Class

Class and constructor for n-dimensional ellipsoidal filter objects.

ellipsoidGate(..., .gate, mean, distance=1, filterId="defaultEllipsoidGate")

Arguments

filterId	An optional parameter that sets the `filterId` of this gate.
.gate	A definition of the gate via a covariance matrix.
mean	Numeric vector of equal length as dimensions in `.gate`.
distance	Numeric scalar giving the Mahalanobis distance defining the size of the ellipse. This mostly exists for compliance reasons to the gatingML standard as `mean` and `gate` should already uniquely define the ellipse. Essentially, `distance` is merely a factor that gets applied to the values in the covariance matrix.
...	You can also directly describe the covariance matrix through named arguments, as described below.

Value

Returns a ellipsoidGate object for use in filtering flowFrames or other flow cytometry objects.

Details

A convenience method to facilitate the construction of a ellipsoid filter objects. Ellipsoid gates in n dimensions (n >= 2) are specified by a a covarinace matrix and a vector of mean values giving the center of the ellipse.

This function is designed to be useful in both direct and programmatic usage. In the first case, simply describe the covariance matrix through named arguments. To use this function programmatically, you may pass a covarince matrix and a mean vector directly, in which case the parameter names are the colnames of the matrix.

Slots

mean

Objects of class "numeric". Vector giving the location of the center of the ellipse in n dimensions.

cov

Objects of class "matrix". The covariance matrix defining the shape of the ellipse.

distance

Objects of class "numeric". The Mahalanobis distance defining the size of the ellipse.

parameters

Object of class "character", describing the parameter used to filter the flowFrame.

filterId

Object of class "character", referencing the filter.

Note

See the documentation in the flowViz package for plotting of ellipsoidGates.

Extends

Class "parameterFilter", directly.

Class "concreteFilter", by class parameterFilter, distance 2.

Class "filter", by class parameterFilter, distance 3.

Objects from the Class

Objects can be created by calls of the form new("ellipsoidGate", ...) or by using the constructor ellipsoidGate. Using the constructor is the recommended way.

Methods

%in%

signature(x = "flowFrame", table = "ellipsoidGate"): The workhorse used to evaluate the filter on data. This is usually not called directly by the user, but internally by calls to the filter methods.

show

signature(object = "ellipsoidGate"): Print information about the filter.

Examples


## Loading example data
dat <- read.FCS(system.file("extdata","0877408774.B08",
package="flowCore"))

## Defining the gate
cov <- matrix(c(6879, 3612, 3612, 5215), ncol=2,
dimnames=list(c("FSC-H", "SSC-H"), c("FSC-H", "SSC-H")))
mean <- c("FSC-H"=430, "SSC-H"=175)
eg <- ellipsoidGate(filterId= "myEllipsoidGate", .gate=cov, mean=mean)

## Filtering using ellipsoidGates
fres <- filter(dat, eg)
fres
#> A filterResult produced by the filter named 'myEllipsoidGate'
summary(fres)
#> myEllipsoidGate+: 4209 of 10000 events (42.09%)

## The result of ellipsoid filtering is a logical subset
Subset(dat, fres)
#> flowFrame object '0877408774.B08'
#> with 4209 cells and 8 observables:
#>      name              desc range minRange maxRange
#> $P1 FSC-H             FSC-H  1024 0.000000     1023
#> $P2 SSC-H             SSC-H  1024 0.000000     1023
#> $P3 FL1-H              <NA>  1024 1.009044    10000
#> $P4 FL2-H              <NA>  1024 1.009044    10000
#> $P5 FL3-H              <NA>  1024 1.009044    10000
#> $P6 FL1-A              <NA>  1024 0.000000     1023
#> $P7 FL4-H              <NA>  1024 1.009044    10000
#> $P8  Time Time (51.20 sec.)  1024 0.000000     1023
#> 164 keywords are stored in the 'description' slot

## We can also split, in which case we get those events in and those
## not in the gate as separate populations
split(dat, fres)
#> $`myEllipsoidGate+`
#> flowFrame object '0877408774.B08 (myEllipsoidGate+)'
#> with 4209 cells and 8 observables:
#>      name              desc range minRange maxRange
#> $P1 FSC-H             FSC-H  1024 0.000000     1023
#> $P2 SSC-H             SSC-H  1024 0.000000     1023
#> $P3 FL1-H              <NA>  1024 1.009044    10000
#> $P4 FL2-H              <NA>  1024 1.009044    10000
#> $P5 FL3-H              <NA>  1024 1.009044    10000
#> $P6 FL1-A              <NA>  1024 0.000000     1023
#> $P7 FL4-H              <NA>  1024 1.009044    10000
#> $P8  Time Time (51.20 sec.)  1024 0.000000     1023
#> 164 keywords are stored in the 'description' slot
#> 
#> $`myEllipsoidGate-`
#> flowFrame object '0877408774.B08 (myEllipsoidGate-)'
#> with 5791 cells and 8 observables:
#>      name              desc range minRange maxRange
#> $P1 FSC-H             FSC-H  1024 0.000000     1023
#> $P2 SSC-H             SSC-H  1024 0.000000     1023
#> $P3 FL1-H              <NA>  1024 1.009044    10000
#> $P4 FL2-H              <NA>  1024 1.009044    10000
#> $P5 FL3-H              <NA>  1024 1.009044    10000
#> $P6 FL1-A              <NA>  1024 0.000000     1023
#> $P7 FL4-H              <NA>  1024 1.009044    10000
#> $P8  Time Time (51.20 sec.)  1024 0.000000     1023
#> 164 keywords are stored in the 'description' slot
#> 

##ellipsoidGate can be converted to polygonGate by interpolation
pg <- as(eg, "polygonGate")
pg
#> Polygonal gate 'myEllipsoidGate' with 50 vertices in dimensions FSC-H and SSC-H

Class "ellipsoidGate"