# Rendering --------------------------------------------------------------------
output$exprKeegMapColors <- renderUI({
data <- plotSelectedData()
if (is.null(data)) {
return(NULL)
}
selectInput("exprKeegMapColors", "Select a color scheme:",
c("Green"="green3", "Blue"="blue","Yellow"="yellow", "Red"="red", "Black"="black"))
})
# output$exprKeegMapColors2 <- renderUI({
# data <- plotSelectedData()
# if (is.null(data)) {
# return(NULL)
# }
# selectInput("exprKeegMapColors2", "Select a color scheme:",
# c("Green"="green3", "Blue"="blue","Yellow"="yellow", "Red"="red", "Gray"="gray"))
# })
output$thrValue <- renderUI({
if(is.null(input$thresholdSelected))
return(NULL)
table<-vertexAnalysisTable()
if(is.null(table))
return(NULL)
switch(input$thresholdSelected, "statistic"= sliderInput("thrValue",h5("Minimum value (threshold) for link construction"),min=min(as.numeric(table[,2])), max=max(as.numeric(table[,2])), value = min(as.numeric(table[,2]))),
"pvalue" = sliderInput("thrValue", h5("Minimum value (threshold) for link construction"),min = 0,max = 1,value = 0.05),
"qvalue" = sliderInput("thrValue", h5("Minimum value (threshold) for link construction"),min = 0,max = 1,value = 0.05))
})
output$thrValue2 <- renderUI({
if(is.null(input$thresholdSelected2))
return(NULL)
table<-vertexAnalysisTable()
if(is.null(table))
return(NULL)
switch(input$thresholdSelected2, "statistic"= sliderInput("thrValue2",h5("Minimum value (threshold) for link construction"),min=min(as.numeric(table[,2])), max=max(as.numeric(table[,2])), value = min(as.numeric(table[,2]))),
"pvalue" = sliderInput("thrValue2", h5("Minimum value (threshold) for link construction"),min = 0,max = 1,value = 0.05),
"qvalue" = sliderInput("thrValue2", h5("Minimum value (threshold) for link construction"),min = 0,max = 1,value = 0.05))
})
# Prepare file with the statistics of the absolute differences between
# correlations for download
output$downloadKeggMap <- downloadHandler(
filename = paste("data", Sys.Date(),input$speciesID, input$pathID, "centrality_bns.tar", sep="_")
,
content = function(file) {
results <- vertexAnalysisTable()
fileCodes<-input$keggCodes
codes<-read.csv(fileCodes$datapath)
if(!dir.exists(file.path("/tmp/", "pathMap"))) dir.create("/tmp/pathMap")
setwd("/tmp/pathMap")
if(input$selectingDataType=="gene"){
l<-which(results[,1] %in% codes[,1])
results[,1]<-codes[l,2]
centralityPathPlot(gene.data=results, cpd.data=NULL, threshold=input$thresholdSelected, thr.value=input$thrValue, species=input$speciesID , pathway.id=input$pathID, kegg.native=input$keggNative, file.name="file",
limit = NULL, bins = list(gene = 15,cpd = 15), both.dirs= list(gene = F,cpd = F),
mid =list(gene = "white", cpd = "white"),high = list(gene = input$exprKeegMapColors,cpd = input$exprKeegMapColors))
}
if(input$selectingDataType=="cpd"){
l<-which(results[,1] %in% codes[,1])
results[,1]<-codes[l,2]
centralityPathPlot(gene.data=NULL, cpd.data=results, threshold=input$thresholdSelected, thr.value=input$thrValue, species=input$speciesID , pathway.id=input$pathID, kegg.native=input$keggNative, file.name="file",
limit = NULL, bins = list(gene = 15,cpd = 15), both.dirs= list(gene = F,cpd = F),
mid =list(gene = "white", cpd = "white"),high = list(gene = input$exprKeegMapColors,cpd = input$exprKeegMapColors))
}
tar(tarfile = file, files ="/tmp/pathMap")
file.remove(list.files())
}
)
output$downloadKeggExprMap <- downloadHandler(
filename = paste("data", Sys.Date(),input$speciesID2, input$pathID2, "expression_bns.tar", sep="_")
,
content = function(file) {
data<-plotSelectedData()
labels <- data$labels
expr<-data$expr
results <- vertexAnalysisTable()
fileCodes<-input$keggCodes2
codes<-read.csv(fileCodes$datapath)
fun<-input$funSelected
if(!dir.exists(file.path("/tmp/", "pathMap"))) dir.create("/tmp/pathMap")
setwd("/tmp/pathMap")
if(input$selectingDataType=="gene"){
l<-match(names(expr),codes[,1])
s<-match(results[,1],codes[,1])
names(expr)<-codes[l,2]
rownames(results)<-results[,1]<-codes[s,2]
pathPlot(gene.data=t(expr), cpd.data=NULL, labels, varr.diff.list=results, threshold=input$thresholdSelected2, thr.value=input$thrValue2, FUN=fun,species=input$speciesID2 , pathway.id=input$pathID2, kegg.native=input$keggNative2, file.name="pathExpr")
}
if(input$selectingDataType=="cpd"){
l<-which(results[,1] %in% codes[,1])
results[,1]<-codes[l,2]
pathPlot(gene.data=NULL, cpd.data=expr, labels, varr.diff.list=results, threshold=input$thresholdSelected2, thr.value=input$thrValue2, FUN=fun,species=input$speciesID2 , pathway.id=input$pathID2, kegg.native=input$keggNative2, file.name="pathExpr")
}
tar(tarfile = file, files ="/tmp/pathMap")
file.remove(list.files())
}
)
output$codeFile <- renderText({
fileCodes<-input$keggCodes
if(is.null(fileCodes)) return (NULL)
codes<-read.csv(fileCodes$datapath)
if(ncol(codes)==2) return(NULL)
if(ncol(codes)!=2) return("The kegg code file has to has to have just two columns. The fisrt one with the variables names and the second one with the respective kegg codes")
})
output$codeFile2 <- renderText({
fileCodes<-input$keggCodes2
if(is.null(fileCodes)) return (NULL)
codes<-read.csv(fileCodes$datapath)
if(ncol(codes)==2) return(NULL)
if(ncol(codes)!=2) return("The kegg code file has to has to have just two columns. The fisrt one with the variables names and the second one with the respective kegg codes")
})
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