citrus.cluster: Cluster a 'citrus.combinedFCSSet'

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

Cluster a citrus.combinedFCSSet

Description

Cluster data in a citrus.combinedFCS set object

Usage

citrus.cluster(citrus.combinedFCSSet, clusteringColumns,
  clusteringType = "hierarchical", ...)

print.citrus.clustering(citrus.clustering)

Arguments

citrus.combinedFCSSet	A citrus.combinedFCSSet object.
clusteringColumns	Vector of names or indicies of data to be used for clustering.
clusteringType	Type of clustering to be perfomed. Valid options are: hierarchical.
...	Other arguments passed to specific clustering algorithm.

Value

A citrus.clustering object.

clustering	Clustering object returned by clustering algorithm.
clusterMembership	List, containing indicies of cells in citrus.combinedFCSSet data that belong to each cluster.
type	Type of clustering performed.
clusteringColumns	Parameters used for clustering

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 of columns to be used for clustering
clusteringColumns = c("Red","Blue")

# Cluster data
citrus.clustering = citrus.cluster(citrus.combinedFCSSet,clusteringColumns)

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