library(GSVA)
library(shiny)
library(shinythemes)
library(geneplotter)
library(GSEABase)
library(GSVAdata)
library(limma)
argumentsDataInput <- function(id) {
# Create a namespace function using the provided id
ns <- NS(id)
#UI Definition
column(
3,
conditionalPanel(
condition = "input.arg == 'yes'",
h3("Select arguments:"),
wellPanel(fluidRow(
column(
12,
selectInput("method", "Choose method:",
c("gsva","ssgsea","zscore","plage")),
selectInput("kcdf", "Choose kcdf:",
c("Gaussian","Poisson","none")),
radioButtons("absRanking", "abs.ranking:",
c("False" = FALSE,
"True" = TRUE)),
numericInput("minSz","min.sz:",value = 1),
numericInput("maxSz","max.sz (Write 0 for infinite):",value = 0),
## numericInput("parallelSz","parallel.sz:",value = 0),
## selectInput("parallelType", "parallel.type:",
## c("SOCK","MPI","NWS")),
radioButtons("mxDiff", "mx.diff:",
c("True" = TRUE,
"False" = FALSE)),
conditionalPanel(
condition = "input.method == 'gsva'",
numericInput("tau1","tau:",value = 1)
),
conditionalPanel(
condition = "input.method == 'ssgsea'",
numericInput("tau2","tau:",value = 0.25)
),
conditionalPanel(
condition = "input.method == 'zscore' || input.method == 'plage'"
),
radioButtons("ssgseaNorm", "ssgsea.norm:",
c("True" = TRUE,
"False" = FALSE)),
radioButtons("verbose", "verbose:",
c("True" = TRUE,
"False" = FALSE))
)))
)
)
}
gsva_validation <- function(input, output, session) {
success <- FALSE #Variable to control if the GSVA variables are assigned correctly
if(input$matrixSourceType == "fileMatrix")
{
if (is.null(input$matrixFile))
{
paste("No matrix file selected!")
success <- FALSE
}
else
{
#Matrix file selected
if(input$genesetSourceType == "fileGeneset")
{
if (is.null(input$genesetFile))
{
paste("No geneSet file selected!")
success <- FALSE
}
else
{
#User selects matrix file and geneSet file
inFile <- input$matrixFile
newY <- as.matrix(read.csv(inFile$datapath, header = TRUE, sep = ",")) #Reading file as matrix
rownames(newY) <- newY[,1] #Taking the first column as rownames
newY <- newY[,-1] #Deleting the first column
inGenesetFile <- input$genesetFile
genes <- getGmt(inGenesetFile$datapath)
if(input$maxSz == 0) {
varMaxsz <- Inf
}else {
varMaxsz <- input$maxSz
}
success <- TRUE
}
}
else
{
#User selects matrix file and geneset var
inFile <- input$matrixFile
newY <- as.matrix(read.csv(inFile$datapath, header = TRUE, sep = ",")) #Reading file as matrix
rownames(newY) <- newY[,1] #Taking the first column as rownames
newY <- newY[,-1] #Deleting the first column
assign("genes",get(input$genesetVar))
if(input$maxSz == 0) {
varMaxsz <- Inf
}else {
varMaxsz <- input$maxSz
}
success <- TRUE
}
}
}
else
{
#User selects matrix varand geneset file
if(input$genesetSourceType == "fileGeneset")
{
if (is.null(input$genesetFile))
{
paste("No geneSet file selected!")
success <- FALSE
}
else
{
assign("newY",get(input$matrixVar))
inGenesetFile <- input$genesetFile
genes <- getGmt(inGenesetFile$datapath)
if(input$maxSz == 0) {
varMaxsz <- Inf
}else {
varMaxsz <- input$maxSz
}
success <- TRUE
}
}
else
{
#User selects matrix var selected and geneset var
assign("newY",get(input$matrixVar))
assign("genes",get(input$genesetVar))
if(input$maxSz == 0) {
varMaxsz <- Inf
}else {
varMaxsz <- input$maxSz
}
success <- TRUE
}
}
if(success==TRUE)
{
gsva_generation(input, output, session, newY, genes,varMaxsz)
gsva_information(input,output,session)
}
}
gsva_generation <- function(input, output, session, newY, genes,varMaxsz) {
x <- input$method
selectedTau <- NULL
switch (x,
"gsva" = {
selectedTau <- input$tau1
},
"ssgsea" = {
selectedTau <- input$tau2
},
"zscore" = {
selectedTau <- NULL
},
"plage" = {
selectedTau <- NULL
}
)
#GSVA Generation
withProgress(message = 'Runing GSVA', value = 0, {
incProgress(1, detail = "This may take a while...")
generated_gsva <<- gsva(newY, genes, method=input$method, kcdf=input$kcdf,
abs.ranking=as.logical(input$absRanking),
min.sz=input$minSz, max.sz=varMaxsz,
## parallel.sz=input$parallelSz, parallel.type=input$parallelType,
parallel.sz=1, ## disable parallelism
mx.diff=as.logical(input$mxDiff),
tau=selectedTau,
ssgsea.norm=as.logical(input$ssgseaNorm),
verbose=as.logical(input$verbose))
})
}
gsva_information <- function(input, output, session) {
if(class(generated_gsva) == "matrix")
{
resultInformation <- matrix(data = c(input$matrixVar,input$genesetVar,ncol(generated_gsva),nrow(generated_gsva)), nrow = 1, ncol = 4)
colnames(resultInformation) <- c("Matrix used","GeneSet used", "Col num", "Row num")
output$result <- renderTable(resultInformation)
output$plot <- renderPlot(multidensity(as.list(as.data.frame(generated_gsva)), legend=NA, las=1, xlab=sprintf("%s scores", input$method), main="", lwd=2))
tagList(
downloadButton('downloadData', 'Download'),
actionButton('closeSave','Save & Close')
)
}
else
{
resultInformation <- matrix(data = c(input$matrixVar,input$genesetVar,ncol(generated_gsva),nrow(generated_gsva)), nrow = 1, ncol = 4)
colnames(resultInformation) <- c("Matrix used","GeneSet used", "Col num", "Row num")
output$result <- renderTable(resultInformation)
if(class(generated_gsva) == "ExpressionSet") #If the generated gsva is an ExpressionSet
{
expressionSetObs <- exprs(generated_gsva)
output$plot <- renderPlot(multidensity(as.list(as.data.frame(expressionSetObs)), legend=NA, las=1, xlab=sprintf("%s scores", input$method), main="", lwd=2))
}
else
{
output$plot <- renderPlot(multidensity(as.list(as.data.frame(generated_gsva)), legend=NA, las=1, xlab=sprintf("%s scores", input$method), main="", lwd=2))
}
tagList(
downloadButton('downloadData', 'Download'),
actionButton('closeSave','Save & Close')
)
}
}
download_handler <- function(input, output, session) {
#Controls the Download button
output$downloadData <- downloadHandler(
filename = function() {
paste("gsva_es-", Sys.Date(), ".csv", sep="")
},
content = function(file) {
if(class(generated_gsva) == "matrix") #If the whole object is a matrix
{
dataFrameObs <- as.data.frame(generated_gsva)
write.csv(dataFrameObs, file)
}
else
{
if(class(generated_gsva) == "ExpressionSet") #If the generated gsva result value is an ExpressionSet
{
expressionSetObs <- exprs(generated_gsva)
dataFrameObs <- as.data.frame(expressionSetObs)
write.csv(dataFrameObs, file)
}
else
{
dataFrameObs <- as.data.frame(generated_gsva)
write.csv(dataFrameObs, file)
}
}
}
)
}
function(input, output, session) {
v <- reactiveValues(action = FALSE)
observeEvent(input$button, {
v$action <- input$button
})
output$download <- renderUI({
if(v$action)
{
#Isolates the Run event, that allows the program to run the generation only if the user clicks the button.
isolate({
gsva_validation(input,output,session)
})
}
})
download_handler(input,output,session)
#Observe the Save & Close button
observeEvent(input$closeSave, {
stopApp(generated_gsva) #Stops the app and returns the generated_gsva object
})
}
