View source: R/citrus.cluster.R
| citrus.clusterAndMapFolds | R Documentation | 
Cluster subsets of data from different samples and maps leftout sample data to fold cluster space.
citrus.clusterAndMapFolds(citrus.combinedFCSSet, clusteringColumns,
  labels = NULL, nFolds = 1, ...)
print.citrus.foldClustering(citrus.foldClustering)
| citrus.combinedFCSSet | A  | 
| clusteringColumns | Vector of parameter names or indicies to be used for clustering. | 
| labels | Labels of samples being clustered. If supplied, used for balancing folds for clustering | 
| nFolds | Number of independent folds of clustering to perform. If  | 
| ... | Other arguments passed to specific clustering functions. | 
A citrus.foldClustering object
| folds | Indicies of sample rows to be omitted during each fold of clustering. Only defined if  | 
| foldClustering | 
 | 
| foldMappingAssignments | 
 | 
| allClustering | 
 | 
| nFolds | Number of independent folds. | 
Robert Bruggner
# Where the data lives
dataDirectory = file.path(system.file(package = "citrus"),"extdata","example1")
# Create list of files to be analyzed
fileList = data.frame("unstim"=list.files(dataDirectory,pattern=".fcs"))
# Read the data
citrus.combinedFCSSet = citrus.readFCSSet(dataDirectory,fileList)
# List disease group of each sample
labels = factor(rep(c("Healthy","Diseased"),each=10))
# List of columns to be used for clustering
clusteringColumns = c("Red","Blue")
# Cluster each fold
citrus.foldClustering = citrus.clusterAndMapFolds(citrus.combinedFCSSet,clusteringColumns,labels,nFolds=4)
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