subsampling: Subsampling function

In inferCSN: Inferring Cell-Specific Gene Regulatory Network

Subsampling function

Description

This function subsamples a matrix using either random sampling or meta cells method.

Usage

subsampling(
  matrix,
  subsampling_method = c("sample", "meta_cells", "pseudobulk"),
  subsampling_ratio = 1,
  seed = 1,
  verbose = TRUE,
  ...
)

Arguments

matrix	The input matrix to be subsampled.
subsampling_method	The method to use for subsampling. Options are "sample", "pseudobulk" or "meta_cells".
subsampling_ratio	The percent of all samples used for fit_srm, default is 1.
seed	The random seed for cross-validation, default is 1.
verbose	Logical value, default is TRUE, whether to print progress messages.
...	Parameters for other methods.

Value

The subsampled matrix.

Examples

data("example_matrix")
data("example_ground_truth")
subsample_matrix <- subsampling(
  example_matrix,
  subsampling_ratio = 0.5
)
subsample_matrix_2 <- subsampling(
  example_matrix,
  subsampling_method = "meta_cells",
  subsampling_ratio = 0.5,
  fast_pca = FALSE
)
subsample_matrix_3 <- subsampling(
  example_matrix,
  subsampling_method = "pseudobulk",
  subsampling_ratio = 0.5
)

calculate_metrics(
  inferCSN(example_matrix),
  example_ground_truth,
  return_plot = TRUE
)
calculate_metrics(
  inferCSN(subsample_matrix),
  example_ground_truth,
  return_plot = TRUE
)
calculate_metrics(
  inferCSN(subsample_matrix_2),
  example_ground_truth,
  return_plot = TRUE
)
calculate_metrics(
  inferCSN(subsample_matrix_3),
  example_ground_truth,
  return_plot = TRUE
)

inferCSN documentation built on April 13, 2025, 5:11 p.m.