generate_samples: Generate random cell number samples

In cellGeometry: Geometric Single Cell Deconvolution

Generate random cell number samples

Description

Used for simulating pseudo-bulk RNA-Seq from a 'cellMarkers' object. Cell counts are randomly sampled from the uniform distribution, using the original subclass contingency table as a limit on the maximum number of cells in each subclass.

Usage

generate_samples(
  object,
  n,
  equal_sample = TRUE,
  method = c("unif", "dirichlet"),
  alpha = 1.5,
  zero_fraction = 0
)

Arguments

object	A 'cellMarkers' class object
n	Integer value for the number of samples to generate
equal_sample	Logical whether to sample subclasses equally or generate samples with proportions of cells in keeping with the original subtotal of cells in the main scRNA-Seq data.
method	Either "unif" or "dirichlet" to specify whether cell numbers are drawn from uniform distribution or dirichlet distribution.
alpha	Shape parameter for gtools::rdirichlet(). Automatically expanded to be a vector whose length is the number of subclasses.
zero_fraction	Numeric from 0 to 1 specifying proportion of cell subclasses to randomly set to zero in each sample.

Details

Leaving equal_sample = TRUE is better for tuning deconvolution parameters.

Value

An integer matrix with n rows, with columns for each cell subclasses in object, representing cell counts for each cell subclass. Designed to be passed to simulate_bulk().

See Also

simulate_bulk()

cellGeometry documentation built on April 20, 2026, 1:06 a.m.