Analogous to the original openCyto::mindensity(), mindensity2 operates on a standard flowFrame. Its behavior is closely modeled on the original mindensity() whenever possible. However, the underlying peak-finding algorithm (improvedMindensity) behaves significantly differently.

gate_mindensity2(
fr,
channel,
filterId = "",
pivot = FALSE,
gate_range = NULL,
min = NULL,
max = NULL,
peaks = NULL,
...
)

## Arguments

fr a flowFrame object the channel to operate on a name to refer to this filter logical value. If TRUE, we choose as the two peaks the largest peak and its neighboring peak. See details. numeric vector of length 2. If given, this sets the bounds on the gate applied. a numeric value that sets the lower boundary for data filtering a numeric value that sets the upper boundary for data filtering numeric vector. If not given , then perform peak detection first by .find_peaks Additional arguments for peak detection.

## Value

a rectangleGate object based on the minimum density cutpoint

## Examples

if (FALSE) {
gate <- gate_mindensity2(fr, channel = "APC-A") # fr is a flowFrame
}