Scale-free properties of a network

Description

Function plots degree distribution of nodes in a given network.

Usage

networkProperties(igr)

Arguments

Details

Biological networks are thought to be scale-free. Scale-free networks follow a power-law distribution of the degrees of nodes in the network. This distribution is characterised by the degree exponent gamma, which for biological networks ranges between 2 and 3.

The function calculates the degree exponent(s) of given network(s) in comparison with degree exponents of biological networks derived from Reactome and BioGRID repositories. Both of these networks are built using functional interaction pairs extracted from mentioned repositories and provided in FIs data package (see example).

For each given igraph three types of plots are created: empirical cumulative distribution, degree distribution and power-law degree distribution on log-log scale with fitted trend line.

Value

A summary table containing number of nodes, number of edges and degree exponents for each given network.

Additionally two .pdf files are created. One containing empirical cumulative distribution frequency plots together with degree distributions and second with plots of power-law degree distribution on log-log scale.

Author(s)

Agata Michna, Martin Selmansberger

References

Barabasi, A. L. and Albert, R. (1999). Emergence of scaling in random networks. Science 286, 509-512.

Barabasi, A. L. and Oltvai, Z. N. (2004). Network biology: understanding the cell's functional organization. Nat. Rev. Genet. 5, 101-113.

See Also

FIs

Examples

## load "eSetObject" containing simulated time-course data
data(TCsimData)

## reconstruct gene association networks from time-course data
igr <- splineNetRecon(eSet = TCsimData, treatmentType = "T2", cutoff.ggm = c(0.8,0.9))

## check for scale-free properties of reconstructed networks (igraphs)
scaleFreeProp <- networkProperties(igr)
head(scaleFreeProp)

## the functional interaction pairs provided in FIs data package
library(FIs)
data(FIs)
names(FIs)
head(FIs$FIs_Reactome)
head(FIs$FIs_BioGRID)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(splineTCDiffExpr)
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: igraph

Attaching package: 'igraph'

The following objects are masked from 'package:BiocGenerics':

    normalize, union

The following objects are masked from 'package:stats':

    decompose, spectrum

The following object is masked from 'package:base':

    union

Loading required package: limma

Attaching package: 'limma'

The following object is masked from 'package:BiocGenerics':

    plotMA

Loading required package: GSEABase
Loading required package: annotate
Loading required package: AnnotationDbi
Loading required package: stats4
Loading required package: IRanges
Loading required package: S4Vectors

Attaching package: 'S4Vectors'

The following object is masked from 'package:igraph':

    compare

The following objects are masked from 'package:base':

    colMeans, colSums, expand.grid, rowMeans, rowSums


Attaching package: 'IRanges'

The following object is masked from 'package:igraph':

    simplify

Loading required package: XML
Loading required package: graph

Attaching package: 'graph'

The following object is masked from 'package:XML':

    addNode

The following objects are masked from 'package:igraph':

    degree, edges, intersection

Loading required package: gtools

Attaching package: 'gtools'

The following object is masked from 'package:igraph':

    permute

Loading required package: splines
Loading required package: GeneNet
Loading required package: corpcor
Loading required package: longitudinal
Loading required package: fdrtool
Loading required package: FIs
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/splineTCDiffExpr/networkProperties.Rd_%03d_medium.png", width=480, height=480)
> ### Name: networkProperties
> ### Title: Scale-free properties of a network
> ### Aliases: networkProperties
> ### Keywords: scale-free properties degree distribution
> 
> ### ** Examples
> 
> ## load "eSetObject" containing simulated time-course data
> data(TCsimData)
> 
> ## reconstruct gene association networks from time-course data
> igr <- splineNetRecon(eSet = TCsimData, treatmentType = "T2", cutoff.ggm = c(0.8,0.9))

----------------------------------------------------------------
All rows from eSetObject will be taken for network reconstruction

----------------------------------------------------------------
Longitudinal object
----------------------------------------------------------------
$time
[1]  1  4  8 16 24 32 40 48

$repeats
[1] 2 2 2 2 2 2 2 2

Estimating optimal shrinkage intensity lambda (correlation matrix): 0.6926 

Estimate (local) false discovery rates (partial correlations):
Step 1... determine cutoff point
Step 2... estimate parameters of null distribution and eta0
Step 3... compute p-values and estimate empirical PDF/CDF
Step 4... compute q-values and local fdr


-------------- igraph_0.8 --------------
Significant edges:  990 
    Corresponding to  0.05 %  of possible edges 
Number of nodes:  473 

-------------- igraph_0.9 --------------
Significant edges:  508 
    Corresponding to  0.03 %  of possible edges 
Number of nodes:  298 
> 
> ## check for scale-free properties of reconstructed networks (igraphs)
> scaleFreeProp <- networkProperties(igr)
> head(scaleFreeProp)
           nodes  edges degree_exponent
igraph_0.8   473   1980          1.5804
igraph_0.9   298   1016          1.6252
Reactome    6770 148733          1.2531
BioGRID    19127 213150          1.5292
> 
> ## the functional interaction pairs provided in FIs data package
> library(FIs)
> data(FIs)
> names(FIs)
[1] "FIs_Reactome" "FIs_BioGRID" 
> head(FIs$FIs_Reactome)
  interactorA interactorB
1       ITGA7       LAMC1
2       ITGA7         TNC
3       ITGA7       LAMA1
4       ITGA7       LAMA4
5       ITGA7       LAMB1
6       ITGA7       ITGB1
> head(FIs$FIs_BioGRID)
  interactorA interactorB
1      MAP2K4        FLNC
2        MYPN       ACTN2
3       ACVR1        FNTA
4       GATA2         PML
5        RPA2       STAT3
6        ARF1        GGA3
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>