split,flowClust-method {flowClust}R Documentation

Splitting Data Based on Clustering Results

Description

This method splits data according to results of the clustering (filtering) operation. Outliers identified will be removed by default.

Usage

## S4 method for signature 'ANY, flowClust':
split(x, f, split, select, rm.outliers=TRUE)

## S4 method for signature 'flowFrame, tmixFilterResult':
split(x, f, split, select, rm.outliers=TRUE)

Arguments

x A numeric vector, matrix, data frame of observations, or object of class flowFrame. This is the object on which flowClust or filter was performed.
f Object returned from flowClust or filter.
split An optional argument which specifies how to split the data. If specified, it takes a list object with named or unnamed elements each of which is a numeric vector specifying which clusters are included. When this argument is missing, the data object will be split into K subsets each of which is formed by one out of the K clusters used to model the data. See examples for more details.
select An optional argument which facilitates the selection of columns. If specified, it either takes a numeric (not supported when x is of class flowFrame) or character vector.
rm.outliers A logical value indicating whether outliers will be removed or not.

Value

A list object with elements each of which is a subset of x and also retains the same class as x. If the split argument is specified with a list of named elements, those names will be used to name the corresponding elements in the resultant list object.

Author(s)

Raphael Gottardo <raph@stat.ubc.ca>, Kenneth Lo <c.lo@stat.ubc.ca>

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

Subset, flowClust, filter


[Package flowClust version 1.3.2 Index]