norm2Filter-class {flowCore} | R Documentation |
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.
norm2Filter(x, y, method="covMcd", scale.factor=1, n=50000, filterId="defaultNorm2Filter")
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. |
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
conveniance 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.
Returns a norm2Filter
object for use in filtering
flowFrame
s or other flow cytometry objects.
Class "parameterFilter"
, directly.
Class "concreteFilter"
, by class
parameterFilter
, distance 2.
Class "filter"
, by class parameterFilter
,
distance 3.
method
:covMcd
or cov.rob
defining method used for computation of covariance matrix.scale.factor
:scalefac
standard deviations are selected).transformation
:"list"
containing transform
objects, if applicable
they are applied to the data before filteringn
:"numeric"
, the number of
events used to compute the covariance matrix of the bivariate
distribution.filterId
:"character"
referencing the filter. parameters
:"ANY"
describing
the parameters used to filter the flowFrame
or
flowSet
.
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:
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. signature(object = "norm2Filter")
: Print
information about the filter.
See the documentation in the
flowViz
package for plotting of
norm2Filters
.
F. Hahne
cov.rob
,
covMcd
, filter
for evaluation of norm2Filters
and split
and
Subset
for splitting and subsetting of flow cytometry
data sets based on that.
## 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)