graphComponents.Rd

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/edgefinder.R
\name{graphComponents}
\alias{graphComponents}
\title{Find clusters, and return node characteristics.}
\usage{
graphComponents(A, minCtr = 5, type = 1)
}
\arguments{
\item{A}{An adjacency Matrix(0/1).}

\item{minCtr}{The minimum centrality value to be considered for a cluster center (default=5).}

\item{type}{Determines how the centrality measure is computed.}
}
\value{
A data frame with the following columns
\itemize{
 \item{labels} {Node label (e.g. gene names).}
\item{degree} {Node degree.}
\item{cc} {Node clustering coefficient.}
\item{ctr} {Node centrality measure: (type\*CC+1)\*deg, or CC\*deg if type is negative.}
\item{clustNo} {Cluster number.}
\item {iscenter} {1 for the node was chosen as the cluster's center, 0 otherwise.}
\item {intEdges} {Number of edges from the node to nodes in the same cluster.}
\item {extEdges} {Number of edges from the node to nodes NOT in the same cluster.}
\item {distCenter} {Standardized Manhattan distance to the central node.}
}
}
\description{
Take an adjacency Matrix as input and find clusters. For each node, find the degree and clustering coefficient (CC). Then, calculate a centrality measure (type\*CC+1)\*deg. For type=0, it's just the degree. Note that setting type=1 we assign a higher value to nodes that not only have many neighbors, but the neighbors are highly interconnected. For example, suppose we have two components with k nodes, one has a star shape, and the other is a complete graph. With type=0 both graphs will get the same value, but with type=1 the complete graph will be picked by the algorithm first. Setting type to a negative value gives CC\*deg as the centrality measure.
}
\examples{
\donttest{
   data(SIM)
   Sres <- edgefinder(SIM, ttl = "hub network")
   SimComp <- graphComponents(Sres$AdjMat)
   head(SimComp)
}
}