simplify: Simplify regulator-target gene network via clustering.
In birte: Bayesian Inference of Regulatory Influence on Expression (biRte)
Description
Usage
Arguments
Value
Author(s)
Examples
Description
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.
Usage
1
simplify(affinities, cutoff=0.9)
Arguments
affinities
original regulator-target gene network
cutoff
cut dendrogram at height 1 - cutoff (i.e. similarity cutoff)
Value
clustered / simplified network
Author(s)
Holger Froehlich
Examples
1
2
3
# artificial data
data(humanNetworkSimul)
affinities2 = simplify(affinities2)
birte documentation built on May 2, 2019, 12:32 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description Usage Arguments Value Author(s) Examples
Description
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.
Usage
1 | simplify(affinities, cutoff=0.9)
|
Arguments
affinities |
original regulator-target gene network |
cutoff |
cut dendrogram at height 1 - cutoff (i.e. similarity cutoff) |
Value
clustered / simplified network
Author(s)
Holger Froehlich
Examples
1 2 3 | # artificial data
data(humanNetworkSimul)
affinities2 = simplify(affinities2)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.