Function that performs a random Walk with restart (RWR) on a given graph

1 |

`W` |
a numeric matrix representing the adjacency matrix of the graph |

`ind.positives` |
indices of the "core" positive examples of the graph. They represent the indices of W corresponding to the positive examples |

`gamma` |
restart parameter (def: 0.6) |

`tmax` |
maximum number of iterations (steps) (def: 1000) |

`eps` |
maximum allowed difference between the computed probabilities at the steady state (def. 1e-10) |

`norm` |
if TRUE (def) the adjacency matrix |

RWR performs a random Walk with restart on a given graph by performing 1 or more steps on the graph, depending on the value of the tmax parameter. The restart parameter expresses the probability of "restarting" from a "core" node at each step of the random walk algorithm. It stops also if the difference of the norm of the probabilities between two consecutive steps is less than eps.

A list with three elements:

`p` |
numeric vector. Probability of each node at the steady state or after tmax iterations |

`ind.positives` |
indices of the "core" positive examples of the graph (it is equal to the same input parameter) |

`n.iter` |
number of performed steps/iterations |

L. Lovasz, Random Walks on Graphs: a Survey, Combinatorics, Paul Erdos is Eighty, vol. 2, pp. 146, 1993.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | ```
# Application of the random walk with restart to the prediction of the
# DrugBank category Penicillins
# using the Tanimoto chemical structure similarity network
# between 1253 DrugBank drugs
library(bionetdata);
data(DD.chem.data);
data(DrugBank.Cat);
labels <- DrugBank.Cat[,"Penicillins"];
ind.pos <- which(labels==1);
# 2-step RWR
res <- RWR(DD.chem.data, ind.pos, tmax = 2);
## Not run:
# till to convergence
res <- RWR(DD.chem.data, ind.pos, tmax = 5000, eps=1e-6);
# 5 steps and higher gamma
res <- RWR(DD.chem.data, ind.pos, tmax = 5, gamma=0.8);
## End(Not run)
``` |

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