summary_delta_con_similarity: Calculate DeltaCon similarity
In drostlab/edgynode: Comparison of Gene Regulatory Networks
View source: R/summary_delta_con_similarity.R
summary_delta_con_similarity R Documentation
Calculate DeltaCon similarity
Description
Computes the similarity matrix of an adjacency based on the DeltaCon method.
Adapted from previous implementation by Baoxu(Dash) Shi, Data Sciense Group,
University of Notre Dame
Usage
summary_delta_con_similarity(adj, degrees, .MAX_POWER = 10, debug = FALSE)
Arguments
adj
the adjacency matrix
degrees
the vector of node degrees
.MAX_POWER
maximum power for matrix inversion
debug
if TRUE, the function will gives you the time it spent on each step
Value
The similarity matrix S as described in the DeltaCon method
References
D. Koutra, J. T. Vogelstein, and C. Faloutsos: DeltaCon:
A Principled Massive-Graph Similarity Function. SIAM 2013: 162-170.
D. Koutra, T. Ke, U. Kang, D. H. Chau, H. K. Pao, C. Faloutsos:
Unifying Guilt-by-Association Approaches: Theorems and Fast Algorithms.
ECML/PKDD (2) 2011: 245-260
drostlab/edgynode documentation built on March 29, 2024, 10:36 a.m.
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View source: R/summary_delta_con_similarity.R
| summary_delta_con_similarity | R Documentation |
Calculate DeltaCon similarity
Description
Computes the similarity matrix of an adjacency based on the DeltaCon method. Adapted from previous implementation by Baoxu(Dash) Shi, Data Sciense Group, University of Notre Dame
Usage
summary_delta_con_similarity(adj, degrees, .MAX_POWER = 10, debug = FALSE)
Arguments
adj |
the adjacency matrix |
degrees |
the vector of node degrees |
.MAX_POWER |
maximum power for matrix inversion |
debug |
if TRUE, the function will gives you the time it spent on each step |
Value
The similarity matrix S as described in the DeltaCon method
References
D. Koutra, J. T. Vogelstein, and C. Faloutsos: DeltaCon: A Principled Massive-Graph Similarity Function. SIAM 2013: 162-170.
D. Koutra, T. Ke, U. Kang, D. H. Chau, H. K. Pao, C. Faloutsos: Unifying Guilt-by-Association Approaches: Theorems and Fast Algorithms. ECML/PKDD (2) 2011: 245-260
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.
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