It simply constructs an boundaryFilter that removes the marginal events. It can be passed directly to ggcyto constructor. See the examples for details.

marginalFilter(fs, dims, ...)

Arguments

fs

flowSet (not used.)

dims

the channels involved

...

arguments passed to boundaryFilter

Value

an boundaryFilter

Examples

data(GvHD) fs <- GvHD[1] chnls <- c("FSC-H", "SSC-H") #before removign marginal events summary(fs[, chnls])
#> $s5a01 #> FSC-H SSC-H #> Min. 59.0000 6.0000 #> 1st Qu. 115.0000 82.0000 #> Median 197.0000 145.5000 #> Mean 245.2456 202.8588 #> 3rd Qu. 338.0000 237.0000 #> Max. 1023.0000 1023.0000 #>
# create merginal filter g <- marginalFilter(fs, chnls) g
#> boundaryFilter 'defaultBoundaryFilter' operating on channels: #> FSC-H (tolerance=2.22e-16, boundary=both) #> SSC-H (tolerance=2.22e-16, boundary=both)
#after remove marginal events fs.clean <- Subset(fs, g) summary(fs.clean[, chnls])
#> $s5a01 #> FSC-H SSC-H #> Min. 59.0000 6.0000 #> 1st Qu. 114.0000 80.0000 #> Median 193.0000 142.0000 #> Mean 236.7293 185.7215 #> 3rd Qu. 331.0000 228.0000 #> Max. 943.0000 1009.0000 #>
#pass the function directly to ggcyto dataDir <- system.file("extdata",package="flowWorkspaceData") gs <- load_gs(list.files(dataDir, pattern = "gs_manual",full = TRUE)) # with marginal events ggcyto(gs, aes(x = CD4, y = CD8), subset = "CD3+") + geom_hex(bins = 64)
# using marginalFilter to remove these events ggcyto(gs, aes(x = CD4, y = CD8), subset = "CD3+", filter = marginalFilter) + geom_hex(bins = 64)