Several regulators (specifically TFs) might have extremely overlapping target genes. In order to identify clusters of highly similar regulators (mainly TFs) we implemented a network simplification algorithm in biRte: We construct the biadjacency matrix of the complete bipartite regulator target-gene graph and then calculate a single linkage clustering of regulators based on the Tanimoto-Jaccard similarity of their target genes. The dendrogram is cut at a defined height (default: 0.1) to idenfity resulting groups. The algorithm is meant to simplify the inference of active regulators, because the resulting regulator clusters have more dissimilar target gene profiles.

1 | ```
simplify(affinities, cutoff=0.9)
``` |

`affinities` |
original regulator-target gene network |

`cutoff` |
cut dendrogram at height 1 - cutoff (i.e. similarity cutoff) |

clustered / simplified network

Holger Froehlich

1 2 3 | ```
# artificial data
data(humanNetworkSimul)
affinities2 = simplify(affinities2)
``` |

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

All documentation is copyright its authors; we didn't write any of that.