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Compute Bidirectional Correlation from Transferred Cell Scores

Source: R/H_extrapolate.R
getTransferBidirCorr.Rd

Given a target object and a list of transferred cell scores (per cell type), compute the bidirectional correlation for each pair of cell types using the provided kernel matrices at a selected sigma value.

Usage

getTransferBidirCorr(
  tar_obj,
  transfer_cell_scores,
  sigma_choice,
  calculationMode = NULL,
  normalize_K = c("row_or_col", "sinkhorn_knopp", "none"),
  filter_kernel = TRUE,
  K_row_sum_cutoff = 0.005,
  K_col_sum_cutoff = 0.005,
  sigma_choice_tar = NULL,
  verbose = TRUE
)

Arguments

tar_obj

A CoProSingle or CoProMulti object containing kernel matrices and metadata needed for alignment.

transfer_cell_scores

A named list of matrices, with one entry per cell type (names must be the cell type names). Each matrix should be cells-by-CCs, where rows are cell IDs and columns are CC_1, CC_2, ..., as returned by getTransferCellScores(agg_cell_type = FALSE).

sigma_choice

Numeric scalar specifying the sigma value of the kernel to use.

calculationMode

For CoProMulti objects only, either "perSlide" or "aggregate". Ignored for CoProSingle. Default "perSlide" if tar_obj is multi-slide.

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.

sigma_choice_tar

Numeric; sigma value for target object kernel matrices. If NULL (default), uses sigma_choice. Not recommended for general use.

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. For single-slide objects, the data.frame has columns sigmaValue, cellType1, cellType2, CC_index, bidirCorrelation. For multi-slide objects in perSlide mode, the data.frame additionally includes slideID. For aggregate mode, the correlation column is named aggregateCorrelation.

Details

This function mirrors the correlation calculation used in computeBidirCorrelation() but operates on precomputed cell scores (e.g., obtained from getTransferCellScores(agg_cell_type = FALSE)).

The bidirectional correlation is computed as the mean of two correlations: cor(t(K) %% A_w1, B_w2) and cor(A_w1, K %% B_w2), where A_w1 and B_w2 are the cell score vectors (for the same CC index) for cell types A and B respectively, and K is the kernel matrix between the two cell types at the chosen sigma.

Examples

# Assuming `tar_obj` is prepared and `trans_scores` was computed with
# getTransferCellScores(..., agg_cell_type = FALSE)
# res <- getTransferBidirCorr(tar_obj, trans_scores, sigma_choice = 2.0)