networkAnalyze: Network Topological Analysis

In Sharonxiaoyuan/eegc: Engineering Evaluation by Gene Categorization (eegc)

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")

Sharonxiaoyuan/eegc documentation built on April 17, 2022, 2:10 a.m.