boundaryFilter-class {flowCore} | R Documentation |
Class and constructor for data-driven filter
objects
that discard margin events.
boundaryFilter(x, tolerance=.Machine$double.eps, filterId="defaultBoundaryFilter")
x |
Character giving the name of the measurement parameter on which the filter is supposed to work on. This can also be a list containing a single character scalar for programmatic access. |
tolerance |
Numerics scalar, used to set the tolerance
slot of the object. |
filterId |
An optional parameter that sets the filterId
slot of this filter. The object can later be identified by this
name. |
Flow cytomtery instruments usually operate on a given data range, and
the limits of this range are stored as keywords in the FSC
files. Depending on the amplification settings and the dynamic range
of the measured signal, values can occur that are outside of the
measurement range, and most instruments will simply pile those values
at the minimum or maximum range limit. The boundaryFilter
removes these values, either for a single parameter, or for a
combination of parameters. Note that it is often desirable to treat
boundary events on a per-parameter basis, since their values might be
uniformative for one particular channel, but still be useful in all of
the other channels.
The constructor boundaryFilter
is a conveniance function for
object instantiation. Evaluating a boundaryFilter
results in a
single sub-populations, an hence in an object of class
filterResult
.
Returns a boundaryFilter
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.
tolerance
:"numeric"
. The
machine tolerance used to decide whether an event is on the
measurement boundary. Essentially, this is done by evaluating
x>minRange+tolerance & x<maxRange-tolerance
.
Objects can be created by calls of the form new("boundaryFilter",
...)
or using the constructor boundaryFilter
. Using the
constructor is the recommended way of object instantiation:
signature(x = "flowFrame", table =
"boundaryFilter")
: 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 = "boundaryFilter")
: Print
information about the filter.
Florian Hahne
flowFrame
, flowSet
,
filter
for evaluation of
boundaryFilters
and Subset
for 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 boundaryFilter("FSC-H", filterId="myBoundaryFilter") ## To facilitate programmatic construction we also have the following bf <- boundaryFilter(filterId="myBoundaryFilter", x=list("FSC-H")) ## Filtering using boundaryFilter fres <- filter(dat, bf) fres summary(fres) ## We can subset the data with the result from the filtering operation. Subset(dat, fres)