Map: Cluster Assignment Based on Clustering Results

In flowClust: Clustering for Flow Cytometry

Description

This method performs cluster assignment according to the posterior probabilities of clustering memberships resulted from the clustering (filtering) operations. Outliers identified will be left unassigned by default.

Usage

Map(f, ...)

## S4 method for signature 'flowClust'
Map(f, rm.outliers = TRUE, ...)

## S4 method for signature 'flowClustList'
Map(f, rm.outliers = TRUE, ...)

Arguments

f	Object returned from flowClust or filter.
...	Further arguments to be passed to or from other methods.
rm.outliers	A logical value indicating whether outliers will be left unassigned or not.

Value

A numeric vector of size N (the number of observations) indicating to which cluster each observation is assigned. Unassigned observations will be labelled as NA.

Note

Even if rm.outliers is set to FALSE, NA may still appear in the resultant vector due to the filtered observations; see the descriptions about the min.count, max.count, min and max arguments of flowClust.

Author(s)

Raphael Gottardo <[e-mail]>, Kenneth Lo <[e-mail]>

References

Lo, K., Brinkman, R. R. and Gottardo, R. (2008) Automated Gating of Flow Cytometry Data via Robust Model-based Clustering. Cytometry A 73, 321-332.

See Also

flowClust, filter, posterior

flowClust documentation built on Nov. 8, 2020, 7:34 p.m.