inferCSN (version 1.2.0)

subsampling: 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,
  ...
)

Value

The subsampled matrix.

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

Whether to print progress messages. Default is TRUE.

...

Parameters for other methods.

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
)