Learn R Programming

brainGraph (version 0.62.0)

set.brainGraph.attributes: Set a number of graph and vertex attributes useful in MRI analyses

Description

This function will set a number of graph, vertex, and edge attributes of a given igraph object.

Usage

set.brainGraph.attributes(g, atlas = NULL, modality = NULL, subject = NULL, group = NULL, rand = FALSE)

Arguments

g
An igraph object
atlas
A character vector indicating which atlas was used for the nodes
modality
A character vector indicating imaging modality (e.g. 'dti')
subject
A character vector indicating subject ID (default: NULL)
group
A character vector indicating group membership (default: NULL)
rand
Logical indicating if the graph is random or not (default: FALSE)

Value

g A copy of the same graph, with the following attributes:
Graph-level
Package version, atlas, density, connected component sizes, diameter, \# of triangles, transitivity, average path length, assortativity, clique number, global & local efficiency, modularity, vulnerability, hub score, rich-club coefficient, \# of hubs, edge asymmetry, and modality
Vertex-level
Degree, strength, betweenness/eigenvector and leverage centralities, hubs, transitivity (local), coreness, local & nodal efficiency, color (community), color (lobe), color (component), membership (community), membership (component), participation coefficient, within-module degree z-score, vulnerability, and coordinates (x, y, and z)
Edge-level
Color (community), color (lobe), color (component), edge betweenness, Euclidean distance (in mm)

See Also

components, diameter, clique_num, centr_betw, part.coeff, edge.betweenness, centr_eigen, hub.score, authority.score, transitivity, mean_distance, assortativity.degree, cluster_louvain, graph.efficiency, color.edges, rich.club.coeff, within_module_deg_z_score, coreness, edge_spatial_dist, vulnerability, centr_lev, edge_asymmetry, graph.knn, vertex_spatial_dist