netwAttr {mAPKL} | R Documentation

## Calculates network characteristics

### 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)

[Package mAPKL version 1.16.0 Index]