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+++ b/man/runPAM.Rd
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+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/runPAM.R
+\name{runPAM}
+\alias{runPAM}
+\title{Run partition around medoids classifier}
+\usage{
+runPAM(
+  train.expr = NULL,
+  moic.res = NULL,
+  test.expr = NULL,
+  gene.subset = NULL
+)
+}
+\arguments{
+\item{train.expr}{A matrix of normalized expression training data with rows for genes and columns for samples; FPKM or TPM without log2 transformation is recommended.}
+
+\item{moic.res}{An object returned by `getMOIC()` with one specified algorithm or `get\%algorithm_name\%` or `getConsensusMOIC()` with a list of multiple algorithms.}
+
+\item{test.expr}{A matrix of normalized expression testing data with rows for genes and columns for samples; FPKM or TPM without log2 transformation is recommended.}
+
+\item{gene.subset}{A string vector to indicate a subset of genes to be used.}
+}
+\value{
+A list with the following components:
+
+        \code{IGP}        a named numeric vector storing the in-group proportion (see \link[clusterRepro]{IGP.clusterRepro}).
+
+        \code{clust.res}  similar to `clust.res` returned by `getMOIC()` or `get%algorithm_name%` or `getConsensusMOIC()`.
+
+        \code{mo.method}  a string value indicating the method used for prediction.
+}
+\description{
+Using partition around medoids (PAM) classifier to predict potential subtype label on external cohort and calculate in-group proportions (IGP) statistics.
+}
+\details{
+This function first trains a partition around medoids (PAM) classifier in the discovery (training) cohort
+ to predict the subtype for patients in the external validation (testing) cohort,
+ and each sample in the validation cohort was assigned to a subtype label whose centroid had the highest Pearson correlation with the sample.
+ Finally, the in-group proportion (IGP) statistic will be performed to evaluate the similarity and reproducibility of the acquired subtypes between discovery and validation cohorts.
+}
+\examples{
+# There is no example and please refer to vignette.
+}
+\references{
+Tibshirani R, Hastie T, Narasimhan B and Chu G (2002). Diagnosis of multiple cancer types by shrunken centroids of gene expression. Proc Natl Acad Sci, 99,6567–6572.
+
+Kapp A V, Tibshirani R. (2007). Are clusters found in one dataset present in another dataset?. Biostatistics, 8(1):9-31.
+}