Compute Self-Bidirectional Correlation using skrCCA Results

This function computes self-bidirectional correlation directly from a CoPro object that has skrCCA results, using the object's own cell scores rather than transferred scores. This is useful for computing spatial autocorrelation patterns within each cell type using the object's native skrCCA results.

Usage

computeSelfBidirCorr(
  object,
  sigma_choice,
  calculationMode = "perSlide",
  normalize_K = c("row_or_col", "sinkhorn_knopp", "none"),
  filter_kernel = TRUE,
  K_row_sum_cutoff = 0.005,
  K_col_sum_cutoff = 0.005,
  verbose = TRUE
)

Arguments

object

A CoProSingle or CoProMulti object with skrCCA results and self-kernel matrices computed using computeSelfKernel().

sigma_choice

Numeric scalar specifying the sigma value to use.

calculationMode

For CoProMulti objects only, either "perSlide" or "aggregate". Default "perSlide".

normalize_K

Character; method for normalizing the kernel matrix, one of "row_or_col", "sinkhorn_knopp", or "none". Default "row_or_col".

filter_kernel

Logical; whether to filter the kernel matrix. Default TRUE.

K_row_sum_cutoff

Numeric; cutoff for row sums when normalizing kernel matrix. Default 5e-3.

K_col_sum_cutoff

Numeric; cutoff for column sums when normalizing kernel matrix. Default 5e-3.

verbose

Logical; whether to print progress messages.

Value

A list with one element named paste0("sigma_", sigma_choice), whose value is a data.frame of results with the same structure as getTransferSelfBidirCorr().

Examples

if (FALSE) { # \dontrun{
# Assuming you have a CoPro object with skrCCA results and self-kernels
object <- runSkrCCA(object)
object <- computeSelfDistance(object)
object <- computeSelfKernel(object, sigmaValues = c(0.01, 0.05, 0.1))

# Compute self-bidirectional correlation using native skrCCA results
self_bidir <- computeSelfBidirCorr(object, sigma_choice = 0.05)
} # }