netwAttr: Calculates network characteristics

In asakellariou/git-git.bioconductor.org-packages-mAPKL: A Hybrid Feature Selection method for gene expression data

Description

Calculate some basic network characteristics of the top ranked genes

Usage

    netwAttr(mAPKLObj, net="clr")

Arguments

mAPKLObj	An object of mAPKL class.
net	The network reconstruction method to be employed. The user may select between "clr" (default), "aracne.a" and "aracne.m".

Details

It calculates some basic network characteristics. Those include the "degree", the "closeness", the "betweenness", and finally the "transitivity" or else clustering coefficient. We calculate the weighted values for both local and global scores.
The three available network reconstruction options are:
clr: Context Likelihood or Relatedness Network
aracne.a: Algorithm for the Reconstruction of Accurate Cellular Networks (additive model)
aracne.m: Algorithm for the Reconstruction of Accurate Cellular Networks (multiplicative model)

Value

Upon successful completion, the function returns an NetAttr object.

Author(s)

Argiris Sakellariou

Examples

library(mAPKLData)
data(mAPKLData)
breast <- sampling(Data=mAPKLData, valPercent=40, classLabels="type", seed=135)
normTrainData <- preprocess(breast$trainData)
normTestData <- preprocess(breast$testData)

exprs(breast$trainData) <- normTrainData$clL2.normdata
exprs(breast$testData) <- normTestData$clL2.normdata

out.clL2 <- mAPKL(trObj=breast$trainData, classLabels="type",
valObj=breast$testData, dataType=7)

net.attr <- netwAttr(mAPKLObj=out.clL2)

asakellariou/git-git.bioconductor.org-packages-mAPKL documentation built on June 5, 2019, 8:49 p.m.