flowFP (version 1.30.0)

flowFP: Fingerprint constructor

Description

Constructor for flowFP-class.

Usage

flowFP(fcs, model = NULL, sampleClasses = NULL, ...)

Arguments

fcs

A flowFrame or flowSet for which fingerprint(s) are desired.

model

A model generated with the flowFPModel constructor, or NULL. if NULL, a default model will be silently generated from all instances in x.

sampleClasses

An optional character vector describing modeling classes. If supplied, there must be exactly one element for each flowFrame in the flowSet in x (see Details).

...

If model is NULL, additional arguments are passed on to the model constructor. see flowFPModel for details.

Value

An instance of an object of type flowFP.

Details

A flowFP object is a reduced representation of a flowFrame or flowSet with respect to a flowFPModel. The model is derived by finding multivariate regions containing (nearly) equal numbers of events in a training set using one or more user-specified parameters (e.g. CD45 and Side Scatter). The resulting flowFP represents the probability (i.e. number of events) of the instance(s) in x in each of the bins in the underlying model.

This representation is carried in a slot (called counts) in the object, a matrix in which each row corresponds ordinally to the flowFrames in x. Note that if x is a flowFrame and not a flowSet, the counts matrix will have only 1 row. In any case, each row of the matrix is an individual fingerprint, where the fingerprint elements (columns) have a one-to-one correspondence with the bins in the underlying model.

Another slot in the flowFP object describes the bin index for each event, allowing the user to select events according to their membership in bins. Think of this as "micro-gating".

References

M. Roederer, et. al. (2001) Probability Binning Comparison: A Metric for Quantitating Multivariate Distribution Differences, Cytometry 45, 47-55.

W. Rogers et. al. (2008) Cytometric Fingerprinting: Quantitative Characterization of Multivariate Distributions, Cytometry Part A 73, 430-441.

See Also

flowFP-class, flowFP, flowFPModel-class, flowFPModel

Examples

	# load a flowSet to use as an example.
	# fs <- read.flowSet(your fcs files...)
	data(fs1)
	model <- flowFPModel(fs1, parameters=c(4,5), nRecursions=6)
	
	fp <- flowFP(fs1, model)
	
	plot(fp)