runmodule: Run module search function

In leiming8886/fRNC: ncRNA module search functions

Run module search function

Description

runmodule constructs a node-weighted ncRNA network, performs module searching, generates simulation data from random networks, normalizes module scores using simulation data, removes un-qualified modules, and orders resultant modules according to their significance.

Usage

runmodule(
  network,
  gene2weight,
  method = c("global", "local"),
  expr1 = NULL,
  expr2 = NULL,
  d = 2,
  r = 0.1,
  seletN = NULL,
  FDR = 1e-14,
  lambda = 0.5,
  min.size = 5,
  maxsize = 15,
  issymbol = TRUE
)

Arguments

network	A data frame containing a symbolic edge list of the ncRNA network in which the columns must contain "node_gene_ID", "type", "target_gene_Name"
gene2weight	A weigth data frame containing three columns:"type","gene", "weight" the first "type" the type of the gene identifier; lncRNA, miRNA, circRNA and RBP the second gene is unique, gene identifier (should be coordinate with the node symbol used in ncRNA network); the third weight is gene-based p-value or corrected p-value derived from differentially gene analysis or survival analysis
method	a character string indicating which the search method is to be computed . One of "global" (default, refer to Heinz method), "local ( refer to GS method)": can be abbreviated
expr1	the expression matrix of the case sample
expr2	the expression matrix of the control sample
d	An integer used to define the order of neighbour genes to be searched in the method of the method "local" . This parameter is default set up as 2
r	A float indicating the cut-off for increment during module expanding process in the method of the method "local". Greater r will generate smaller module. Default is 0.1.
seletN	a vector: gene identifier IDs, or a gene identifier ID, for example "MIMAT0000461", or c("MIMAT0000461", "ENSG00000250742")
FDR	Numeric value, from the false discovery rate a p-value threshold is calculated. P-values below this threshold are considered to be significant The FDR can be used to control the size of the maximum scoring module
min.size	An integer: the min numbel of size of the module for user settings in the method of "global", default 5.
maxsize	An integer: the max numbel of size of the module for user settings in the method of "global", default 15.
issymbol	Boolean value, whether to set the node attribute "symbol"(gene symbol) in the network.

Value

runmodule returns a list containing relevant data and results, including:

GNCW	the node-weighted network used for searching
module	list of genes comprising each module, named for the seed gene if the method is "local" or the igraph class of the module if the method is "global"
module.score.matrix	contains Zm, Zn

References

Hongbo Shi, Jiayao Li, Qiong Song et al. (2019) Systematic identification and analysis of dysregulated miRNA and transcription factor feed-forward loops in hypertrophic cardiomyopathy

Peilin Jia, Siyuan Zheng, Jirong Rong, Wei Zheng, Zhongming Zhao. (2011) Bioformatics. dmGWAS: dense module searching for genome-wide association studies in protein-protein interaction networks.

Daniela Beisser, Gunnar W. Klau, Thomas Dandekar et al. (2019) BioNet: an R-Package for the functional analysis of biological networks

Examples

## Not run: 
data("dataN")
gene2weight <- combinp(dataN[,c("type","logFC","PValue")])
interac <- interStringency(type = "transcription", spec ="hg",
				stringency = "strict")
interac <- interac[,c("node_gene_ID","type","target_gene_ID")]
 res.list_global <- runmodule(network = interac, gene2weight, 
 								method = "global",FDR = 1e-14)
 res.list_local <- runmodule(network = interac, gene2weight, 
 		method = "local",maxsize=15, seletN = "MIMAT0000461")
 

## End(Not run)

leiming8886/fRNC documentation built on Feb. 21, 2023, 4:12 p.m.