Run the full kernel-based RaCInG workflow

Usage

compute_racing_kernel(
  counts = NULL,
  output_folder = "~/Documents/racing/vignettes/",
  deconv = NULL,
  cc_network = NULL,
  fun_LR = min,
  cell_expr_profile = NULL,
  source = "source_genesymbol",
  target = "target_genesymbol",
  signed = FALSE,
  deconv_method = "Quantiseq",
  cbsx.name = NULL,
  cbsx.token = NULL,
  file_name = NULL,
  nPatients = "all",
  communication_type = "W",
  norm = TRUE,
  pt_idx = NULL,
  remove_direction = TRUE,
  input_data = NULL
)

Arguments

counts: Gene-by-sample count matrix. Required when input_data is not supplied; ignored otherwise.
output_folder: Directory used to write and read intermediate input files.
deconv: Optional deconvolution matrix.
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 in cc_network.
signed: Logical; if TRUE, also try to load a sign matrix.
deconv_method: Deconvolution method used when deconv is not supplied.
cbsx.name, cbsx.token: Optional credentials for the deconvolution workflow.
file_name: File stem used for intermediate input files.
nPatients: Number of patients to process, or "all".
communication_type: Feature family to compute.
norm: Logical; if TRUE, compute a normalized baseline kernel.
pt_idx: Optional single patient index to process.
remove_direction: Logical; if TRUE, merge directionally equivalent features.
input_data: Optional named list of pre-computed input matrices as returned by prepare_input_files(). Must contain Lmatrix, Rmatrix, Cmatrix, LRmatrix, celltypes, ligands, and receptors. When supplied, the counts argument and all preprocessing parameters (deconv, cc_network, etc.) are ignored.

Value

A list with the kernel arrays and the derived feature matrix.