spade (version 1.20.0)

SPADE.FCSToTree: Cluster and build minimum spanning tree from data in FCS files

Description

Hierarchically cluster observations in a set of FCS files and build a minimum spanning tree connecting those clusters.

Usage

SPADE.FCSToTree(infilenames, outfilename, graphfilename, clusterfilename,
		  cols = NULL, k = 200, arcsinh_cofactor=NULL, transforms=flowCore::arcsinhTransform(a=0, b=0.2), 
		  desired_samples = 50000, comp=TRUE)

Arguments

infilenames

Vector of FCS file names that should be used as input

outfilename

Name of FCS file to write subset of cells used for clustering along with their cluster assignment

graphfilename

Name of file to write gml graph description

clusterfilename

Name of file to write table of cluster centers

cols

Usually a vector of strings specifying the columns to be used in the density calculation, e.g., c("(Cd110)D","(Cs111)D"). Strings will be matched against the parameter names extracted from the FCS file. The default=NULL will use all parameters.

k

Desired number of clusters. Algorithm might create between [k/2,3k/2] clusters.

arcsinh_cofactor

DEPRECATED. Cofactor used in arcsinh transform asinh(data/arcsinh_cofactor) of data.

transforms

Transform object to apply to data. A single transform object will be applied to all channels. To apply different transforms to specific channels use a named vector of transform objects (where names are parameter names).

desired_samples

Desired number of samples to be used in clustering. Usually leave at default.

comp

Apply compensation matrix if present in SPILL or SPILLOVER keywords

Value

None.

See Also

SPADE.downsampleFCS

Examples

	## Load two-parameters sample data included in package
	#data_file_path = paste(installed.packages()["spade","LibPath"],"spade","extdata","SimulatedRawData.fcs",sep=.Platform$file.sep)

	#output_dir <- tempdir()
	#
	## Compute and annotate FCS file with density
	#density_file_path <- paste(output_dir,.Platform$file.sep,basename(data_file_path),".density.fcs",sep="")
	#SPADE.addDensityToFCS(data_file_path, density_file_path, cols=c("marker1","marker2"))

	## Downsample FCS file based on density
	#downsample_file_path <- paste(output_dir,.Platform$file.sep,basename(data_file_path),".density.fcs",sep="")
	#SPADE.downsampleFCS(density_file_path, downsample_file_path)

	## Create tree from downsampled FCS file
	#cells_file_path <- paste(output_dir,"clusters.fcs",sep="")
	#clust_file_path <- paste(output_dir,"clusters.table",sep="")
	#graph_file_path <- paste(output_dir,"mst.gml",sep="")
	#SPADE.FCSToTree(downsample_file_path, cells_file_path, graph_file_path, clust_file_path, cols=c("marker1","marker2"))