kmeansFilter-class {flowCore} | R Documentation |
A filter that performs one-dimensional k-means (Lloyd-Max) clustering on a single flow parameter.
kmeansFilter(..., filterId="defaultKmeansFilter")
... |
or
If the parameter is not fully realized, but instead is the result of a
|
filterId |
An optional parameter that sets the |
The one-dimensional k-means filter is a multiple population filter
capable of operating on a single flow parameter. It takes a parameter
argument associated with two or more populations and results in the
generation of an object of class multipleFilterResult
.
Populations are considered to be ordered such that the population with
the smallest mean intensity will be the first population in the list
and the population with the highest mean intensity will be the last
population listed.
Returns a kmeansFilter
object for use in filtering
flowFrames
or other flow cytometry
objects.
Class parameterFilter
, directly.
Class concreteFilter
, by class
parameterFilter
, distance 2.
Class filter
, by class parameterFilter
,
distance3.
populations
:Object of class character
. The
names of the k
populations (or clusters) that will be
created by the kmeansFilter
. These names will later be used
for the respective subpopulations in split
operations and for the summary of the filterResult
.
parameters
:Object of class parameters
,
defining a single parameter for which the data in the
flowFrame
is to be clustered. This may also
be a transformation
object.
filterId
:Object of class character
, an
identifier or name to reference the kmeansFilter
object
later on.
Like all other filter
objects in flowCore
,
kmeansFilter
objects should be instantiated through their
constructor kmeansFilter()
. See the Usage
section for
details.
signature(x = "flowFrame", table =
"kmeansFilter")
: The workhorse used to evaluate the filter on
data.
Usage:
This is usually not called directly by the user, but internally by
the filter
methods.
signature(object = "kmeansFilter")
: Print
information about the filter.
Usage:
The method is called automatically whenever the object is printed on the screen.
See the documentation in the
flowViz
package for plotting of
kmeansFilters
.
F. Hahne, B. Ellis, N. LeMeur
flowFrame
, flowSet
, filter
for evaluation of kmeansFilters
and split
for
splitting of flow cytometry data sets based on the result of the
filtering operation.
## Loading example data dat <- read.FCS(system.file("extdata","0877408774.B08", package="flowCore")) ## Create the filter kf <- kmeansFilter("FSC-H"=c("Pop1","Pop2","Pop3"), filterId="myKmFilter") ## Filtering using kmeansFilters fres <- filter(dat, kf) fres summary(fres) names(fres) ## The result of quadGate filtering are multiple sub-populations ## and we can split our data set accordingly split(dat, fres) ## We can limit the splitting to one or several sub-populations split(dat, fres, population="Pop1") split(dat, fres, population=list(keep=c("Pop1","Pop2")))