Nuclei Analysis Toolkit

run_doubletfinder

R Documentation

Find singlets in a SingleCellExperiment with DoubletFinder by McGinnis CS et al

Description

Runs the doubletfinder algorithm on the SingleCellExperiment. Returns a SingleCellExperiment annotated with is_singlet and tSNE coordinates.

Usage

run_doubletfinder(
  sce,
  pK = NULL,
  pca_dims = 10,
  var_features = 2000,
  vars_to_regress_out = "nCount_RNA",
  doublet_rate = 0,
  dpk = 8,
  num_cores = max(1, future::availableCores() - 2)
)

Arguments

`sce`	a SingleCellExperiment object
`pK`	a pK value to use in place of a parameter sweep
`pca_dims`	the number of principal components to use
`var_features`	the top n variable features to use
`vars_to_regress_out`	the variables to regress out
`doublet_rate`	either a fixed doublet rate (e.g. 0.075) or 0 to
`dpk`	doublets per thousand cells increment if doublet_rate is 0.
`num.cores`	the number of CPU cores to use

Details

Remember to cite: - DoubletFinder: Doublet Detection in Single-Cell RNA Sequencing Data Using Artificial Nearest Neighbors. McGinnis CS, Murrow LM, Gartner ZJ. Cell Syst. 2019 Apr 24;8(4):329-337.e4. doi: https://doi.org/10.1016/j.cels.2019.03.003.

Value

sce a SingleCellExperiment object annotated for singlets

Other annotation functions: .preprocess_seurat_object(), annotate_celltype_metrics(), annotate_integrated_sce(), annotate_merged_sce(), annotate_sce(), annotate_sce_cells(), annotate_sce_genes(), filter_sce(), find_cells(), find_singlets(), generate_sce(), map_ensembl_gene_id(), merge_sce(), read_metadata(), report_celltype_metrics(), report_celltype_model(), report_merged_sce(), report_qc_sce(), sce_to_seu()