1/2/2015 · network.test.edges returns a data frame containing all edges listed in order of the magnitude of the partial correlation associated with each edge. If fdr=TRUE then in addition the p-values, q-values and posterior probabilities (=1 – local fdr) for each potential edge are computed.
Description. network.test.edges returns a data frame containing all edges listed in order of the magnitude of the partial correlation associated with each edge. If fdr=TRUE then in addition the p-values, q-values and posterior probabilities (=1 – local fdr) for each potential edge are computed. extract.network returns a data frame with a subset of …
1/2/2015 · network. test.edges : Graphical Gaussian Models: Assess Significance of Edges (and Directions) z.transform: Variance-Stabilizing Transformations of the Correlation Coefficient: ggm.estimate.pcor: Graphical Gaussian Models: Small Sample Estimation of Partial Correlation: GeneNet-package: The GeneNet package: GeneNet-internal: Internal GeneNet Functions: ecoli, 1/2/2015 · network.make.dot converts an edge list as obtained by network. test.edges into a dot file that can directly be used for plotting the network with graphviz. network.make.graph converts an edge list as obtained by network. test.edges into a graph object. edge.info shows the edge weights and the edge directions. node.degree shows number of edges connected to a node (bi-directional/undirected edges.
11/8/2020 · Finally, the network.test.edges function estimates the probabilities for all possible edges and lists them in descending order (for details see network.test.edges help). cutoff.ggm can be a single number or a vector of numbers.
7/2/2020 · View source: R/network.make.graph.R. Description. network.make.dot converts an edge list as obtained by network.test.edges into a dot file that can directly be used for plotting the network with graphviz. network.make.graph converts an edge list as obtained by network.test.edges into a graph object. edge.info shows the edge weights and the edge directions, 7/2/2020 · network. test.edges : Graphical Gaussian Models: Assess Significance of Edges (and… z.transform: Variance-Stabilizing Transformations of the Correlation… Browse all…
ecoli.edges = network. test.edges (pc, direct = TRUE, fdr = TRUE) dim(ecoli.edges) # ‘ The table lists all edges in the order strength of partial correlations: ecoli.edges [1: 5,] # ‘ # ‘ # Decide which edges to include in the network # ‘ To obtain a graph you need to select top ranking edges according to # ‘ a suitable criterion. Here are some suggestions: # ‘ # ‘ 1. Use local fdr cutoff 0.2, i.e. include all edges …
