title{Get subtypes from ConsensusClustering}
+\usage{
+getConsensusClustering(
+  data = NULL,
+  N.clust = NULL,
+  type = rep("gaussian", length(data)),
+  norMethod = "none",
+  reps = 500,
+  pItem = 0.8,
+  pFeature = 0.8,
+  clusterAlg = "hc",
+  innerLinkage = "ward.D",
+  finalLinkage = "ward.D",
+  distance = "pearson",
+  plot = NULL,
+  writeTable = F,
+  title = file.path(getwd(), "consensuscluster"),
+  seed = 123456,
+  verbose = F
+)
+}
+\arguments{
+\item{data}{List of matrices.}
+
+\item{N.clust}{Number of clusters.}
+
+\item{type}{Data type corresponding to the list of matrics, which can be gaussian, binomial or possion.}
+
+\item{norMethod}{A string vector indicate the normalization method for consensus clustering.}
+
+\item{reps}{An integer value to indicate the number of subsamples.}
+
+\item{pItem}{A numerical value to indicate the proportion of items to sample.}
+
+\item{pFeature}{A numerical value to indicate the proportion of features to sample.}
+
+\item{clusterAlg}{A string value to indicate the cluster algorithm.}
+
+\item{innerLinkage}{A string value to indicate the heirachical linakge method for subsampling.}
+
+\item{finalLinkage}{A string value to indicate the heirarchical method for consensus matrix.}
+
+\item{distance}{A string value to indicate the distance function.}
+
+\item{plot}{A string value to indicate the output format for heatmap.}
+
+\item{writeTable}{A logical value to indicate if writing output and log to csv.}
+
+\item{title}{A string value for output directory.}
+
+\item{seed}{A numerical value to set random seed for reproducible results.}
+
+\item{verbose}{A logical value to indicate if printing messages to the screen to indicate progress.}
+}
+\value{
+A list with the following components:
+
+        \code{fit}        an object returned by \link[ConsensusClusterPlus]{ConsensusClusterPlus}.
+
+        \code{clust.res}  a data.frame storing sample ID and corresponding clusters.
+
+        \code{clust.dend} a dendrogram of sample clustering.
+
+        \code{mo.method}  a string value indicating the method used for multi-omics integrative clustering.
+}
+\description{
+This function wraps the Consensus Clustering algorithm and provides standard output for `getMoHeatmap()` and `getConsensusMOIC()`.
+}
+\examples{
+# There is no example and please refer to vignette.
+}
+\references{
+Monti S, Tamayo P, Mesirov J, et al (2003). Consensus Clustering: A Resampling-Based Method for Class Discovery and Visualization of Gene Expression Microarray Data. Mach Learn, 52:91-118.
+}