| backbone {backbone} | R Documentation |
Provides methods for extracting from an unweighted and sparse subgraph (i.e., a backbone) that contains only the most "important" edges in a weighted bipartite projection, a non-projection weighted network, or an unweighted network.
Available backbone extraction functions include:
For weighted bipartite projections of weighted bipartite networks: osdsm().
For weighted bipartite projections of binary bipartite networks: fixedfill(), fixedrow(), fixedcol(), sdsm(), and fdsm().
For non-projection weighted networks: global(), disparity().
For unweighted networks: sparsify(), sparsify.with.skeleton(), sparsify.with.gspar(), sparsify.with.lspar(), sparsify.with.simmelian(), sparsify.with.jaccard(), sparsify.with.meetmin(), sparsify.with.geometric(), sparsify.with.hypergeometric(), sparsify.with.localdegree(), sparsify.with.quadrilateral().
For all networks: backbone.suggest() will examine the data and suggest an appropriate backbone function
The package also includes some utility functions:
fastball() - Fast marginal-preserving randomization of binary matrices
bicm() - Compute probabilities under the bipartite configuration model
bipartite.from.probability(), bipartite.from.sequence(), and bipartite.from.distribution() - Generate random bipartite networks with given edge probability, degree sequences, or degree distributions.
For additional documentation and background on the package functions, see vignette("backbone").
For updates, papers, presentations, and other backbone news, please see www.rbackbone.net
Domagalski, R., Neal, Z. P., and Sagan, B. (2021). backbone: An R Package for Backbone Extraction of Weighted Graphs. PLoS ONE, 16, e0244363. doi: 10.1371/journal.pone.0244363
Neal, Z. P., Domagalski, R., and Sagan, B. (2021). Comparing Alternatives to the Fixed Degree Sequence Model for Extracting the Backbone of Bipartite Projections. Scientific Reports, 11, 23929. doi: 10.1038/s41598-021-03238-3