gate_mindensity: Determines a cutpoint as the minimum point of a kernel...

In RGLab/openCyto: Hierarchical Gating Pipeline for flow cytometry data

Determines a cutpoint as the minimum point of a kernel density estimate between two peaks

Description

We fit a kernel density estimator to the cells in the flowFrame and identify the two largest peaks. We then select as the cutpoint the value at which the minimum density is attained between the two peaks of interest.

Usage

gate_mindensity(
  fr,
  channel,
  filterId = "",
  positive = TRUE,
  gate_range = NULL,
  min = NULL,
  max = NULL,
  peaks = NULL,
  ...
)

Arguments

fr	a flowFrame object
channel	TODO
filterId	TODO
positive	If TRUE, then the gate consists of the entire real line to the right of the cutpoint. Otherwise, the gate is the entire real line to the left of the cutpoint. (Default: TRUE)
gate_range	numeric vector of length 2. If given, this sets the bounds on the gate applied. If no gate is found within this range, we set the gate to the minimum value within this range if positive is TRUE and the maximum value of the range otherwise.
min	a numeric value that sets the lower boundary for data filtering
max	a numeric value that sets the upper boundary for data filtering
peaks	numeric vector. If not given , then perform peak detection first by .find_peaks
...	Additional arguments for peak detection.

Details

In the default case, the two peaks of interest are the two largest peaks obtained from the link{density} function.

In the special case that there is only one peak, we are conservative and set the cutpoint as the min(x) if positive is TRUE, and the max(x) otherwise.

Value

a rectangleGate object based on the minimum density cutpoint

Examples

## Not run: 
 gate <- gate_mindensity(fr, channel = "APC-A") # fr is a flowFrame

## End(Not run)

RGLab/openCyto documentation built on Nov. 7, 2024, 9:23 p.m.