bcds {scds} | R Documentation

## Find doublets/multiplets in UMI scRNA-seq data;

### Description

Annotates doublets/multiplets using a binary classification approach to discriminate artificial doublets from original data.

### Usage

    bcds(sce, ntop = 500, srat = 1, verb = FALSE, retRes = FALSE,
      nmax = "tune", varImp = FALSE, estNdbl = FALSE)

### Arguments

`sce` | single cell experiment (`SingleCellExperiment`) object to analyze; needs `counts` in assays slot.
`ntop` | integer, indicating number of top variance genes to consider. Default: 500
`srat` | numeric, indicating ratio between orginal number of "cells" and simulated doublets; Default: 1
`verb` | progress messages. Default: FALSE
`retRes` | logical, should the trained classifier be returned? Default: FALSE
`nmax` | maximum number of training rounds; integer or "tune". Default: "tune"
`varImp` | logical, should variable (i.e., gene) importance be returned? Default: FALSE
`estNdbl` | logical, should the numer of doublets be estimated from the data. Enables doublet calls. Default:FALSE. Use with caution.

### Value

sce input sce object `SingleCellExperiment` with doublet scores added to colData as "bcds_score" column, and possibly more (details)

### Examples

    data("sce_chcl")
    ## create small data set using only 100 cells
    sce_chcl_small = sce_chcl[, 1:100]
    sce_chcl_small = bcds(sce_chcl_small)

[Package scds version 1.3.0 Index]