Aggregate single-cell data into pseudobulk samples based on read coverage

This function aggregates single-cell RNA-seq data into pseudobulk samples by sequentially accumulating cells until a cumulative read coverage threshold is reached. Each pseudobulk sample is guaranteed to contain at least the specified number of total reads, ensuring sufficient sequencing depth for downstream transcriptomic age prediction.

Usage

aggregate_pseudobulk(
  seurat_obj,
  coverage_threshold = 1e+06,
  assay = "RNA",
  layer = "counts",
  shuffle = FALSE,
  seed = NULL,
  new_sample_prefix = "",
  verbose = TRUE
)

Arguments

seurat_obj: A Seurat object containing single-cell RNA-seq data.
coverage_threshold: Integer specifying the minimum cumulative read count per pseudobulk sample. Cells are sequentially added to a group until this threshold is met, then a new group begins. Default is 1e6 (1 million reads).
assay: Character string specifying which assay to use. Default is "RNA".
layer: Character string specifying which layer to use. Default is "counts".
shuffle: Logical indicating whether to randomly shuffle cells before aggregation. Shuffling breaks any ordering present in the data. Default is FALSE.
seed: Integer seed for reproducibility when shuffle = TRUE. Default is NULL.
new_sample_prefix: Character string prefix for pseudobulk sample names. Default is "".
verbose: Logical indicating whether to print progress messages. Default is TRUE.

Value

An ExpressionSet object with pseudobulk expression data and metadata including cumulative_coverage (total reads) and n_cells per pseudobulk sample.

Examples

if (FALSE) { # \dontrun{
# Basic coverage-based aggregation
eset <- aggregate_pseudobulk(seurat_obj, coverage_threshold = 1e6)

# With shuffling for randomized grouping
eset <- aggregate_pseudobulk(seurat_obj, coverage_threshold = 5e5,
                             shuffle = TRUE, seed = 42)
} # }