Nothing
callModule(moduleStaticDataTable,"overview_Aggregation", table2show=reactive({GetDatasetOverview()}),
filename='Aggregation_overview')
callModule(moduleProcess, "moduleProcess_Aggregation",
isDone = reactive({rvModProcess$moduleAggregationDone}),
pages = reactive({rvModProcess$moduleAggregation}),
rstFunc = resetModuleAggregation,
forceReset = reactive({rvModProcess$moduleAggregationForceReset }) )
callModule(modulePopover,"modulePopover_includeShared",
data = reactive(list(title=HTML(paste0("<strong>Include shared peptides</strong>")),
content= HTML(paste0("<ul><li><strong>No:</strong> only protein-specific peptides</li><li><strong>Yes 1:</strong> shared peptides processed as protein specific</li><li><strong>Yes 2</strong>: proportional redistribution of shared peptides</li></ul>")
)
)
)
)
resetModuleAggregation <- reactive({
## update widgets values (reactive values)
resetModuleProcess("Aggregation")
rv$widgets$aggregation$includeSharedPeptides <- "Yes2"
rv$widgets$aggregation$operator <- "Mean"
rv$widgets$aggregation$considerPeptides <- 'allPeptides'
rv$widgets$aggregation$proteinId <- "None"
rv$widgets$aggregation$topN <- 3
rv$widgets$aggregation$filterProtAfterAgregation <- NULL
rv$widgets$aggregation$columnsForProteinDataset.box <- NULL
rv$widgets$aggregation$nbPeptides <- 0
rvModProcess$moduleAggregationDone = rep(FALSE, 3)
##update dataset to put the previous one
rv$current.obj <- rv$dataset[[input$datasets]]
## reset temp object
rv$temp.aggregate <- NULL
})
observeEvent(input$radioBtn_includeShared,ignoreInit = TRUE,{
rv$widgets$aggregation$includeSharedPeptides <- input$radioBtn_includeShared
})
observeEvent(input$AggregationOperator,ignoreInit = TRUE,{
rv$widgets$aggregation$operator <- input$AggregationOperator
})
observeEvent(input$AggregationConsider,ignoreInit = TRUE,{
rv$widgets$aggregation$considerPeptides <- input$AggregationConsider
})
observeEvent(req(input$proteinId),{
rv$proteinId <- input$proteinId
rv$matAdj <- ComputeAdjacencyMatrices()
ComputeConnexComposants()
rv$widgets$aggregation$proteinId <- input$proteinId
})
observeEvent(input$nTopn,{
rv$widgets$aggregation$topN <- input$nTopn
})
observeEvent(input$filterProtAfterAgregation,ignoreInit = TRUE,{
rv$widgets$aggregation$filterProtAfterAgregation <- input$filterProtAfterAgregation
})
observeEvent(input$columnsForProteinDataset.box,{
rv$widgets$aggregation$columnsForProteinDataset.box <- input$columnsForProteinDataset.box
})
observeEvent(input$nbPeptides,ignoreInit = TRUE,{
rv$widgets$aggregation$nbPeptides <- input$nbPeptides
})
output$screenAggregation1 <- renderUI({
tagList(
uiOutput("warningAgregationMethod"),
div(
div( style="display:inline-block; vertical-align: top;",
uiOutput("chooseProteinId")),
div( style="display:inline-block; vertical-align: top;",
modulePopoverUI("modulePopover_includeShared"),
radioButtons("radioBtn_includeShared", NULL, choices=
c("No" = "No",
"Yes (as protein specific)"= "Yes1" ,
"Yes (redistribution)" = "Yes2" ),
selected=rv$widgets$aggregation$includeSharedPeptides)),
div( style="display:inline-block; vertical-align: top; padding-right: 10px;",
radioButtons("AggregationConsider", "Consider",
choices=c('all peptides'="allPeptides",
"N most abundant"="onlyN"),
selected=rv$widgets$aggregation$considerPeptides)),
div( style="display:inline-block; vertical-align: top; padding-right: 10px;",
uiOutput('nTopn_widget')),
div( style="display:inline-block; vertical-align: top;",
uiOutput("operatorChoice")
)
),
actionButton("perform.aggregation","Perform aggregation", class = actionBtnClass),
uiOutput("ObserverAggregationDone"),
hr(),
div(
div( style="display:inline-block; vertical-align: top;",
uiOutput("specificPeptideBarplot")),
div( style="display:inline-block; vertical-align: top; padding-right: 20px;",
uiOutput("allPeptideBarplot")),
div( style="display:inline-block; vertical-align: top;",
DT::dataTableOutput("aggregationStats"))
)
)
})
output$nTopn_widget <- renderUI({
req(rv$widgets$aggregation$considerPeptides)
if (rv$widgets$aggregation$considerPeptides!='onlyN'){return(NULL)}
numericInput("nTopn", "N",value = rv$widgets$aggregation$topN, min = 0, step=1, width='100px')
})
output$operatorChoice <- renderUI({
rv$widgets$aggregation$includeSharedPeptides
choice <- NULL
if (rv$widgets$aggregation$includeSharedPeptides %in% c("No", "Yes1")){
choice <- c("Mean"="Mean","Sum"="Sum")
} else {choice <- c("Mean"="Mean")}
choice
radioButtons("AggregationOperator", "Operator",
choices=choice,
selected=rv$widgets$aggregation$operator)
})
output$screenAggregation2 <- renderUI({
tagList(
uiOutput(outputId = "progressSaveAggregation"),
withProgress(message = '',detail = '', value = 0, {
incProgress(0.5, detail = 'Aggregation in progress')
uiOutput("Aggregation_Step2")
})
)
})
output$screenAggregation3 <- renderUI({
tagList(
h4("Once the saving operation is done, the new current dataset is a protein dataset.
Prostar will automatically switch to the home page with the new dataset."),
actionButton("valid.aggregation","Save aggregation", class = actionBtnClass)
)
})
observeEvent(rv$widgets$aggregation$includeSharedPeptides, {
if (rv$widgets$aggregation$includeSharedPeptides=='Yes2'){
ch <- c("Mean"="Mean")
} else {
ch <- c("Sum"='Sum', "Mean"="Mean")
}
#updateRadioButtons(session,"AggregationOperator", choices=ch, selected=rv$widgets$aggregation$operator)
})
########################################################
RunAggregation <- reactive({
req(rv$matAdj)
rv$widgets$aggregation$includeSharedPeptides
rv$widgets$aggregation$operator
rv$widgets$aggregation$considerPeptides
rv$widgets$aggregation$topN
withProgress(message = '',detail = '', value = 0, {
incProgress(0.2, detail = 'loading foreach package')
require(foreach)
incProgress(0.5, detail = 'Aggregation in progress')
obj.prot <- NULL
if(rv$widgets$aggregation$includeSharedPeptides %in% c("Yes2", "Yes1")){
X <- rv$matAdj$matWithSharedPeptides
if (rv$widgets$aggregation$includeSharedPeptides == 'Yes1'){
if (rv$widgets$aggregation$considerPeptides == 'allPeptides') {
obj.prot <- do.call(paste0('aggregate',rv$widgets$aggregation$operator),list( obj.pep=rv$current.obj,X=X))
} else {
obj.prot <- aggregateTopn(rv$current.obj, X,rv$widgets$aggregation$operator, n=as.numeric(rv$widgets$aggregation$topN))
}
} else {
if (rv$widgets$aggregation$considerPeptides == 'allPeptides') {
obj.prot <- aggregateIterParallel(rv$current.obj, X,init.method='Sum', method='Mean')
} else {
obj.prot <- aggregateIterParallel(rv$current.obj, X, init.method='Sum', method='onlyN', n=rv$widgets$aggregation$topN)
}
}
} else {
X <- rv$matAdj$matWithUniquePeptides
if (rv$widgets$aggregation$considerPeptides == 'allPeptides') {
obj.prot <- do.call(paste0('aggregate',rv$widgets$aggregation$operator),list(obj.pep=rv$current.obj,X=X))
} else {
obj.prot <- aggregateTopn(rv$current.obj, X, rv$widgets$aggregation$operator,n=as.numeric(rv$widgets$aggregation$topN))
}
}
} )
return(obj.prot)
})
##' -- Validate the aggregation ---------------------------------------
##' @author Samuel Wieczorek
observeEvent(input$valid.aggregation,{
req(rv$matAdj)
req(rv$temp.aggregate)
isolate({
withProgress(message = '',detail = '', value = 0, {
X <- NULL
if(rv$widgets$aggregation$includeSharedPeptides %in% c("Yes2", "Yes1")){
X <- rv$matAdj$matWithSharedPeptides}
else { X <- rv$matAdj$matWithUniquePeptides}
total <- 60
delta <- round(total / length(rv$widgets$aggregation$columnsForProteinDataset.box))
cpt <- 10
print(rv$widgets$aggregation$columnsForProteinDataset.box)
for(c in rv$widgets$aggregation$columnsForProteinDataset.box){
newCol <- BuildColumnToProteinDataset(
Biobase::fData(rv$current.obj), X, c, rownames(Biobase::fData(rv$temp.aggregate)))
cnames <- colnames(Biobase::fData(rv$temp.aggregate))
Biobase::fData(rv$temp.aggregate) <-
data.frame(Biobase::fData(rv$temp.aggregate), newCol)
print("possibles colnames dupliques")
print(c)
print(cnames)
colnames(Biobase::fData(rv$temp.aggregate)) <- c(cnames, c)
cpt <- cpt + delta
incProgress(cpt/100, detail = paste0('Processing column ', c))
}
rv$current.obj <- rv$temp.aggregate
rv$current.obj@experimentData@other$Prostar_Version <-
installed.packages(lib.loc = Prostar.loc)["Prostar","Version"]
rv$current.obj@experimentData@other$DAPAR_Version <-
installed.packages(lib.loc = DAPAR.loc)["DAPAR","Version"]
rv$typeOfDataset <- rv$current.obj@experimentData@other$typeOfData
rv$current.obj <- DAPAR::addOriginOfValue(rv$current.obj,NULL)
name <- paste0("Aggregated", ".", rv$typeOfDataset)
rv$current.obj <- saveParameters(rv$current.obj, name,"Aggregation",build_ParamsList_Aggregation())
rv$dataset[[name]] <- rv$current.obj
rvModProcess$moduleAggregationDone[3] <- TRUE
updateSelectInput(session, "datasets", choices = names(rv$dataset), selected = name)
})
})
})
#-----------------------------------------------
output$ObserverAggregationDone <- renderUI({
req(rv$temp.aggregate)
req(input$perform.aggregation)
isolate({
h3("Aggregation done")
})
})
output$aggregationStats <- DT::renderDataTable (server=TRUE,{
req(rv$matAdj)
if (is.null(rv$widgets$aggregation$proteinId) || rv$widgets$aggregation$proteinId == "None") {return(NULL)}
res <- getProteinsStats(rv$matAdj$matWithSharedPeptides)
#print(res)
rv$AggregProtStats$nb <- c(res$nbPeptides,
res$nbSpecificPeptides,
res$nbSharedPeptides,
res$nbProt,
length(res$protOnlyUniquePep),
length(res$protOnlySharedPep),
length(res$protMixPep))
df <- as.data.frame(rv$AggregProtStats)
names(df) <- c('Description', 'Value')
DT::datatable(df,
escape = FALSE,
rownames= FALSE,
extensions = c('Scroller', 'Buttons'),
option=list(initComplete = initComplete(),
buttons = list('copy',
list(
extend = 'csv',
filename = 'aggregation stats'
),'print'),
dom='Brt',
autoWidth=TRUE,
ordering=F,
columnDefs = list(list(width='150px',targets= 0),
list(width='100px',targets= 1))
)
)
})
output$aggregationPlotShared <- renderPlot({
req(rv$matAdj)
GraphPepProt(rv$matAdj$matWithSharedPeptides)
})
output$aggregationPlotUnique <- renderPlot({
req(rv$matAdj)
GraphPepProt(rv$matAdj$matWithUniquePeptides)
})
###------------ Perform aggregation--------------------
observeEvent(input$perform.aggregation,{
#isolate({
rv$temp.aggregate <- RunAggregation()
rvModProcess$moduleAggregationDone[1] <- TRUE
#})
})
output$specificPeptideBarplot <- renderUI({
req(rv$matAdj)
withProgress(message = 'Rendering plot, pleast wait...',detail = '', value = 1, {
tagList(
h4("Only specific peptides"),
plotOutput("aggregationPlotUnique", width="400px")
)
})
})
output$allPeptideBarplot <- renderUI({
req(rv$matAdj)
withProgress(message = 'Rendering plot, pleast wait...',detail = '', value = 1, {
tagList(
h4("All (specific & shared) peptides"),
plotOutput("aggregationPlotShared", width="400px")
)
})
})
output$displayNbPeptides <- renderUI({
req(rv$widgets$aggregation$filterProtAfterAgregation)
if (rv$widgets$aggregation$filterProtAfterAgregation) {
numericInput("nbPeptides", "Nb of peptides defining a protein",
value = 0, min =0, step=1,
width = "250px")
}
})
callModule(modulePopover,"modulePopover_colsForAggreg",
data = reactive(list(title=HTML(paste0("<strong><font size=\"4\">Columns of the meta-data</font></strong>")),
content= "Select the columns of the meta-data (related to proteins) that have to be recorded in the new protein dataset (e.g. the columns which contains the protein ID if you wish to perform a GO analysis.)")))
## -----------------------------------------------
## Second screen of aggregation tool
## -----------------------------------------------
output$Aggregation_Step2 <- renderUI({
req(rv$current.obj)
#if (rv$current.obj@experimentData@other$typeOfData == typePeptide) {
choices <- colnames(Biobase::fData(rv$current.obj))
names(choices) <- colnames(Biobase::fData(rv$current.obj))
tagList(
uiOutput("displayNbPeptides"),
div(
div(
style="display:inline-block; vertical-align: middle; padding-right: 20px;",
modulePopoverUI("modulePopover_colsForAggreg")
),
div(
style="display:inline-block; vertical-align: middle;",
selectInput("columnsForProteinDataset.box",
label = "",
choices = choices,
multiple = TRUE, width='200px',
#size = 10,
selectize = TRUE)
)
)
)
# } else {
# tagList(
# h4("The peptide dataset has been aggregated into a protein dataset."),
# tags$div(style="align: center;",
# moduleStaticDataTableUI("overview_Aggregation")
# )
# )
# }
})
observe({
rv$widgets$aggregation$columnsForProteinDataset.box
if (length(rv$widgets$aggregation$columnsForProteinDataset.box) > 0){
rvModProcess$moduleAggregationDone[2] <- TRUE
} else {
rvModProcess$moduleAggregationDone[2] <- FALSE
}
})
output$warningAgregationMethod <- renderUI({
req(rv$current.obj)
if (length(which(is.na(Biobase::exprs(rv$current.obj)))) > 0)
{
tags$p(tags$b('Warning:')," Your dataset contains missing values.
For better results, you should impute them first")
}
})
#########################################################
output$columnsForProteinDataset <- renderUI({
req(rv$current.obj)
choices <- colnames(Biobase::fData(rv$current.obj))
names(choices) <- colnames(Biobase::fData(rv$current.obj))
selectInput("columnsForProteinDataset.box",
label = "",
choices = choices,
multiple = TRUE, width='200px',
size = 20,
selectize = FALSE)
})
output$chooseProteinId <- renderUI({
if (!is.null(rv$current.obj@experimentData@other$proteinId)) {return(NULL)}
selectInput("proteinId",
"Choose the protein ID",
choices = c("None",colnames(Biobase::fData(rv$current.obj))),
selected = rv$widgets$aggregation$proteinId)
})
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