gate_mindensity2 {openCyto} | R Documentation

## An improved version of mindensity used to determines a cutpoint as the minimum point of a kernel density estimate between two peaks.

### Description

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.

### Usage

    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

### Author(s)

Greg Finak, Phu T. Van

### Examples

    ## Not run:
     gate <- gate_mindensity2(fr, channel = "APC-A") # fr is a flowFrame

    ## End(Not run)

[Package openCyto version 2.2.0 Index]