Function to Identify Network Regulators from Directed Weighted Networks — regulatorAnalysis.directed

Identifies network regulators from directed network weights.

Usage

regulatorAnalysis.directed_weighted(
  adj,
  G,
  h = 3,
  n = 100,
  correction.method = "bonferroni",
  pval.cutoff = 0.01
)

adj: Required. An n x n weighted upper triangular adjacency in the matrix class format.
G: Required. A named vector of node scores.
h: Optional. Neighborhood search distance (h nodes away from current node) (Default = 3)
n: Optional. Number of randomisation for pvalue computation. (Default = 100)
correction.method: Optional. Multiple testing correction method. Options are; c("holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none") (Default = 'bonferroni')
pval.cutoff: Optional. Adjusted pvalue cutoff for regulator selection. (Default = 0.01)

scores = n x 5 dimensional data frame with columns giving neighborhood based score, adjusted pvalue, whether a gene is regulator/global regulator.