Class "norm2Filter"

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Description

Class and constructors for a filter that fits a bivariate normal distribution to a data set of paired values and selects data points according to their standard deviation from the fitted distribution.

Usage

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norm2Filter(x, y, method="covMcd", scale.factor=1, n=50000,
filterId="defaultNorm2Filter")

Arguments

x,y

Characters giving the names of the measurement parameter on which the filter is supposed to work on. y can be missing in which case x is expected to be a character vector of length 2 or a list of characters.

filterId

An optional parameter that sets the filterId slot of this filter. The object can later be identified by this name.

scale.factor, n

Numerics of length 1, used to set the scale.factor and n slots of the object.

method

Character in covMcd or cov.rob, used to set the method slot of the object.

Details

The filter fits a bivariate normal distribution to the data and selects all events within the Mahalanobis distance multiplied by the scale.factor argument. The constructor norm2Filter is a convenience function for object instantiation. Evaluating a curv2Filter results in an object of class logicalFilterResult. Accordingly, norm2Filters can be used to subset and to split flow cytometry data sets.

Value

Returns a norm2Filter object for use in filtering flowFrames or other flow cytometry objects.

Extends

Class "parameterFilter", directly.

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

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

Slots

method:

One of covMcd or cov.rob defining method used for computation of covariance matrix.

scale.factor:

Numeric vector giving factor of standard deviations used for data selection (all points within scalefac standard deviations are selected).

n:

Object of class "numeric", the number of events used to compute the covariance matrix of the bivariate distribution.

filterId:

Object of class "character" referencing the filter.

parameters:

Object of class "ANY" describing the parameters used to filter the flowFrame or flowSet.

Objects from the Class

Objects can be created by calls of the form new("norm2Filter", ...) or using the constructor norm2Filter. The constructor is the recommended way of object instantiation:

Methods

%in%

signature(x = "flowFrame", table = "norm2Filter"): 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 = "norm2Filter"): Print information about the filter.

Note

See the documentation in the flowViz package for plotting of norm2Filters.

Author(s)

F. Hahne

See Also

cov.rob, CovMcd, filter for evaluation of norm2Filters and split and Subsetfor splitting and subsetting of flow cytometry data sets based on that.

Examples

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

## Create directly. Most likely from a command line
norm2Filter("FSC-H", "SSC-H", filterId="myCurv2Filter")

## To facilitate programmatic construction we also have the following
n2f <- norm2Filter(filterId="myNorm2Filter", x=list("FSC-H", "SSC-H"),
scale.factor=2)
n2f <- norm2Filter(filterId="myNorm2Filter", x=c("FSC-H", "SSC-H"),
scale.factor=2)

## Filtering using norm2Filter
fres <- filter(dat, n2f)
fres
summary(fres)

## The result of norm2 filtering is a logical subset
Subset(dat, fres)

## We can also split, in which case we get those events in and those
## not in the gate as separate populations
split(dat, fres)

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