citrus.buildFoldsEndpointModels: Build models from each fold of clustering

In nolanlab/citrus: Citrus: Identification of stratifying subpopulations in Flow Cytometry Data.

Build models from each fold of clustering

Description

Builds a model from features derived from each independent fold of clustering.

Usage

citrus.buildFoldsEndpointModels(type, citrus.foldFeatureSet, labels,
  regularizationThresholds = NULL, family = "classification", ...)

Arguments

type	Model Type. Valid options are pamr, glmnet, and sam.
labels	Endpoint labels for samples.
regularizationThresholds	Regularization thresholds for penalized models.
family	Family of model to be constructed. Valid options are classification and continuous.
...	Other arguments passed to model-fitting functions.
citrus.foldFeatureSet.	A citrus.foldFeatureSet object.

Value

A list of models, one model fit on each fold's feature set.

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)

# Build fold features and leftout features
citrus.foldFeatureSet = citrus.calculateFoldFeatureSet(citrus.foldClustering,citrus.combinedFCSSet)

# Build fold models
citrus.foldModels = citrus.buildFoldsEndpointModels(type="pamr",citrus.foldFeatureSet,labels)

nolanlab/citrus documentation built on April 19, 2024, 6:49 p.m.