gate_singlet {flowStats} | R Documentation

## Creates a singlet polygon gate using the prediction bands from a robust linear model

### Description

We construct a singlet gate by applying a robust linear model with `rlm`. By default, we model the forward-scatter height (FSC-H)as a function of forward-scatter area (FSC-A). If `sidescatter` is given, forward-scatter height is as a function of `area` + `sidescatter` + `sidescatter / area`.

### Usage

    gate_singlet(
      x,
      area = "FSC-A",
      height = "FSC-H",
      sidescatter = NULL,
      prediction_level = 0.99,
      subsample_pct = NULL,
      wider_gate = FALSE,
      filterId = "singlet",
      maxit = 5,
      ...
    )

    singletGate(
      x,
      area = "FSC-A",
      height = "FSC-H",
      sidescatter = NULL,
      prediction_level = 0.99,
      subsample_pct = NULL,
      wider_gate = FALSE,
      filterId = "singlet",
      maxit = 5,
      ...
    )

### Arguments

`x` | a `flowFrame` object
`area` | character giving the channel name that records the signal intensity as peak area
`height` | character giving the channel name that records the signal intensity as peak heightchannel name of height
`sidescatter` | character giving an optional channel name for the sidescatter signal. By default, ignored.
`prediction_level` | a numeric value between 0 and 1 specifying the level to use for the prediction bands
`subsample_pct` | a numeric value between 0 and 1 indicating the percentage of observations that should be randomly selected from `x` to construct the gate. By default, no subsampling is performed.
`wider_gate` | logical value. If `TRUE`, the prediction bands used to construct the singlet gate use the robust fitted weights, which increase prediction uncertainty, especially for large FSC-A. This leads to wider gates, which are sometimes desired.
`filterId` | the name for the filter that is returned
`maxit` | the limit on the number of IWLS iterations passed to `rlm`
`...` | additional arguments passed to `rlm`

### Details

Because `rlm` relies on iteratively reweighted least squares (IRLS), the runtime to construct a singlet gate is dependent in part on the number of observations in `x`. To improve the runtime, we provide an option to subsample randomly a subset of `x`. A percentage of observations to subsample can be given in `subsample_pct`. By default, no subsampling is applied.

### Value

a `polygonGate` object with the singlet gate

### Examples

    ## Not run:
     # fr is a flowFrame
     sg <- gate_singlet(fr, area = "FSC-A", height = "FSC-H")
     sg
     # plot the gate
     xyplot(`FSC-H` ~ `FSC-A`, fr, filter = sg)

    ## End(Not run)

[Package flowStats version 4.0.0 Index]