deGate: 1D density gating method
In flowDensity: Sequential Flow Cytometry Data Gating

Description Usage Arguments Value Author(s) See Also Examples

View source: R/flowDensity_methods.R

Find the best threshold for a single channel in flow cytometry data based on its density distribution.

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deGate(obj,channel, n.sd = 1.5, use.percentile = FALSE,  percentile = 0.95,use.upper=FALSE, upper = NA,verbose=TRUE,twin.factor=.98, bimodal=F,after.peak=NA,alpha = 0.1, sd.threshold = FALSE,
all.cuts = FALSE, tinypeak.removal=1/25,node=NA, adjust.dens = 1,count.lim=20,magnitude=.3, ...)

`obj`	obj: a 'FlowFrame' object, 'CellPopulation' or 'GatingHierarchy'
`channel`	a channel's name or its corresponding index in the 'flow.frame'.
`n.sd`	an integer coefficient for the standard deviation to determine the threshold based on the standard deviation if 'sd.threshold' is TRUE.
`use.percentile`	if TRUE, forces to return the 'percentile'th threshold.
`percentile`	a value in [0,1] that is used as the percentile. The default value is 0.95.
`use.upper`	Logical. If TRUE, forces to return the inflection point based on the first (last) peak if upper=F (upper=T). Default value is set to 'FALSE'
`upper`	if TRUE, finds the change in the slope at the tail of the density curve, if FALSE, finds it at the head. Default value is set to 'NA'.
`verbose`	Logical. If TRUE, Prints a message if only one peak is found, or when inflection point is used to set the gates.
`twin.factor`	a value in [0,1] that is used to exclude twinpeaks
`bimodal`	Logical. If TRUE, it returns a cutoff that splits population closer to 50-50, when there are more than two peaks.
`after.peak`	Logical. If TRUE, it returns a cutoff that is after the maximum peaks, when there are more than two peaks.
`alpha`	a value in [0,1) specifying the significance of change in the slope being detected. This is by default 0.1, and typically need not be changed.
`sd.threshold`	if TRUE, uses 'n.sd' times standard deviation as the threshold. Default value is set to 'FALSE'.
`all.cuts`	if TRUE, returns all the identified cutoff points, i.e. potential thresholds for that channel. Default value is set to 'FALSE'.
`tinypeak.removal`	A number in [0,1] to exclude/include tiny peaks in density distribution.
`node`	A character defining the parent population when extracting data from GatingHierarchy.
`adjust.dens`	The smoothness of density in [0,Inf] to be used in density(.). The default value is 1 and should not be changed unless necessary
`count.lim`	minimum limit for events count in order to calculate the threshold. Default is 20, returning NA as threshold.
`magnitude`	A value between 0 and 1, for tracking a slope and reporting changes that are smaller than magnitude*peak_height
`...`	Extra arguments to be passed to smoothSpline function.

an integer value (vector) of cutoff(s), i.e. threshold(s), on the specified channel

Mehrnoush Malek <[email protected]>

getflowFrame notSubFrame flowDensity

data_dir <- system.file("extdata", package = "flowDensity")
load(list.files(pattern = 'sampleFCS_1', data_dir, full = TRUE))
#Find the threshold for CD20
cd19.gate <- deGate(f,channel="PerCP-Cy5-5-A")
# Gate out the CD20- populations using the notSubFrame
plotDens(f,c("APC-H7-A","PerCP-Cy5-5-A"))
abline(h=cd19.gate,lty=3,col=2)