filter-methods | R Documentation |
These methods link filter descriptions to a particular set of flow cytometry data allowing for the lightweight calculation of summary statistics common to flow cytometry analysis.
filter(x, filter, method = c("convolution", "recursive"),
sides = 2L, circular = FALSE, init = NULL)
x |
Object of class |
filter |
An object of class |
method , sides , circular , init |
These arguments are not used. |
The filter
method conceptually links a filter description,
represented by a filter
object, to a particular
flowFrame
. This is accomplished via the
filterResult
object, which tracks the linked frame as
well as caching the results of the filtering operation itself, allowing for
fast calculation of certain summary statistics such as the percentage of
events accepted by the filter
. This method exists chiefly to allow
the calculation of these statistics without the need to first
Subset
a flowFrame
, which can be quite
large.
When applying on a flowSet
, the filter
argument can either be
a single filter
object, in which case it is recycled for all frames
in the set, or a named list of filter
objects. The names are supposed
to match the frame identifiers (i.e., the output of sampleNames(x)
of
the flowSet
. If some frames identifiers are missing, the particular
frames are skipped during filtering. Accordingly, all filters
in the
filter list that can't be mapped to the flowSet
are ignored. Note
that all filter
objects in the list must be of the same type, e.g.
rectangleGates
.
A filterResult
object or a
filterResultList
object if x
is a
flowSet
. Note that filterResult
objects are themselves filters, allowing them to be used in filter
expressions or Subset
operations.
F Hahne, B. Ellis, N. Le Meur
Subset
, filter
, filterResult
## Filtering a flowFrame
samp <- read.FCS(system.file("extdata","0877408774.B08", package="flowCore"))
rectGate <- rectangleGate(filterId="nonDebris","FSC-H"=c(200,Inf))
fr <- filter(samp,rectGate)
class(fr)
summary(fr)
## filtering a flowSet
data(GvHD)
foo <- GvHD[1:3]
fr2 <- filter(foo, rectGate)
class(fr2)
summary(fr2)
## filtering a flowSet using different filters for each frame
rg2 <- rectangleGate(filterId="nonDebris","FSC-H"=c(300,Inf))
rg3 <- rectangleGate(filterId="nonDebris","FSC-H"=c(400,Inf))
flist <- list(rectGate, rg2, rg3)
names(flist) <- sampleNames(foo)
fr3 <- filter(foo, flist)
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