Initialize a Seurat object with optional QC metrics — sn_initialize_seurat

This function creates a Seurat object from counts (and optional metadata), then calculates common QC metrics such as mitochondrial and ribosomal gene percentages when species is supplied. Currently supports human and mouse patterns for these gene sets.

Usage

sn_initialize_seurat_object(
  x,
  metadata = NULL,
  names_field = 1L,
  names_delim = "_",
  project = "Shennong",
  min_cells = 0,
  min_features = 0,
  sample_name = NULL,
  study = NULL,
  species = NULL,
  standardize_gene_symbols = FALSE,
  is_gene_id = FALSE,
  ...
)

Arguments

x: A matrix, data.frame, sparse matrix, or path to counts data.
metadata: Optional metadata (data.frame or similar) to add to the Seurat object.
names_field: Passed to SeuratObject::CreateSeuratObject, indicating how to parse cell names.
names_delim: Passed to SeuratObject::CreateSeuratObject, indicating the delimiter for cell names.
project: A project name for the Seurat object.
min_cells: Filter out genes expressed in fewer than min_cells cells.
min_features: Filter out cells with fewer than min_features genes.
sample_name: Optional sample name to store in meta.data$sample.
study: Optional study name to store in meta.data$study.
species: Either "human" or "mouse" (case-sensitive). Affects QC metric patterns.
standardize_gene_symbols: Logical; standardize gene symbols after object creation.
is_gene_id: Logical; treat row names as gene IDs and convert them to symbols when standardizing.
...: Additional arguments passed to SeuratObject::CreateSeuratObject().

Value

A Seurat object with optional QC metadata in its meta.data slot.

Examples

if (FALSE) { # \dontrun{
# Minimal example:
seurat_obj <- sn_initialize_seurat_object(x = my_counts, project = "ExampleProject")
} # }