Propagate In-Silico Perturbation Signal Through a Gene Network

Propagates a log-space perturbation delta through a gene-gene co-expression or regulatory network without count-space floor constraints, ensuring symmetric behavior between up- and down-regulation perturbations.

Usage

ApplyPropagation(
  log_obs_mod,
  delta_log,
  network,
  n_iters = 3,
  delta_scale = 0.2,
  row_normalize = FALSE,
  prune_network = FALSE,
  prune_percentile = 0.95
)

Arguments

log_obs_mod

A genes-by-cells log-normalized expression matrix for the module (or network) genes at baseline. Typically a row subset of the full log-normalized observed expression matrix.

delta_log

A genes-by-cells log-space delta matrix for the same genes. Only the directly-perturbed (hub) gene rows are non-zero at input; the propagation step fills in downstream gene rows.

network

A gene-by-gene matrix (e.g., TOM or regulatory adjacency) defining how signal routes between genes.

n_iters

Number of iterative propagation steps. Default is 3.

delta_scale

Dampening factor applied at each iteration to prevent signal explosion. Default is 0.2.

row_normalize

Logical. If TRUE, each row of the network is scaled to sum to 1 before propagation (weighted-average diffusion rather than summation). Default is FALSE.

prune_network

Logical. If TRUE, zero out edges below the prune_percentile threshold before propagation. Default is FALSE.

prune_percentile

Numeric in \((0,1)\). Percentile threshold for edge pruning when prune_network = TRUE. Default is 0.95.

Value

A genes-by-cells matrix of log-normalized simulated expression for the module genes.

Details