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+++ b/man/getiClusterBayes.Rd
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+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/getiClusterBayes.R
+\name{getiClusterBayes}
+\alias{getiClusterBayes}
+\title{Get subtypes from iClusterBayes}
+\usage{
+getiClusterBayes(
+  data = NULL,
+  N.clust = NULL,
+  type = rep("gaussian", length(data)),
+  n.burnin = 18000,
+  n.draw = 12000,
+  prior.gamma = rep(0.5, length(data)),
+  sdev = 0.05,
+  thin = 3
+)
+}
+\arguments{
+\item{data}{List of matrices with maximum of 6 subdatasets.}
+
+\item{N.clust}{Number of clusters.}
+
+\item{type}{Data type corresponding to the list of matrics, which can be gaussian, binomial or possion.}
+
+\item{n.burnin}{An integer value to indicate the number of MCMC burnin.}
+
+\item{n.draw}{An integer value to indicate the number of MCMC draw.}
+
+\item{prior.gamma}{A numerical vector to indicate the prior probability for the indicator variable gamma of each subdataset.}
+
+\item{sdev}{A numerical value to indicate the standard deviation of random walk proposal for the latent variable.}
+
+\item{thin}{A numerical value to thin the MCMC chain in order to reduce autocorrelation.}
+}
+\value{
+A list with the following components:
+
+        \code{fit}       an object returned by \link[iClusterPlus]{iClusterBayes}.
+
+        \code{clust.res} a data.frame storing sample ID and corresponding clusters.
+
+        \code{feat.res}  the results of features selection process.
+
+        \code{mo.method} a string value indicating the method used for multi-omics integrative clustering.
+}
+\description{
+This function wraps the iClusterBayes (Integrative clustering by Bayesian latent variable model) algorithm and provides standard output for `getMoHeatmap()` and `getConsensusMOIC()`.
+}
+\examples{
+# There is no example and please refer to vignette.
+}
+\references{
+Mo Q, Shen R, Guo C, Vannucci M, Chan KS, Hilsenbeck SG (2018). A fully Bayesian latent variable model for integrative clustering analysis of multi-type omics data. Biostatistics, 19(1):71-86.
+}