Decompose a Triangle's edges into per-edge ligand-receptor contributions

A bundled Triangle (see computeTriangles()) combines all 6 directed edges among 3 cell types (i, j, k) into 8 direction-combination products. As with Wedges, edges are multiplied together rather than summed, so there is no single well-defined "share of the Triangle score" attributable to one edge's ligand-receptor pair alone – instead, this decomposes each of the 6 directed edges separately via computeLRContributions() (bundle = FALSE), so PctOfTotal in the result is relative to each edge's own kernel value.

Usage

computeTriangleLRContributions(
  Lmatrix,
  Rmatrix,
  Cmatrix,
  LRmatrix,
  celltypes,
  i,
  j,
  k,
  Dcell = Cmatrix,
  patient_names = NULL,
  top_n = NULL
)

Arguments

Lmatrix, Rmatrix, Cmatrix, LRmatrix

Same inputs as compute_kernel().

celltypes

Character vector of cell-type names, in the row order of Lmatrix/Rmatrix/columns of Cmatrix.

i, j, k

Cell-type names for the triangle's 3 vertices.

Dcell

Patient-by-cell-type abundance matrix used to scale raw contributions to the same units as calculateDirect()'s raw score. Defaults to Cmatrix.

patient_names

Optional character vector of patient labels, matching the patient order in LRmatrix. Defaults to Patient_1, Patient_2, ...

top_n

Optional; if given, keep only the top top_n ligand-receptor pairs per patient (by Contribution).

Value

A data frame like computeLRContributions()'s, pooled across the 6 directed edges (Edge identifies which one, e.g. "i -> j").