View source: R/regulatorAnalysis.directed_weighted.R
regulatorAnalysis.directed_weighted | R Documentation |
Identifies network regulators from directed network weights.
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.
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