\title{Cluster samples from an IcaSet}
  clusterSamplesByComp(icaSet, params,
    funClus = c("Mclust", "kmeans", "pam", "pamk", "hclust", "agnes"),
    filename, clusterOn = c("A", "S"),
    level = c("genes", "features"), nbClus,
    metric = "euclidean", method = "ward", ...)
  \item{icaSet}{An \code{IcaSet} object}

  \item{params}{A \code{MineICAParams} object}

  \item{funClus}{The function to be used for clustering,
  must be one of

  \item{filename}{A file name to write the results of the
  clustering in}

  \item{clusterOn}{Specifies the matrix used to apply
  clustering: \describe{ \item{\code{"A"}:}{the clustering
  is performed in one dimension, on the vector of sample
  contributions,} \item{"S":}{the clustering is performed
  on the original data restricted to the contributing

  \item{level}{The level of projections to be used when
  \code{clusterOn="S"}, either \code{"features"} or

  \item{nbClus}{The number of clusters to be computed,
  either a single number or a numeric vector whose length
  equals the number of components. If missing (only allowed
  if \code{funClus} is one of \code{c("Mclust","pamk")})}

  \item{metric}{Metric used in \code{pam} and
  \code{hclust}, default is \code{"euclidean"}}

  \item{method}{Method of hierarchical clustering, used in
  \code{hclust} and \code{agnes}}

  \item{...}{Additional parameters required by the
  clustering function \code{funClus}.res <-
  clusterSamplesByComp(icaSet=icaSetCarbayo, params=params,
  A list consisting of three elements
  \describe{\item{clus:}{a list specifying the sample
  clustering for each component,}\item{resClus:}{the
  complete output of the clustering
  function,}\item{funClus:}{the function used to perform
  the clustering.}}. When \code{clusterOn="S"}, if some
  components were not used because no contributing elements
  is selected using the cutoff, the icaSet with the
  corresponding component deleted is also returned.
  This function allows to cluster samples according to the
  results of an ICA decomposition. One clustering is run
  independently for each component.
params <- buildMineICAParams(resPath="carbayo/", selCutoff=4)

## cluster samples according to their contributions
# using Mclust without a number of clusters
res <- clusterSamplesByComp(icaSet=icaSetCarbayo, params=params, funClus="Mclust",
                            clusterOn="A", filename="clusA")

# using kmeans
res <- clusterSamplesByComp(icaSet=icaSetCarbayo, params=params, funClus="kmeans",
                            clusterOn="A", nbClus=2, filename="clusA")
  Anne Biton
  \code{Mclust}, \code{kmeans}, \code{pam}, \code{pamk},
  \code{hclust}, \code{agnes}, \code{cutree}