NetCen: Compute the centrality metrics for the nodes composing the...
In GALLO: Genomic Annotation in Livestock for Positional Candidate LOci
NetCen R Documentation
Compute the centrality metrics for the nodes composing the network generated by the NetVis function
Description
Compute the centrality metrics for the nodes composing the network generated by the NetVis function
Usage
NetCen(data, g1, g2)
Arguments
data
A data frame containing the relationship between the two groups to be represented in the network
g1
Name of the column containing the labels of the first group that will be used to create the network
g2
Name of the column containing the labels of the second group that will be used to create the network
Details
This function returns the following centrality metrics for each node that composed the network: Degree (The number of edges incident to the node), Betweenness (The fraction of shortest paths between pairs of nodes that pass through the node), Closeness (The inverse of the sum of the shortest path distances from the node to all other nodes), and Eigenvector Centrality (The centrality measure based on the eigenvector of the adjacency matrix).
Value
A data frame with the centrality metrics for each node in the network.
GALLO documentation built on June 22, 2024, 9:17 a.m.
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| NetCen | R Documentation |
Compute the centrality metrics for the nodes composing the network generated by the NetVis function
Description
Compute the centrality metrics for the nodes composing the network generated by the NetVis function
Usage
NetCen(data, g1, g2)
Arguments
data |
A data frame containing the relationship between the two groups to be represented in the network |
g1 |
Name of the column containing the labels of the first group that will be used to create the network |
g2 |
Name of the column containing the labels of the second group that will be used to create the network |
Details
This function returns the following centrality metrics for each node that composed the network: Degree (The number of edges incident to the node), Betweenness (The fraction of shortest paths between pairs of nodes that pass through the node), Closeness (The inverse of the sum of the shortest path distances from the node to all other nodes), and Eigenvector Centrality (The centrality measure based on the eigenvector of the adjacency matrix).
Value
A data frame with the centrality metrics for each node in the network.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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