birewire.induced.bipartite: Transform a SIF data frame into a dsg object (a list of...

In BiRewire: High-performing routines for the randomization of a bipartite graph (or a binary event matrix), undirected and directed signed graph preserving degree distribution (or marginal totals)

Description

The routine transforms the initial dsg graph in SIF format into a dsg object made of two bipartite graphs: one for positive edges and the other for negative edges.

Usage

birewire.induced.bipartite(g,delimitators=list(negative='-',positive='+'),sparse=FALSE)

Arguments

g	A dataframe in SIF format describing a dsg (for example the output of birewire.load.dsg;
delimitators	list(negative='-',positive='+') (default):a list with 'positive' and 'negative' names identifying the character encoding the relation;
sparse	FALSE (default): if TRUE the two bipartite graphs are saved as igraph bipartite graphs ;

Details

This fuction extract the positive and negative part of g and create a dsg object that can be used for example in the rewiring algorithm. Is is the inverse function of birewire.build.dsg.

Value

A list of two incidence matrix or bipartite igraph objects.

References

Iorio, F. and and Bernardo-Faura, M. and Gobbi, A. and Cokelaer, T.and Jurman, G.and Saez-Rodriguez, J. (2016) Efficient randomization of biologicalnetworks while preserving functionalcharacterization of individual nodes Bioinformatics 2016 1 (17):542 doi: 10.1186/s12859-016-1402-1.

Examples

data(test_dsg)
dsg=birewire.induced.bipartite(test_dsg)

BiRewire documentation built on Nov. 8, 2020, 8:09 p.m.