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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