downsampling: Downsampling Cells

In CIDER: Meta-Clustering for scRNA-Seq Integration and Evaluation

Downsampling Cells

Description

Downsamples cells from each group for IDER-based similarity calculation.

Usage

downsampling(
  metadata,
  n.size = 35,
  seed = NULL,
  include = FALSE,
  replace = FALSE,
  lower.cutoff = 3
)

Arguments

metadata	A data frame containing at least two columns: one for group labels and one for batch information. Each row corresponds to a single cell. Required.
n.size	Numeric value specifying the number of cells to use in each group. Default is 35.
seed	Numeric value to set the random seed for sampling. Default is 12345.
include	Logical value indicating whether to include groups that have fewer cells than n.size. Default is FALSE.
replace	Logical value specifying whether to sample with replacement if a group is smaller than n.size. Default is FALSE.
lower.cutoff	Numeric value indicating the minimum group size required for inclusion. Default is 3.

Value

A list of numeric indices (or cell names) for cells to be kept for downstream computation.

Examples

  # 'meta' is a data frame with columns 'label' and 'batch'
  meta <- data.frame(
    label = c(rep("A", 40), rep("A", 35), rep("B", 20)),
    batch = c(rep("X", 40), rep("Y", 35), rep("X", 20))
  )
  keep_cells <- downsampling(meta, n.size = 35, seed = 12345)
  
  # Display the selected indices
  print(keep_cells)

CIDER documentation built on April 4, 2025, 2:28 a.m.