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DO.Import

DO.Import.Rd

Imports and processes single-cell RNA-seq data from various formats (10x Genomics, CellBender, or CSV), performs quality control (QC), filtering, normalization, variable gene selection, and optionally detects doublets. Returns a merged and processed Seurat object ready for downstream analysis.

Usage

DO.Import(
  pathways,
  ids,
  minCellGenes = 5,
  FilterCells = T,
  cut_mt = 0.05,
  min_counts = NULL,
  max_counts = NULL,
  min_genes = NULL,
  max_genes = NULL,
  low_quantile = NULL,
  high_quantile = NULL,
  DeleteDoublets = T,
  include_rbs = T,
  ...
)

Arguments

pathways

A character vector of paths to directories or files containing raw expression matrices.

ids

A character vector of sample identifiers, matching the order of pathways.

minCellGenes

Integer. Minimum number of cells a gene must be expressed in to be retained. Default is 5.

FilterCells

Logical. If TRUE, applies QC filtering on cells based on mitochondrial content, counts, and feature thresholds. Default is TRUE.

cut_mt

Numeric. Maximum allowed mitochondrial gene proportion per cell. Default is 0.05.

min_counts

Numeric. Minimum UMI count threshold (optional, used only if low_quantile is NULL).

max_counts

Numeric. Maximum UMI count threshold (optional, used only if high_quantile is NULL).

min_genes

Numeric. Minimum number of genes detected per cell to retain. Optional.

max_genes

Numeric. Maximum number of genes detected per cell to retain. Optional.

low_quantile

Numeric. Quantile threshold (0–1) to filter low UMI cells (used if min_counts is NULL).

high_quantile

Numeric. Quantile threshold (0–1) to filter high UMI cells (used if max_counts is NULL).

DeleteDoublets

Logical. If TRUE, doublets are detected and removed using scDblFinder. Default is TRUE.

include_rbs

Logical. If TRUE, calculates ribosomal gene content in addition to mitochondrial content. Default is TRUE.

...

Additional arguments passed to RunPCA().

Value

A merged Seurat object containing all samples, with normalization, QC, scaling, PCA, and optional doublet removal applied.

Author

Mariano Ruz Jurado & David John

Examples

if (FALSE) { # \dontrun{
merged_obj <- DO.Import(
  pathways = c("path/to/sample1", "path/to/sample2"),
  ids = c("sample1", "sample2"),
  TenX = TRUE,
  CellBender = FALSE,
  minCellGenes = 5,
  FilterCells = TRUE,
  cut_mt = 0.05,
  min_counts = 1000,
  max_counts = 20000,
  min_genes = 200,
  max_genes = 6000,
  DeleteDoublets = TRUE
)
} # }