createNet {coexnet} | R Documentation

## Creating a co-expression network from expression matrix.

### Description

From an expression matrix, this function creates a co-expression network like a graph object using a threshold value and one similarity function.

### Usage

    createNet(expData, method, threshold)

### Arguments

`expData` | A whole expression matrix or differentially expressed genes matrix, it may be stored in a SummarizedExperiment object.
`method` | A function to calculate the similarity matrix between genes. It can be "correlation" to use Pearson function or "mutual information" to use a based on entropy information function.
`threshold` | A value between 0 and 1 to filter the similarity matrix and create the co-expression network.

### Value

An undirected co-expression network as igraph object.

### Author(s)

Juan David Henao Sanchez <judhenaosa@unal.edu.co>

Liliana Lopez Kleine <llopezk@unal.edu.co>

### See Also

`findThreshold` to obtain a threshold value based on biology network assumptions.

### Examples

    # Loading data

    pathfile <- system.file("extdata","expression_example.txt",package = "coexnet")
    data <- read.table(pathfile,stringsAsFactors = FALSE)

    # Building the network

    cor_pearson <- createNet(expData = data,threshold = 0.7,method = "correlation")
    cor_pearson

    mut_inf <- createNet(expData = data,threshold = 0.5,method = "mutual information")
    mut_inf

[Package coexnet version 1.2.0 Index]