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Compute the Laplacian matrix of a (directed) igraph
structure, preserving node/column/row names (and direction).
make_laplacian_adjmat(mat, directed = FALSE)make_laplacian_graph(graph, directed = FALSE)
An Laplacian matrix compatible with generating an expression matrix
precomputed adjacency matrix.
logical. Whether directed information is passed to the Laplacian matrix.
An igraph
object. May be directed or weighted.
Tom Kelly tom.kelly@riken.jp
See also generate_expression
for computing the simulated data,
make_sigma
for computing the Sigma (make_distance
for computing distance from a graph object,
make_state
for resolving inhibiting states.
See also plot_directed
for plotting graphs or
heatmap.2
for plotting matrices.
See also make_commonlink
or make_adjmatrix
for computing input matrices.
See also igraph
for handling graph objects.
Other graphsim functions:
generate_expression()
,
make_adjmatrix
,
make_commonlink
,
make_distance
,
make_sigma
,
make_state
,
plot_directed()
Other graph conversion functions:
make_adjmatrix
,
make_commonlink
# construct a synthetic graph module
library("igraph")
graph_test_edges <- rbind(c("A", "B"), c("B", "C"), c("B", "D"))
graph_test <- graph.edgelist(graph_test_edges, directed = TRUE)
# compute Laplacian matrix for toy example
laplacian_matrix <- make_laplacian_graph(graph_test)
laplacian_matrix
# compute Laplacian matrix from adjacency matrix
adjacency_matrix <- make_adjmatrix_graph(graph_test)
laplacian_matrix <- make_laplacian_adjmat(adjacency_matrix)
laplacian_matrix
# construct a synthetic graph network
graph_structure_edges <- rbind(c("A", "C"), c("B", "C"), c("C", "D"), c("D", "E"),
c("D", "F"), c("F", "G"), c("F", "I"), c("H", "I"))
graph_structure <- graph.edgelist(graph_structure_edges, directed = TRUE)
# compute Laplacian matrix for toy network
graph_structure_laplacian_matrix <- make_laplacian_graph(graph_structure)
graph_structure_laplacian_matrix
# import graph from package for reactome pathway
# TGF-\eqn{\Beta} receptor signaling activates SMADs (R-HSA-2173789)
TGFBeta_Smad_graph <- identity(TGFBeta_Smad_graph)
# compute Laplacian matrix for TGF-\eqn{\Beta} receptor signaling activates SMADs
TGFBeta_Smad_laplacian_matrix <- make_laplacian_graph(TGFBeta_Smad_graph)
dim(TGFBeta_Smad_laplacian_matrix)
TGFBeta_Smad_laplacian_matrix[1:12, 1:12]
# visualise matrix
library("gplots")
heatmap.2(TGFBeta_Smad_laplacian_matrix, scale = "none", trace = "none",
col = colorpanel(50, "blue", "white", "red"))
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