create.multiplexHetNetwork.topResults {RandomWalkRestartMH} | R Documentation

## Creates a Network with the top results of the Random Walk with restart on a Multiplex and Heterogeneous Network

### Description

`create.multiplexHetNetwork.topResults` is a function to create a network from the top results of the Random Walk with Restart on Multiplex and Heterogeneous networks algorithm (a `RWRMH_Results` object).

### Usage

    create.multiplexHetNetwork.topResults(RWRMH_Results_Object,
        MultiplexHetObject, bipartite_relations, bipartite_name, k=25)

### Arguments

`RWRMH_Results_Object` | A `RWRMH_Results` object generated by the function `Random.Walk.Restart.MultiplexHet` representing the results of the Random Ralk with restart on the multiplex and heterogeneous network described in the following argument.
`MultiplexHetObject` | A `MultiplexHet` object generated by the function `create.multiplexHet` representing a multiplex and heterogeneous network.
`bipartite_relations` | A data frame containing the relationships between the nodes of the multiplex network and the nodes of the second network of the heterogeneous system. The data frame should contain two columns: the first one with the nodes of the multiplex network; the second one with the nodes of the second network. Every node should be present in their corresponing network.
`bipartite_name` | A vector containing the name for the bipartite relations to be integrated as part of the resulting network. It is included as an attribute for all the bipartite edges of the resulting network. It's optional and its default value is "bipartiteRelations".
`k` | A numeric value between 1 and 200. It is the number of top ranked nodes to be included in the resulting multiplex network.

### Value

An `igraph` object containing the top `k` ranked multiplex nodes and the top `k` ranked second network nodes in the Random Walk with Restart on a Multiplex and Heterogeneous network algorithm. We include all the possible types of interactions between pairs of nodes according to the different layers of the multiplex network, the bipartite interactions and the second network type of interactions.

### Author(s)

Alberto Valdeolivas Urbelz alvaldeolivas@gmail.com

### See Also

`create.multiplexHet, isRWRMH_Results, Random.Walk.Restart.MultiplexHet create.multiplexNetwork.topResults`

### Examples

    m1 <- igraph::graph(c(1,2,1,3,2,3), directed = FALSE)
    m2 <- igraph::graph(c(1,3,2,3,3,4,1,4), directed = FALSE)
    multiObject <- create.multiplex(m1,m2)
    h1 <- igraph::graph(c("A","C","B","E","E","D","E","C"), directed = FALSE)
    bipartite_relations <- data.frame(m=c(1,3),h=c("A","E"))
    multiHetObject <-
        create.multiplexHet(multiObject, h1,bipartite_relations)
    MultiHetTranMatrix <- compute.transition.matrix(multiHetObject)
    Multiplex_Seeds <- c(1)
    SecondNet_Seeds <- c("E")
    RWR_MultiHetResults <-
        Random.Walk.Restart.MultiplexHet(MultiHetTranMatrix, multiHetObject,
            Multiplex_Seeds,SecondNet_Seeds)
    create.multiplexHetNetwork.topResults(RWR_MultiHetResults,multiHetObject,
        bipartite_relations)

[Package RandomWalkRestartMH version 1.6.0 Index]