fRNC: ncRNA module search functions

#' fRNC: Search for modules in a node-weighted ncRNA network
#'
#' fRNC 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.
#'
#' @details
#' This package takes three types of data as input: a list of genes with
#' association p-values and logFC, a human ncRNA network. generate_graph constructs a
#' node-weighted ncRNA network. runmodule performs  module
#' search upon the node-weighted ncRNA network.
#'
#' @references
#' @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
#' @references 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.
#' @docType package
#' @name fRNC-package
#' @aliases fRNC
#' @import igraph
#' @importFrom methods is
#' @importFrom stats pnorm sd qnorm na.omit pbeta model.matrix optim phyper runif var
#' @importFrom grDevices colorRampPalette dev.off png
#' @importFrom graphics plot symbols
#' @importFrom utils data write.table
#' @importFrom edgeR cpm DGEList calcNormFactors estimateGLMCommonDisp estimateGLMTrendedDisp estimateGLMTagwiseDisp glmFit glmLRT topTags
#' @importFrom limma makeContrasts lmFit contrasts.fit eBayes topTable
#' @importFrom Biobase exprs
#' @importFrom survival coxph
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