annotate_sce_genes: Add basic gene-wise annotations for a SingleCellExperiment

In combiz/scFlow: A Single-Cell/Nuclei Analysis Toolkit

Add basic gene-wise annotations for a SingleCellExperiment

Description

Adds biomaRt annotations (e.g. gene, gene_biotype) and calculates the following QC metrics:

• qc_metric_ensembl_mapped - was the ensembl_gene_id found in biomaRt

• qc_metric_is_mito - is the gene mitochondrial

• qc_metric_is_ribosomal - is the gene ribosomal

Usage

annotate_sce_genes(
  sce,
  drop_unmapped = TRUE,
  drop_mito = TRUE,
  drop_ribo = FALSE,
  ensembl_mapping_file = NULL,
  species = getOption("scflow_species", default = "human")
)

Arguments

sce	a SingleCellExperiment object with ensembl_gene_id rowData
drop_unmapped	set TRUE to remove unmapped ensembl_gene_id
drop_mito	set TRUE to remove mitochondrial genes
drop_ribo	set TRUE to remove ribosomal genes
ensembl_mapping_file	a local tsv file with ensembl_gene_id and additional columns for mapping ensembl_gene_id to gene info. If not provided, the biomaRt db is queried (slower).
species	The biological species of the sample.#'

Value

sce a SingleCellExperiment object annotated with gene data

See Also

Other annotation functions: .preprocess_seurat_object(), annotate_celltype_metrics(), annotate_integrated_sce(), annotate_merged_sce(), annotate_sce(), annotate_sce_cells(), 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(), run_doubletfinder(), sce_to_seu()

combiz/scFlow documentation built on Feb. 25, 2024, 10:25 a.m.