citrus.selectClusters.minimumClusterSize: Selects clusters for endpoint analysis

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

Selects clusters for endpoint analysis

Description

Selects clusters for endpoint analysis by cluster size. Selected clusters must have a minimum number of cells in them as a proportion of the total number of clustered events. If n total events are clustered, clusters contatining at least n * minimumClusterSizePercent events are selected.

Usage

citrus.selectClusters.minimumClusterSize(citrus.clustering,
  minimumClusterSizePercent = 0.05, ...)

Arguments

citrus.clustering	A citrus.clustering object.
minimumClusterSizePercent	The percentage 0 < x < 1 of the total number of clustered events a cluster must contain in order to be selected.
...	Other arguments (ignored).

Author(s)

Robert Bruggner

See Also

citrus.selectClusters

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)

# Select clusters that contain at least 1% of clustered events.
largeEnoughClusters = citrus.selectClusters.minimumClusterSize(citrus.clustering,minimumClusterSizePercent=0.01)

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