birewire.visual.monitoring.bipartite: Visual monitoring of the Markov chain underlying the SA for...

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

This function generates a cascade-sampling from the model at different switching steps given in sequence. For each step the routine computes the pairwise Jaccard distance (1-JI) among the samples and perfroms, on the resulting matix, a dimentional scaling reduction (using tsne). If display is set to TRUE the relative plot is displayed.

Usage

birewire.visual.monitoring.bipartite(data,accuracy=0.00005,verbose=FALSE,MAXITER_MUL=10,
  exact=FALSE,n.networks=100,perplexity=15,sequence=c(1,5,100,"n"),ncol=2,
  nrow=length(sequence)/ncol,display=TRUE)

Arguments

data	The initial bipartite graph, either an incidence matrix or an igraph bipartite graph object. Since 3.6.0, if the matrix is provided, such matrix can contain also NAs and the position of such entries will be preserved by the SA;
accuracy	0.00005 (default) is the desired level of accuracy reflecting the average distance between the Jaccard index at the N-th step and its analytically derived fixed point in terms of fracion of common edges;
verbose	TRUE (default). When TRUE a progression bar is printed during computation.
MAXITER_MUL	10 (default). If exact==TRUE in order to prevent a possible infinite loop the program stops anyway after MAXITER_MUL*max.iter iterations;
exact	FALSE (default). If TRUE the program performs max.iter swithcing steps, otherwise the program will count also the not-performed swithcing steps;
n.networks	100 (default): the number of network generated for each step defined in sequence ;
perplexity	15 (default): the value of perplexity passed to the function tsne;
sequence	c(1,5,100,"n")(default) the sequence of step for wich generating a sampler (seebirewire.sampler.bipartite)
ncol	2 (default). The number of column in the plot;
nrow	length(sequence)/ncol (default). The number of row in the plot;
display	TRUE (default). If TRUE the result is displayed.

Details

For each value p in sequence (it that can also contain the special character "n", see birewire.rewire.bipartite), the routine generates n.networks sampled each p SS from the SA initialized with the given data. Pariwise distance are computed using the Jaccard distance and the resulting matrix is the input for the dimensional scaling performed by the function tsne. An explorative plot is displayed if display is set to TRUE.

Value

A list containing the list containing the distance matrices dist and the list containing the tsne results tsne.

Author(s)

Andrea Gobbi
Maintainer: Andrea Gobbi <[e-mail]>

References

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

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

Examples

library(BiRewire)
g <- graph.bipartite( rep(0:1,length=100), c(1:100))
birewire.visual.monitoring.bipartite(g,display=FALSE,n.networks=10)

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