citrus.clusterAndMapFolds: Cluster independent folds of data

View source: R/citrus.cluster.R

citrus.clusterAndMapFoldsR Documentation

Cluster independent folds of data

Description

Cluster subsets of data from different samples and maps leftout sample data to fold cluster space.

Usage

citrus.clusterAndMapFolds(citrus.combinedFCSSet, clusteringColumns,
  labels = NULL, nFolds = 1, ...)

print.citrus.foldClustering(citrus.foldClustering)

Arguments

citrus.combinedFCSSet

A citrus.combinedFCSSet object.

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 nFolds=1, all data are clustered together and model is regression model is constructed from single feature set.

...

Other arguments passed to specific clustering functions.

Value

A citrus.foldClustering object

folds

Indicies of sample rows to be omitted during each fold of clustering. Only defined if nFolds > 1.

foldClustering

citrus.clustering objects for each fold. Only defined if nFolds > 1.

foldMappingAssignments

citrus.mapping objects for each fold, containing mapping of data from left-out samples. Only defined if nFolds > 1

allClustering

citrus.clusteringObject from all sample data.

nFolds

Number of independent folds.

Author(s)

Robert Bruggner

Examples

# 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)

nolanlab/citrus documentation built on April 30, 2022, 3:24 a.m.