Construct network for single target gene

Construct network for single target gene

Usage

single_network(
  matrix,
  regulators,
  target,
  pseudotime = NULL,
  max_support_size = NULL,
  lag_fraction = 0.05,
  lag_steps = NULL,
  cores = 1,
  verbose = TRUE
)

Arguments

matrix

An expression matrix.

regulators

Candidate regulator genes.

target

The target gene.

pseudotime

Optional pseudotime vector or branch matrix passed to [inferCSN()].

max_support_size

Optional support-size cap passed to [inferCSN()].

lag_fraction

Fractional state lag passed to [inferCSN()].

lag_steps

Optional integer state lag passed to [inferCSN()].

cores

Number of inference workers.

verbose

Whether to report progress.

Value

A data frame containing only selected edges for the requested target. The data frame has three columns: regulator, target, and weight.

Examples

data(example_matrix)
head(
  single_network(
    example_matrix,
    regulators = colnames(example_matrix),
    target = "g1"
  )
)
#> ℹ [2026-09-08 16:58:04] Inferring network for <matrix/array>...
#> ◌ [2026-09-08 16:58:04] Checking parameters...
#> ✔ [2026-09-08 16:58:04] Inferring network done
#> ℹ [2026-09-08 16:58:04] Network information:
#> ℹ                         Edges Regulators Targets
#> ℹ                       1     2          2       1
#>   regulator target weight
#> 1        g6     g1   0.75
#> 2        g5     g1  -0.25
single_network(
  example_matrix,
  regulators = c("g1", "g2", "g3"),
  target = "g1"
)
#> ℹ [2026-09-08 16:58:04] Inferring network for <matrix/array>...
#> ◌ [2026-09-08 16:58:04] Checking parameters...
#> ✔ [2026-09-08 16:58:04] Inferring network done
#> ℹ [2026-09-08 16:58:04] Network information:
#> ℹ                         Edges Regulators Targets
#> ℹ                       1     2          2       1
#>   regulator target weight
#> 1        g2     g1  -0.75
#> 2        g3     g1  -0.25