runBcds {singleCellTK} | R Documentation

## Find doublets/multiplets using bcds.

### Description

A wrapper function for bcds. Annotate doublets/multiplets using a binary classification approach to discriminate artificial doublets from original data. Generate a doublet score for each cell. Infer doublets if `estNdbl` is `TRUE`.

### Usage

    runBcds(
      inSCE,
      sample = NULL,
      seed = 12345,
      ntop = 500,
      srat = 1,
      verb = FALSE,
      retRes = FALSE,
      nmax = "tune",
      varImp = FALSE,
      estNdbl = FALSE,
      useAssay = "counts"
    )

### Arguments

`inSCE` | A SingleCellExperiment object. Needs `counts` in assays slot.
`sample` | Character vector. Indicates which sample each cell belongs to. bcds will be run on cells from each sample separately. If NULL, then all cells will be processed together. Default NULL.
`seed` | Seed for the random number generator. Default 12345.
`ntop` | See bcds for more information. Default `500`.
`srat` | See bcds for more information. Default `1`.
`verb` | See bcds for more information. Default `FALSE`.
`retRes` | See bcds for more information. Default `FALSE`.
`nmax` | See bcds for more information. Default `"tune"`.
`varImp` | See bcds for more information. Default `FALSE`.
`estNdbl` | See bcds for more information. Default `FALSE`.
`useAssay` | A string specifying which assay in the SCE to use.

### Value

A SingleCellExperiment object with bcds output appended to the colData slot. The columns include bcds_score and optionally bcds_call. Please refer to the documentation of bcds for details.

### Examples

    data(scExample, package = "singleCellTK")
    sce <- subsetSCECols(sce, colData = "type != 'EmptyDroplet'")
    sce <- runBcds(sce)

[Package singleCellTK version 2.2.0 Index]