CallCellRangerV3: CellRanger_v3 method used to recognize cell-containing...

In zh542370159/dropSplit: Automatically identify cell-containing and empty droplets for droplet-based scRNAseq data using dropSplit

CellRanger_v3 method used to recognize cell-containing droplets.

Description

CellRanger_v3 method used to recognize cell-containing droplets.

Usage

CallCellRangerV3(
  counts,
  recovered_cells = 3000,
  recovered_cells_quantile = 0.99,
  n_candidate_barcodes = 20000,
  n_partitions = 90000,
  min_umis_nonambient = 500,
  min_umi_frac_of_median = 0.01,
  max_adj_pvalue = 0.01
)

Arguments

counts	A matrix object or a dgCMatrix object which columns represent features and rows represent droplets.
recovered_cells	Expected number of recovered cells. Default is 3000.
recovered_cells_quantile	Quantile of the top recovered_cells barcodes by total UMI counts. Default is 0.99.
n_candidate_barcodes	Number of additional barcodes to consider after the initial cell calling. Default is 20000.
n_partitions	Number of partitions (max number of barcodes to consider for ambient estimation). Default is 90000.
min_umis_nonambient	Minimum number of UMIS per barcode to consider after the initial cell calling. Default is 500.
min_umi_frac_of_median	Minimum ratio of UMIs to the median (initial cell call UMI) to consider after the initial cell calling. Default is 0.01.
max_adj_pvalue	Minimum ratio of UMIs to the median (initial cell call UMI) to consider after the initial cell calling. Default is 0.01.

Value

A DataFrame containing the classification column named 'CellRangerV3Class'.

Examples

counts <- simSimpleCounts()
result <- CallCellRangerV3(counts)
head(result)

zh542370159/dropSplit documentation built on June 19, 2022, 2:49 p.m.