RunCellQC: Run cell-level quality control for single cell RNA-seq data.

In zh542370159/SCP: Single Cell Pipeline

Run cell-level quality control for single cell RNA-seq data.

Description

This function handles multiple quality control methods for single-cell RNA-seq data.

Usage

RunCellQC(
  srt,
  assay = "RNA",
  split.by = NULL,
  return_filtered = FALSE,
  qc_metrics = c("doublets", "outlier", "umi", "gene", "mito", "ribo", "ribo_mito_ratio",
    "species"),
  db_method = "scDblFinder",
  db_rate = NULL,
  db_coefficient = 0.01,
  outlier_threshold = c("log10_nCount:lower:2.5", "log10_nCount:higher:5",
    "log10_nFeature:lower:2.5", "log10_nFeature:higher:5", "featurecount_dist:lower:2.5"),
  outlier_n = 1,
  UMI_threshold = 3000,
  gene_threshold = 1000,
  mito_threshold = 20,
  mito_pattern = c("MT-", "Mt-", "mt-"),
  mito_gene = NULL,
  ribo_threshold = 50,
  ribo_pattern = c("RP[SL]\\d+\\w{0,1}\\d*$", "Rp[sl]\\d+\\w{0,1}\\d*$",
    "rp[sl]\\d+\\w{0,1}\\d*$"),
  ribo_gene = NULL,
  ribo_mito_ratio_range = c(1, Inf),
  species = NULL,
  species_gene_prefix = NULL,
  species_percent = 95,
  seed = 11
)

Arguments

srt	A Seurat object.
assay	The name of the assay to be used for doublet-calling. Default is "RNA".
split.by	Name of the sample variable to split the Seurat object. Default is NULL.
return_filtered	Logical indicating whether to return a cell-filtered Seurat object. Default is FALSE.
qc_metrics	A character vector specifying the quality control metrics to be applied. Default is 'c("doublets", "outlier", "umi", "gene", "mito", "ribo", "ribo_mito_ratio", "species")'.
db_method	Doublet-calling methods used. Can be one of scDblFinder, Scrublet, DoubletDetection, scds_cxds, scds_bcds, scds_hybrid
db_rate	The expected doublet rate. By default this is assumed to be 1% per thousand cells captured (so 4% among 4000 thousand cells), which is appropriate for 10x datasets.
db_coefficient	The coefficient used to calculate the doublet rate. Default is 0.01. Doublet rate is calculated as'ncol(srt) / 1000 * db_coefficient'
outlier_threshold	A character vector specifying the outlier threshold. Default is 'c("log10_nCount:lower:2.5", "log10_nCount:higher:5", "log10_nFeature:lower:2.5", "log10_nFeature:higher:5", "featurecount_dist:lower:2.5")'. See isOutlier.
outlier_n	Minimum number of outlier metrics that meet the conditions for determining outlier cells. Default is 1.
UMI_threshold	UMI number threshold. Cells that exceed this threshold will be considered as kept. Default is 3000.
gene_threshold	Gene number threshold. Cells that exceed this threshold will be considered as kept. Default is 1000.
mito_threshold	Percentage of UMI counts of mitochondrial genes. Cells that exceed this threshold will be considered as discarded. Default is 20.
mito_pattern	Regex patterns to match the mitochondrial genes. Default is 'c("MT-", "Mt-", "mt-")'.
mito_gene	A defined mitochondrial genes. If features provided, will ignore the mito_pattern matching. Default is NULL.
ribo_threshold	Percentage of UMI counts of ribosomal genes. Cells that exceed this threshold will be considered as discarded. Default is 50.
ribo_pattern	Regex patterns to match the ribosomal genes. Default is 'c("RP[SL]\d+\w0,1\d*$", "Rp[sl]\d+\w0,1\d*$", "rp[sl]\d+\w0,1\d*$")'.
ribo_gene	A defined ribosomal genes. If features provided, will ignore the ribo_pattern matching. Default is NULL.
ribo_mito_ratio_range	A numeric vector specifying the range of ribosomal/mitochondrial gene expression ratios for ribo_mito_ratio outlier cells. Default is c(1, Inf).
species	Species used as the suffix of the QC metrics. The first is the species of interest. Default is NULL.
species_gene_prefix	Species gene prefix used to calculate QC metrics for each species. Default is NULL.
species_percent	Percentage of UMI counts of the first species. Cells that exceed this threshold will be considered as kept. Default is 95.
seed	Set a random seed. Default is 11.

Value

Returns Seurat object with the QC results stored in the meta.data slot.

Examples

data("pancreas_sub")
pancreas_sub <- RunCellQC(pancreas_sub)
CellStatPlot(
  srt = pancreas_sub,
  stat.by = c(
    "db_qc", "outlier_qc", "umi_qc", "gene_qc",
    "mito_qc", "ribo_qc", "ribo_mito_ratio_qc", "species_qc"
  ),
  plot_type = "upset", stat_level = "Fail"
)
table(pancreas_sub$CellQC)

data("ifnb_sub")
ifnb_sub <- RunCellQC(ifnb_sub, split.by = "stim", UMI_threshold = 1000, gene_threshold = 550)
CellStatPlot(
  srt = ifnb_sub,
  stat.by = c(
    "db_qc", "outlier_qc", "umi_qc", "gene_qc",
    "mito_qc", "ribo_qc", "ribo_mito_ratio_qc", "species_qc"
  ),
  plot_type = "upset", stat_level = "Fail"
)
table(ifnb_sub$CellQC)

zh542370159/SCP documentation built on Nov. 22, 2023, 2:34 a.m.