prep_scATAC_cinaR: prep_scATAC_cinaR

In cinaR: A Computational Pipeline for Bulk 'ATAC-Seq' Profiles

prep_scATAC_cinaR

Description

Prepare 10x scATAC peak-by-cell matrices for cinaR by pseudobulking per sample.

Usage

prep_scATAC_cinaR(
  counts,
  cell.meta,
  sample.col,
  group.col,
  cluster.col = NULL,
  peak.bed = NULL,
  min.cells = 20,
  verbose = TRUE
)

Arguments

counts	peak-by-cell count matrix (dense matrix or sparse dgCMatrix).
cell.meta	data.frame with rownames as cell barcodes.
sample.col	column name in cell.meta indicating biological replicate.
group.col	column name in cell.meta indicating condition/group.
cluster.col	optional column name for cell type/cluster. If provided, output is a named list per cluster.
peak.bed	optional data.frame with CHR/START/STOP columns for peaks. If not provided, rownames(counts) are parsed as "chr:start-end" or "chr_start_end".
min.cells	minimum number of cells required per sample (and per cluster if used).
verbose	logical, prints informative messages.

Value

list with elements 'bed', 'contrasts', and 'group.info', or a named list of such lists when cluster.col is provided.

Examples

counts <- matrix(c(1, 0, 2, 1, 0, 1, 3, 0, 0, 2, 1, 0),
                 nrow = 2, byrow = TRUE)
rownames(counts) <- c("chr1:1-100", "chr1:101-200")
colnames(counts) <- paste0("cell", 1:6)
meta <- data.frame(sample = c("S1", "S1", "S2", "S2", "S3", "S3"),
                   group = c("A", "A", "B", "B", "B", "B"),
                   row.names = colnames(counts))
prep <- prep_scATAC_cinaR(counts, meta, sample.col = "sample", group.col = "group",
                          min.cells = 2)

cinaR documentation built on Feb. 4, 2026, 5:13 p.m.