networkAnalyze {eegc} | R Documentation

## Network Topological Analysis

### Description

This function analyzes the topological structure of gene regulation network (GRN) by calculating the "degree", "betweenness", "closeness" and "stress" parameters, and output the centrality values for given genes in each gene categories.

### Usage

    networkAnalyze(grn.data, cate.gene, centrality = c("degree", "betweenness",
    "stress", "closeness"), mode = c("all","in", "out", "total"))

### Arguments

`grn.data` | a data frame with two columns named "TF" and "TG" to specify the genes as transcription regulators (TF) and target genes (TG) being regulated.
`cate.gene` | a list of the five gene categories as nodes in the network, alternatively output by `categorizeGene`.
`centrality` | charactor string of "degree", "betweenness", "closeness" and "stress" to calculate the centrality of network built from input `grn.data`, see `degree`. `betweenness`, `closeness`, and `stresscent` for details.
`mode` | character string of "all", "in", "out" and "total", only used when `centrality` is "degree" or "closeness", see `degree`, `closeness` for details.

### Value

data frame with genes and centrality scores.

### Examples

    # load the CellNet GRN and gene categories
    data(human.grn)
    data(cate.gene)

    # specify a tissue-specifc network
    tissue = "Hspc"
    degree = networkAnalyze(human.grn[[tissue]], cate.gene = cate.gene,
                           centrality = "degree", mode ="all")

[Package eegc version 1.6.1 Index]