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

channel

the channel to operate on

filterId

a name to refer to this filter

pivot

logical value. If TRUE, we choose as the two peaks the largest peak and its neighboring peak. See details.

gate_range

numeric vector of length 2. If given, this sets the bounds on the gate applied.

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.

Value

a rectangleGate object based on the minimum density cutpoint

Examples

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