Motif Analysis in Multi-Level Networks

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Documentation for package ‘motifr’ version 1.0.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

compare_to_baseline	Compare motif occurence in empirical network to occurence in a baseline model
count_motifs	Count multi-level motifs
critical_dyads	List critical dyads
directed_dummy_net	Two-level directed network dummy example
dummy_net	Three-level network dummy example
edge_contribution	List edge contribution
exemplify_motif	Returns an example for a motif found in a given network
explore_motifs	Explore the motif zoo interactively in a shiny app
identify_gaps	List gaps
induced_level_subgraph	Returns subgraph induced by one level of the network
is.directed	Checks whether the given network is directed
large_directed_dummy_net	Large two-level directed network dummy example
list_motifs	Lists motifs of a given class or all motifs with a given signature
ml_net	Two-level network example (wetlands management)
motifs_distribution	Compute statistical properties (expectation and variance) of the distribution of motifs in a baseline model
motif_summary	Summary for motif counts and Erdős-Rényi distribution
plot_critical_dyads	Plot critical dyads in network visualisation
plot_gaps	Plot gaps in network visualisation
plot_gaps_or_critical_dyads	Helper function for plotting gaps and critical edges
plot_mnet	Visualize a multi-level network (using ggraph)
show_motif	Plots an example for a motif with given motif identifier string taken from the given graph.
simulate_baseline	Simulate a baseline baseline model
supported_classes	Lists all supported motif classes for a given signature
supported_signatures	Lists all supported signatures
tidygraph_dummy_net	Two-level tidygraph network example
to_py_graph	Translate multi-level statnet or igraph network object to Python networkx object
update_motifr	Checks for updates for motifr's Python core, the sma package