Description Usage Arguments Value Author(s) See Also Examples

View source: R/InduceNetworks.R

`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).

1 2 | ```
create.multiplexHetNetwork.topResults(RWRMH_Results_Object,
MultiplexHetObject, bipartite_relations, bipartite_name, k=25)
``` |

`RWRMH_Results_Object` |
A |

`MultiplexHetObject` |
A |

`bipartite_relations` |
A data frame containing the relationships (bipartite interactions) between the nodes of the first multiplex network and the nodes of the second multiplex of the heterogeneous system. The data frame should contain two or three columns: the first one with the nodes of the multiplex network; the second one with the nodes of the second network. The third one is not mandatory and it should contain the weights. Every node should be present in their corresponding multiplex 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. |

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.

Alberto Valdeolivas Urbelz alvaldeolivas@gmail.com

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ```
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_1 <- create.multiplex(list(m1=m1,m2=m2))
h1 <- igraph::graph(c("A","C","B","E","E","D","E","C"), directed = FALSE)
multiObject_2 <- create.multiplex(list(h1=h1))
bipartite_relations <- data.frame(m=c(1,3),h=c("A","E"))
multiHetObject <-
create.multiplexHet(multiObject_1, multiObject_2,bipartite_relations)
MultiHetTranMatrix <- compute.transition.matrix(multiHetObject)
Multiplex1_Seeds <- c(1)
Multiplex2_Seeds <- c("E")
RWR_MultiHetResults <-
Random.Walk.Restart.MultiplexHet(MultiHetTranMatrix, multiHetObject,
Multiplex1_Seeds,Multiplex2_Seeds)
create.multiplexHetNetwork.topResults(RWR_MultiHetResults,multiHetObject,
bipartite_relations)
``` |

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