fit.structure: Calculate structural fitness of networks

In wyguo/RLowPC: Inference of co-expression gene network using relevance low order partial correlation from large scale expression data

Description

The function is to used to calcuate the scale-free or modularity fitness of networks. The scale-free fitness is calcuated as -R^2\times slope of the fit index of the model. Please refer to the package WGCNA [1,2] for details.The fitness of modularity is computed using igraph package [3].

Usage

fit.structure(edgelist, method = "scale-free")

Arguments

edgelist	a data frame of network edge list, with regulators in first column, target genes in second column and edge weights in third column.
method	a character string used to calculate the structural fitness. Options are "scale-free" and "modularity".

Value

fit.structure returns a numeric value measures the structural fitness.

References

[1] Langfelder P, Horvath S: WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics 2008, 9:559.

[2] Zhao W, Langfelder P, Fuller T, Dong J, Li A, Hovarth S: Weighted gene coexpression network analysis: state of the art. J Biopharm Stat 2010, 20(2):281-300.

[3] Csardi G, Nepusz T: The igraph software package for complex network research. InterJournal 2006, Complex Systems:1695.

Examples

 library(RLowPC)
 data(gnwdata)
 edgelist<-gnwdata$size500$net1
 edgelist[,3]<-1
 fit.structure(edgelist,method='scale-free')
 fit.structure(edgelist,method='modularity')

wyguo/RLowPC documentation built on May 4, 2019, 12:04 p.m.