get.DegreeHubStatistic: calculate module degree statistics based on random...

In MEGENA: Multiscale Clustering of Geometrical Network

Description

calculation of module p-values.

Usage

get.DegreeHubStatistic(subnetwork,n.perm = 100,doPar = FALSE,n.core = 4)

Arguments

subnetwork	a planar network as an igraph object.
n.perm	number of random networks generated, constraint with number of links and nodes same to "subnetwork".
doPar	TRUE/FALSE to parallelize.
n.core	number of cores/threads to use.

Details

Hub significance calculation functionality. Make sure that, if doPar = TRUE, register cores using registerDoParallel() from doParallel package.

Value

a data.frame table showing node-wise statistics.

Author(s)

Won-Min Song

Examples

## Not run: 
	rm(list = ls())
	data(Sample_Expression)
	ijw <- calculate.correlation(datExpr[1:100,],doPerm = 2)
	el <- calculate.PFN(ijw[,1:3])
	g <- graph.data.frame(el,directed = FALSE)

	out <- get.DegreeHubStatistic(subnetwork = g,n.perm = 100,doPar = FALSE,n.core = 4)

## End(Not run)

Example output

Loading required package: doParallel
Loading required package: foreach
Loading required package: iterators
Loading required package: parallel
Loading required package: igraph

Attaching package: ‘igraph’

The following objects are masked from ‘package:stats’:

    decompose, spectrum

The following object is masked from ‘package:base’:

    union

i = 1
i = 2
- outputting correlation results...
####### PFN Calculation commences ########
[1] "PFG is complete."
permutation no.:1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,

MEGENA documentation built on May 1, 2019, 8:07 p.m.