Build RaCInG input files from raw count data

This function combines the preprocessing and input-loading steps into a single call. It generates the L, R, C, and LR CSV files from raw counts, then reads them back to produce the normalised matrices and 3-D tensor required by the kernel and Monte Carlo workflows.

Usage

prepare_input_files(
  counts,
  output_folder = "Results/",
  deconv = NULL,
  cc_network = NULL,
  fun_LR = min,
  cell_expr_profile = NULL,
  source = "source_genesymbol",
  target = "target_genesymbol",
  deconv_method = "Quantiseq",
  cbsx.name = NULL,
  cbsx.token = NULL,
  file_name = NULL,
  signed = FALSE
)

Arguments

counts

Gene-by-sample count matrix.

output_folder

Directory where the generated L, R, C, and LR files are written.

deconv

Optional deconvolution matrix. If omitted, the function will try to compute it.

cc_network

Optional ligand-receptor prior network.

fun_LR

Function used to combine ligand and receptor expression values.

cell_expr_profile

Optional cell-type expression profile matrix.

source, target

Column names to use as ligand and receptor identifiers when cc_network is supplied.

deconv_method

Deconvolution method passed to multideconv::compute.deconvolution().

cbsx.name, cbsx.token

Optional credentials forwarded to the deconvolution workflow.

file_name

File stem used when exporting the generated CSV files.

signed

Logical; if TRUE, also try to load a sign matrix from output_folder.

Value

A named list with the processed input matrices and their labels: Lmatrix, Rmatrix, Cmatrix (normalised), LRmatrix (3-D tensor), celltypes, ligands, receptors, Sign_matrix, and CC_table.