BiRewire-package: The BiRewire package

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

R package for computationally-efficient rewiring of bipartite graphs (or randomisation of 0-1 tables with prescribed marginal totals), undirected and directed signed graphs (dsg). The package provides useful functions for the analysis and the randomisation of large biological datasets that can be encoded as 0-1 tables, hence modeled as bipartite graphs by considering a 0-1 table as an incidence matrix, and for data that can be encoded as directed signed graphs such as patways and signaling networks. Large collections of such randomised tables can be used to approximate null models, preserving event-rates both across rows and columns, for statistical significance tests of combinatorial properties of the original dataset. The package provides an interface to a sampler routine useful for generating correctly such collections. Moreover a visual monitoring for the Markov Chain underlying the swithicng algorithm has been implemented. Since version 3.6.0 the SA can be performed also using matrices with NAs. In this case the positions of the NAs are preserved as the degree distribution. This extension is limited when the tables are provided instead of the graphs and does not work for the dsg.

Details

Summary:

Package:	BiRewire
Version:	3.7.0
Date: 2017-02-27
Require: slam, igraph, tsne, Matrix, R>=2.10
URL: http://www.ebi.ac.uk/~iorio/BiRewire
License:	GPL-3

Author(s)

Andrea Gobbi [aut], Davide Albanese [cbt], Francesco Iorio [cbt], Giuseppe Jurman [cbt].

Maintainer: Andrea Gobbi <[e-mail]>

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.

Gobbi, A. and Iorio, F. and Dawson, K. J. and Wedge, D. C. and Tamborero, D. and Alexandrov, L. B. and Lopez-Bigas, N. and Garnett, M. J. and Jurman, G. and Saez-Rodriguez, J. (2014) Fast randomization of large genomic datasets while preserving alteration counts Bioinformatics 2014 30 (17): i617-i623 doi: 10.1093/bioinformatics/btu474.

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.

Jaccard, P. (1901), Étude comparative de la distribution florale dans une portion des Alpes et des Jura, Bulletin de la Société Vaudoise des Sciences Naturelles 37: 547–579.

R. Milo, N. Kashtan, S. Itzkovitz, M. E. J. Newman, U. Alon (2003), On the uniform generation of random graphs with prescribed degree sequences, eprint arXiv:cond-mat/0312028 Csardi, G. and Nepusz, T (2006)
Van der Maaten, L.J.P. and Hinton, G.E., Visualizing High-Dimensional Data Using t-SNE. Journal of Machine Learning Research 9(Nov):2579-2605, 2008 The igraph software package for complex network research, InterJournal, Complex Systems http://igraph.sf.net

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