#' BioNetWork Function
#'
#' This function allows you to analyze genes from a signature using the bionet algorithm from the package "bionet" and uses interactome dataset
#' @param File ? Defaults to NULL.
#' @keywords bioNetwork
#' @export
#' @examples
#' bioNetwork() will analyze network for vorinostat signature from ilincs
bioNetwork<-function(File=NULL,upload2=NULL,phy=FALSE,layOut=1,package=FALSE){
library(igraph)
library(BioNet)
library(DLBCL)
data(interactome)
library(visNetwork)
if(!is.null(File))
{
if(is.null(upload2)){
logic<-File
}
else{
logic<-read.csv(file=File,sep='\t')
colnames(logic)<-c("signatureID","GeneID","GeneNames","coefficients","Pvals")
}
}
else{
logic<-read.csv(file=system.file("extdata", "sig_try3.tsv", package = "SigNetA"),sep='\t')
}
#source("geneInfoFromPortals.R")
geninfo<-geneInfoFromPortals(geneList=as.character(logic$GeneID),symbol=T,names=F)
geneLabels<-apply(geninfo,1,function(x) paste(x[2],"(",as.integer(x[1]),")",sep=""))
pval<-as.numeric(logic$Pvals)
names(pval)<-geneLabels
logFC<-as.numeric(logic$coefficients)
names(logFC)<-geneLabels
subnet <- subNetwork(geneLabels, interactome)
subnet <- rmSelfLoops(subnet)
system.time( fb <- fitBumModel(pval, plot = FALSE))
#err2<<-try(scoreNodes(subnet, fb, fdr = 0.1),silent=TRUE)
#if(class(err2)=="try-error"){
# output$input_error=renderText("No significant subnetwork generated.Please upload another Signature.")
# }
#else{
#output$input_error=renderText("")
system.time(scores <- scoreNodes(subnet, fb, fdr = 0.1))
#err<<-try(runFastHeinz(subnet, scores),silent=TRUE)
# if(class(err) == "try-error"){
#
#
# output$input_error=renderText("No significant subnetwork generated.Please upload another Signature.")
# stopifnot(class(err) == "try-error")
#
# }
# else{
#output$input_error=renderText("")
system.time(module <- runFastHeinz(subnet, scores))
# source("rashidplotmodule.R")
pdf("wor.pdf")
colorNet<-plotmodule2(module, scores = scores, diff.expr = logFC)
dev.off()
#library(rcytoscapejs)
## IGRAPH LAYOUTS FOR RCYTOSCAPEJS2
if(layOut=="1"){
l<-layout_with_fr(colorNet$n)
visLay<-"layout_with_fr"
}
else if(layOut=="3"){
l<-layout_on_grid(colorNet$n)
visLay<-"layout_on_grid"
}
else if(layOut=="4"){
l<-layout_with_kk(colorNet$n)
visLay<-"layout_with_kk"
}
else if(layOut=="5"){
l<-layout_on_sphere(colorNet$n)
visLay<-"layout_on_sphere"
}
else if(layOut=="6"){
l<-layout_with_graphopt(colorNet$n)
visLay<-"layout_with_graphopt"
}
id <- nodes(module)
name <- id
label<-id #visNetwork and interactome
nodeData <- data.frame(id, name, stringsAsFactors=FALSE)
nodeVisData<-data.frame(id,label,stringsAsFactors = FALSE) #visNetwork
nodeData$color<- rep("#00FF0F",nrow(nodeData)) #changed color of nodes
nodeData$shape <- "none" #default shape
nodeData$href <- paste0("http://www.ncbi.nlm.nih.gov/gene/",gsub("[\\(\\)]", "", regmatches(nodeData$name, gregexpr("\\(.*?\\)", nodeData$name))))
nodeData$geneID<-gsub("[\\(\\)]", "", regmatches(nodeData$name, gregexpr("\\(.*?\\)", nodeData$name)))
nodeNameEntrez<-nodeData$name
nodeData$name<-sub(" *\\(.*", "", nodeData$name)
nodeData$Diff_Exp="none"
nodeData$score="none"
for(i in 1:length(name)){
nodeData[i,3]<-colorNet$c[i];
nodeData[i,7]<-colorNet$d[i]
nodeData[i,8]<-colorNet$sc[i]
}
for(i in 1:length(name)){
if(colorNet$s[i]=="csquare")
#colorNet$s[i]<-"rectangle"
colorNet$s[i]<-"ellipse"
else
colorNet$s[i]<-"ellipse"
nodeData[i,4]<-colorNet$s[i];
}
statNet<<-nodeData
ltn<-unlist(lapply(edgeL(module),function(x) length(x[[1]])))
source<-unlist(lapply(1:length(ltn),function(x) rep(id[x],ltn[x])))
target<-unlist(lapply(edgeL(module), function(x) id[unlist(x)]))
vect<-c()
for(i in 1:length(target)) #extracting the value from the key value pair
vect[i]<-target[[i]]
edgeData <- data.frame(source, target, stringsAsFactors=FALSE)
# network <- createCytoscapeJsNetwork(nodeData, edgeData)
# for(i in 1:length(target)){
#
# network$edges[[i]]$data$edgeTargetShape="none" #making undirected graphss
#
# }
# for(i in 1:length(target)){
# for(j in i:length(target)){
# if(network$edges[[i]]$data$source == network$edges[[j]]$data$target)
# network$edges[[j]]$data$target= "none"
#
# }
#
# }
##VisNetwork###########
nodeVisData$color.background<-rep("blue",nrow(nodeData))
nodeVisData$borderWidth <- 2
nodeVisData$color.border <- "black"
nodeVisData$title<-"<p>Hello world</p>"
nodeVisData$shape<-"dot"
nodeVisData$size<-0
nodeVisData$id<-sub(" *\\(.*", "", nodeVisData$id)
nodeVisData$label<-sub(" *\\(.*", "", nodeVisData$label)
normalize <- function(x) {
return (((x - min(x)) / (max(x) - min(x)))*50)
}
for(i in 1:length(label)){
nodeVisData[i,3]<-colorNet$c[i];
nodeVisData[i,6]<-paste0("<p><b>Gene name:</b>",statNet$name[i],"</p><br><p><b>Gene ID:</b>",statNet$geneID[i],"</p><br><p><b>Differential Expression:</b>",statNet$Diff_Exp[i],"</p><p><b>NCBI link:</b><a href='",statNet$href[i],"' target='_blank'>",statNet$href[i],"</a></p>")
if(colorNet$d[i]<0)
{
nodeVisData[i,8]<-colorNet$d[i] * -1
}
else{
nodeVisData[i,8]<-colorNet$d[i]
}
}
nodeVisData<-data.frame(nodeVisData[1:7], apply(nodeVisData["size"],2, normalize) )
for( l in 1:length(nodeVisData$size)){
if(nodeVisData$size[l]<1)
{
nodeVisData$size[l]<-1
}
}
ltn<-unlist(lapply(edgeL(module),function(x) length(x[[1]])))
sourceVis<-unlist(lapply(1:length(ltn),function(x) rep(id[x],ltn[x])))
targetVis<-unlist(lapply(edgeL(module), function(x) id[unlist(x)]))
vect<-c()
for(i in 1:length(targetVis)) #extracting the value from the key value pair
vect[i]<-targetVis[[i]]
sourceVis<-sub(" *\\(.*", "", sourceVis)
targetVis<-sub(" *\\(.*", "", targetVis)
edgeVisData <- data.frame(from=sourceVis, to=targetVis, stringsAsFactors=FALSE)
for (i in 1:nrow(edgeVisData))
{
edgeVisData[i, ] = sort(edgeVisData[i, ])
}
edgeVisData = edgeVisData[!duplicated(edgeVisData),]
visObj<- visNetwork(nodeVisData, edgeVisData,height="800px",width="900px")
visObj<-visExport(visObj,type ="png", name="network",float="right")
if(phy){
}
else{
visObj<-visIgraphLayout(visObj,layout=visLay)
}
if(package==TRUE)
{
visNetwork(nodeVisData, edgeVisData,height="800px",width="900px")
}
else{
visObj<-visInteraction(visObj,navigationButtons = TRUE)
visObj<-visOptions(visObj,manipulation = TRUE)
}
#plotInput(network,network$nodes,network$edges)
#rcytoscapejs2(network$nodes, network$edges,width=1500,height=1800, layout="spread", showPanzoom=TRUE)
#}
###END FILE GENERATE UPLOAD NETWORK###
#}
} #end of bionet algorithm
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