inst/app/outputs.R
In C3BI-pasteur-fr/UTechSCB-SCHNAPPs: Single Cell Shiny Application for Analysing Single Cell Transcriptomics Data
# inst/app.outputs.R
#
if (DEBUG) cat(file = stderr(), "outputs.R started.\n")
suppressMessages(require(shinyTree))
suppressMessages(require(stringr))
# require(rintrojs)
# SUMMARY STATS ----------------------------------------------------------------
base::source(paste0(packagePath, .Platform$file.sep, "moduleServer.R"), local = TRUE)
DEBUGSAVE <- get(".SCHNAPPs_DEBUGSAVE", envir = .schnappsEnv)
# normalizationRadioButtonValue --------------------------------
# Parameters / normalization
output$normalizationRadioButtonValue <- renderPrint({
input$normalizationRadioButton
})
library(profvis)
callModule(profvis_server, "profiler")
normaliztionParameters <- list(raw = "no Parameters needed")
# localContributionDir <- .SCHNAPPs_locContributionDir
parFiles <-
dir(
path = c(paste0(packagePath, .Platform$file.sep, "contributions"), localContributionDir),
pattern = "parameters.R",
full.names = TRUE,
recursive = TRUE
)
for (fp in parFiles) {
myNormalizationParameters <- list()
source(fp, local = TRUE)
if (.schnappsEnv$DEBUGSAVE) {
save(file = normalizePath("~/SCHNAPPsDebug/normalizationsParameters.RData"),
list = c("normaliztionParameters", ls())
)
}
# load(file = '~/SCHNAPPsDebug/normalizationsParameters.RData')
if (length(myNormalizationParameters) > 0) {
for (li in 1:length(myNormalizationParameters)) {
lVal <- myNormalizationParameters[[li]]
if (length(lVal) > 0) {
# if (DEBUG) {
# cat(
# file = stderr(),
# paste(
# "normalization Choice: ",
# names(myNormalizationParameters)[li],
# " ",
# lVal,
# "\n"
# )
# )
# cat(file = stderr(), paste(
# "class: ",
# class(myNormalizationParameters[[li]]),
# " ",
# lVal,
# "\n"
# ))
# }
oldNames <- names(normaliztionParameters)
normaliztionParameters[[length(normaliztionParameters) + 1]] <-
lVal
names(normaliztionParameters) <-
c(oldNames, names(myNormalizationParameters)[li])
}
}
}
}
observe(label ="obs_pcaRank", x = {
.schnappsEnv$defaultValues[["pcaRank"]] = input$pcaRank
})
observe(label ="obs_normalizationRadioButton", x = {
.schnappsEnv$defaultValues[["normalizationRadioButton"]] = input$normalizationRadioButton
})
observe(label ="obs_cellSelectionComment", x = {
.schnappsEnv$defaultValues[["cellSelectionComment"]] = input$cellSelectionComment
})
observe(label ="obs_cellsFiltersOut", x = {
.schnappsEnv$defaultValues[["cellsFiltersOut"]] = input$cellsFiltersOut
})
observe(label ="obs_cellKeepOnly", x = {
.schnappsEnv$defaultValues[["cellKeepOnly"]] = input$cellKeepOnly
})
observe(label ="obs_cellKeep", x = {
.schnappsEnv$defaultValues[["cellKeep"]] = input$cellKeep
})
observe(label ="obs_cellPatternRM", x = {
.schnappsEnv$defaultValues[["cellPatternRM"]] = input$cellPatternRM
})
observe(label ="obs_maxGenes", x = {
.schnappsEnv$defaultValues[["maxGenes"]] = input$maxGenes
})
observe(label ="obs_minGenes", x = {
.schnappsEnv$defaultValues[["minGenes"]] = input$minGenes
})
observe(label ="obs_minNonExpGenes", x = {
.schnappsEnv$defaultValues[["minNonExpGenes"]] = input$minNonExpGenes
})
observe(label ="obs_minExpGenes", x = {
.schnappsEnv$defaultValues[["minExpGenes"]] = input$minExpGenes
})
observe(label ="obs_genesKeep", x = {
.schnappsEnv$defaultValues[["genesKeep"]] = input$genesKeep
})
observe(label ="obs_minGenesGS", x = {
.schnappsEnv$defaultValues[["minGenesGS"]] = input$minGenesGS
})
observe(label ="obs_selectIds", x = {
.schnappsEnv$defaultValues[["selectIds"]] = input$selectIds
})
observe(label ="obs_whichscLog", x = {
.schnappsEnv$defaultValues[["whichscLog"]] = input$whichscLog
})
observe(label ="obs_subsampleNum", x = {
.schnappsEnv$defaultValues[["subsampleNum"]] = input$subsampleNum
})
observe(label ="obs_sampleInput", x = {
.schnappsEnv$defaultValues[["sampleInput"]] = input$sampleInput
})
observe(label ="obs_simlr_maxClust", x = {
.schnappsEnv$defaultValues[["simlr_maxClust"]] = input$simlr_maxClust
})
observe(label ="obs_simlr_nClust", x = {
.schnappsEnv$defaultValues[["simlr_nClust"]] = input$simlr_nClust
})
observe(label ="obs_snnType", x = {
.schnappsEnv$defaultValues[["snnType"]] = input$snnType
})
observe(label ="obs_snnClusterSource", x = {
.schnappsEnv$defaultValues[["snnClusterSource"]] = input$snnClusterSource
})
observe(label ="obs_geneSelectionClustering", x = {
.schnappsEnv$defaultValues[["geneSelectionClustering"]] = input$geneSelectionClustering
})
observe(label ="obs_useRanks", x = {
.schnappsEnv$defaultValues[["useRanks"]] = input$useRanks
})
observe(label ="obs_minClusterSize", x = {
.schnappsEnv$defaultValues[["minClusterSize"]] = input$minClusterSize
})
observe(label ="obs_clusterMethod", x = {
.schnappsEnv$defaultValues[["clusterMethod"]] = input$clusterMethod
})
observe(label ="obs_clusterSource", x = {
.schnappsEnv$defaultValues[["clusterSource"]] = input$clusterSource
})
observe(label ="obs_seurClustresolution", x = {
.schnappsEnv$defaultValues[["seurClustresolution"]] = input$seurClustresolution
})
observe(label ="obs_seurClustk.param", x = {
.schnappsEnv$defaultValues[["seurClustk.param"]] = input$seurClustk.param
})
observe(label ="obs_seurClustDims", x = {
.schnappsEnv$defaultValues[["seurClustDims"]] = input$seurClustDims
})
observe(label ="obs_tabsetCluster", x = {
.schnappsEnv$defaultValues[["tabsetCluster"]] = input$tabsetCluster
})
observe(label ="obs_genesRMPCA", x = {
.schnappsEnv$defaultValues[["genesRMPCA"]] = input$genesRMPCA
})
observe(label ="obs_genes4PCA", x = {
.schnappsEnv$defaultValues[["genes4PCA"]] = input$genes4PCA
})
observe(label ="obs_useSeuratPCA", x = {
.schnappsEnv$defaultValues[["useSeuratPCA"]] = input$useSeuratPCA
})
observe(label ="obs_hvgSelection", x = {
.schnappsEnv$defaultValues[["hvgSelection"]] = input$hvgSelection
})
observe(label ="obs_pcaScale", x = {
.schnappsEnv$defaultValues[["pcaScale"]] = input$pcaScale
})
observe(label ="obs_pcaN", x = {
.schnappsEnv$defaultValues[["pcaN"]] = input$pcaN
})
# # check gene names ----
# observe({
# scEx = scEx()
# req(scEx)
# if(any(stringr::str_detect( rownames(scEx), "_"))){
# showNotification(
# "gene names contain '_', which will be replaced by Seurat by '.', which can cause artefacts",
# type = "error",
# duration = NULL
# )
# }
# })
output$noLogWarning <- renderText({
logCalc <- input$whichscLog
if(logCalc != "calcLog") return("Warning normalization not being calculated due to input page selection of Compute normalizations?")
return("")
})
# dimPlotPCA ----
# <- reactive({
output$dimPlotPCA <- renderPlot({
if (DEBUG) {
cat(file = stderr(), "dimPlotPCA started.\n")
}
start.time <- base::Sys.time()
on.exit({
printTimeEnd(start.time, "dimPlotPCA")
if (!is.null(getDefaultReactiveDomain())) {
removeNotification(id = "dimPlotPCA")
}
})
if (!is.null(getDefaultReactiveDomain())) {
showNotification("dimPlotPCA", id = "dimPlotPCA", duration = NULL)
}
input$updateDimPlot
scEx_log <- isolate(scEx_log())
scEx <- isolate(scEx())
pca <- isolate(pcaReact())
if (is.null(scEx_log)) {
if (DEBUG) {
cat(file = stderr(), "dimPlotPCA:NULL\n")
}
return(0)
}
if (.schnappsEnv$DEBUGSAVE) {
save(file = normalizePath("~/SCHNAPPsDebug/dimPlotPCA.RData"), list = c(ls()))
}
# cp =load(file='~/SCHNAPPsDebug/dimPlotPCA.RData')
# return NuLL because it is not working correctly
# return(NULL)
scEx = scEx[rownames(pca$rotation),]
scEx_log = scEx_log[rownames(pca$rotation),]
cellMeta = colData(scEx_log)
rData = rowData(scEx)
meta.data = cellMeta[,"sampleNames", drop = FALSE]
dat = assays(scEx)[[1]][rownames(scEx_log),]
rownames(dat) = rData[rownames(scEx_log),"symbol"]
rownames(pca$rotation) = rData[rownames(pca$rotation),"symbol"]
seurDat <- CreateSeuratObject(
counts = dat,
meta.data = meta.data
)
# TODO use scEx_log
logDat = assays(scEx_log)[[1]]
rData = rowData(scEx_log)
rownames(logDat) = rData$symbol
seurDat@assays$RNA$counts = as(logDat,"CsparseMatrix")
# seurDat <- NormalizeData(seurDat, normalization.method = "LogNormalize", scale.factor = 10000)
# seurDat <- FindVariableFeatures(seurDat, selection.method = "vst", nfeatures = 2000)
# recalculating because createDimReducObject is not working
all.genes <- rownames(seurDat)
# seurDat <- ScaleData(seurDat, features = all.genes)
# seurDat <- RunPCA(seurDat, features = VariableFeatures(object = seurDat))
colnames(pca$x) = str_replace(colnames(pca$x), "PC", "PC_")
ndim = min(15,ncol(pca$x))
# pca.res = irlba(A=t(x=seurDat@assays$RNA@data), nv=50)
# not working
seurDat[["pca"]] = CreateDimReducObject(embeddings = pca$x[colnames(seurDat),],
loadings = pca$rotation,
stdev = pca$var_pcs,
key = "PC_",
assay = "RNA")
# seurDat <- ProjectDim(object = seurDat, reduction = "pca", assay = "RNA")
# DimPlot(seurDat, reduction = "pca")
# seurDat <- ProjectDim(seurDat, reduction = "pca", assay = 'RNA')
d = DimHeatmap(seurDat, dims = 1:ndim, slot = 'counts',
balanced = TRUE, fast = TRUE, projected = FALSE,
reduction = "pca")
d
})
# normalizationsParametersDynamic -------------------------
output$normalizationsParametersDynamic <- renderUI({
if (is.null(input$normalizationRadioButton)) {
return(NULL)
}
selectedChoice <- input$normalizationRadioButton
if (.schnappsEnv$DEBUGSAVE) {
save(file = normalizePath("~/SCHNAPPsDebug/normalizationsParametersDynamic.RData"),
list = c("normaliztionParameters", ls())
)
}
# load(file = '~/SCHNAPPsDebug/normalizationsParametersDynamic.RData')
do.call("switch",
args = c(
selectedChoice,
normaliztionParameters,
h3("no parameters provided")
)
)
})
cellSelectionValues <- reactiveVal(
list(
minExpGenes = defaultValue("minExpGenes", defaultValueRegExGene),
minGenes = defaultValue("minGenes", 20),
maxGenes = defaultValue("maxGenes", 1000000),
cellPatternRM = defaultValue("cellPatternRM", ""),
cellKeep = defaultValue("cellKeep", ""),
cellKeepOnly = defaultValue("cellKeepOnly", ""),
cellsFiltersOut = defaultValue("cellsFiltersOut", ""),
minNonExpGenes = defaultValue("minNonExpGenes", "")
)
)
geneSelectionValues <- reactiveVal(
{
list(
selectIds = defaultValue("selectIds", "^MT-|^RP|^MRP"),
geneListSelection = defaultValue("geneListSelection", NULL),
minGenesGS = defaultValue("minGenesGS", 2),
genesKeep = defaultValue("genesKeep", "")
)
}
)
observeEvent(
label = "ob20",
eventExpr = input$updateCellSelectionParameters,
handlerExpr = {
deepDebug()
if (DEBUG) cat(file = stderr(), "observe updateCellSelectionParameters\n")
cellSelectionValues(list(
minExpGenes = input$minExpGenes,
minGenes = input$minGenes,
maxGenes = input$maxGenes,
cellPatternRM = input$cellPatternRM,
cellKeep = input$cellKeep,
cellKeepOnly = input$cellKeepOnly,
cellsFiltersOut = input$cellsFiltersOut,
minNonExpGenes = input$minNonExpGenes
))
if (DEBUG) cat(file = stderr(), "\nCellSelectionValues\n")
updateButtonColor(buttonName = "updateCellSelectionParameters", parameters = c(
"minExpGenes", "minGenes", "minNonExpGenes",
"maxGenes", "cellPatternRM", "cellKeep", "cellKeepOnly", "cellsFiltersOut"
))
}
)
observe(label = "ob_cellSelection",
{
deepDebug()
if (DEBUG) cat(file = stderr(), "observe ob_cellSelection\n")
setRedGreenButtonCurrent(
vars = list(
c("minExpGenes", input$minExpGenes),
c("minGenes", input$minGenes),
c("maxGenes", input$maxGenes),
c("cellPatternRM", input$cellPatternRM),
c("cellKeep", input$cellKeep),
c("cellKeepOnly", input$cellKeepOnly),
c("cellsFiltersOut", input$cellsFiltersOut),
c("minNonExpGenes", input$minNonExpGenes)
)
)
updateButtonColor(buttonName = "updateCellSelectionParameters", parameters = c(
"minExpGenes", "minGenes", "minNonExpGenes",
"maxGenes", "cellPatternRM", "cellKeep", "cellKeepOnly", "cellsFiltersOut"
))
})
# observe: clustering Button ----
ob_clusteringParams <- observe(label = "ob_clusteringParams", {
deepDebug()
if (DEBUG) cat(file = stderr(), "observe ob_clusteringParams\n")
# this happens when the lite version is used
if (is.null(input$tabsetCluster)){
ob_clusteringParams$destroy()
return(NULL)
}
input$updateClusteringParameters
whichClustering = isolate(input$tabsetCluster)
req(whichClustering)
if ( whichClustering == "scran_Cluster"){
setRedGreenButtonCurrent(
vars = list(
c("seed", input$seed),
c("useRanks", input$useRanks),
c("clusterSource", clusterMethodReact$clusterSource),
c("geneSelectionClustering", input$geneSelectionClustering),
c("minClusterSize", input$minClusterSize),
c("clusterMethod", clusterMethodReact$clusterMethod)
)
)
updateButtonColor(buttonName = "updateClusteringParameters", parameters = c(
"seed", "useRanks", "minClusterSize", "clusterMethod",
"clusterSource", "geneSelectionClustering"
))
}
})
observeEvent(
label = "ob21",
eventExpr = input$updateGeneSelectionParameters,
handlerExpr = {
deepDebug()
geneSelectionValues(list(
selectIds = input$selectIds,
geneListSelection = input$geneListSelection,
minGenesGS = input$minGenesGS,
genesKeep = input$genesKeep
))
if (DEBUG) cat(file = stderr(), "\ngeneSelectionValues\n")
updateButtonColor(buttonName = "updateGeneSelectionParameters", parameters = c(
"selectIds", "geneListSelection",
"minGenesGS", "genesKeep"
))
}
)
observe(label = "ob_geneSelection",
{
deepDebug()
if (DEBUG) cat(file = stderr(), "observe ob_geneSelection\n")
setRedGreenButtonCurrent(
vars = list(
c("selectIds", input$selectIds),
c("geneListSelection", input$geneListSelection),
c("minGenesGS", input$minGenesGS),
c("genesKeep", input$genesKeep)
)
)
updateButtonColor(buttonName = "updateGeneSelectionParameters", parameters = c(
"selectIds", "geneListSelection",
"minGenesGS", "genesKeep"
))
})
# summaryStatsSideBar -----------------------------
output$summaryStatsSideBar <- renderUI({
if (DEBUG) {
cat(file = stderr(), "output$summaryStatsSideBar\n")
}
scEx <- scEx()
scEx_log <- scEx_log()
if (is.null(scEx)) {
if (DEBUG) {
cat(file = stderr(), "output$summaryStatsSideBar:NULL\n")
}
return(NULL)
}
# if (input$noStats) {
# if (DEBUG) {
# cat(file = stderr(), "output$summaryStatsSideBar:off\n")
# }
# return(NULL)
# }
annFile <- inputFile$annFile
medianUMI <- medianUMI()
medianENSG <- medianENSG()
memoryUsed <- getMemoryUsed()
infile <- inputFile$inFile
normalizationRadioButton <- input$normalizationRadioButton
if (.schnappsEnv$DEBUGSAVE) {
save(file = normalizePath("~/SCHNAPPsDebug/summaryStatsSideBar.RData"),
list = c("normaliztionParameters", ls())
)
}
# cp = load("~/SCHNAPPsDebug/summaryStatsSideBar.RData")
line0 <- paste(infile, " _ ", annFile)
line0a <- paste("Number of samples: ", length(levels(scEx$sampleNames)), sep = "\t")
line1 <- paste("No. of cells: ", dim(scEx)[2], sep = "\t")
line2 <- paste("No. of genes: ", dim(scEx)[1], sep = "\t")
line1a <- paste("No. of cells (log): ", dim(scEx_log)[2], sep = "\t")
line2a <- paste("No. of genes (log): ", dim(scEx_log)[1], sep = "\t")
line3 <- paste("Median UMIs per cell: ", medianUMI, sep = "\t")
line4 <-
paste("Median Genes with min 1 UMI: ", medianENSG, sep = "\t")
line5 <-
paste("Total number of reads: ", sum(assays(scEx)[["counts"]]))
line6 <- paste("Memory used:", memoryUsed)
line7 <-
paste("Normalization selected:", normalizationRadioButton)
htmlOut <- paste0(
"<br/>",
"<br/>",
"<br/>",
"Summary statistics of this dataset:",
"<br/>",
"<br/>",
line0,
"<br/>",
line0a,
"<br/>",
line1,
"<br/>",
line2,
"<br/>",
line1a,
"<br/>",
line2a,
"<br/>",
line3,
"<br/>",
line4,
"<br/>",
line5,
"<br/>",
# line6,
# "<br/>",
line7,
"<br/>",
"<br/>"
)
exportTestValues(summaryStatsSideBar = {
htmlOut
})
HTML(htmlOut)
})
if ("shinyBS" %in% rownames(installed.packages())) {
addPopover(
session = session, id = "summaryStatsSideBar", title = "Data summary",
content = "<ul><li>medium UMI: shows how many genes are expressed in log2 space of normalized data</li> </ul> ",
trigger = "click", options = list(container = "body")
)
}
# Select Genes ----
# this is part of the basic functionality from this
# tools and thus, can stay in this file.
output$geneListSelection <- shinyTree::renderTree({
geneLists
})
# selectedGenesTable ----
# ONOFF TAB RENDER TABLE ALL CELLS
# TODO module for DT this is part
# of the basic functionality from this tools and thus, can stay in this file.
# output$selectedGenesTable <- DT::renderDataTable({
# if (DEBUG) {
# cat(file = stderr(), "output$selectedGenesTable\n")
# }
# dataTables <- inputData()
# useGenes <- useGenes()
# useCells <- useCells()
# minGenes <- input$minGenesGS
#
# if (is.null(dataTables) | is.null(useGenes) | is.null(useCells)) {
# return(NULL)
# }
# if (.schnappsEnv$DEBUGSAVE) {
# save(file = "~/SCHNAPPsDebug/selectedGenesTable.RData",
# list = c("normaliztionParameters", ls())
# )
# }
# # load("~/SCHNAPPsDebug/selectedGenesTable.RData")
#
# scEx <- assays(dataTables$scEx)[[1]]
# fd <- rowData(dataTables$scEx)
# dt = fd[useGenes,]
# dt$rowSums <- Matrix::rowSums(scEx[useGenes, useCells])
# dt$rowSamples <- Matrix::rowSums(scEx[useGenes, useCells] > 0)
# # get the order of the frist two columns correct
# firstCol = which(colnames(dt) == "symbol")
# firstCol = c(firstCol, which(colnames(dt) == "Description"))
# # those we created so we know they are there
# firstCol = firstCol = c(firstCol,which (colnames(dt) %in% c("rowSums", "rowSamples")))
# colOrder = c(firstCol, (1:ncol(dt))[-firstCol])
# dt <- dt[, colOrder]
# dt <- dt[dt$rowSums >= minGenes, ]
# exportTestValues(selectedGenesTable = {
# as.data.frame(dt)
# })
# DT::datatable(as.data.frame(dt),
# options = list(scrollX = TRUE))
# })
# removedGenesTable --------------------------
# TODO module for DT TODO move to were it belongs
# output$removedGenesTable <- DT::renderDataTable({
# if (DEBUG) {
# cat(file = stderr(), "output$removedGenesTable\n")
# }
# dataTables <- inputData()
# useGenes <- useGenes()
# useCells <- useCells()
# minGenes <- input$minGenesGS
#
# if (is.null(dataTables) | is.null(useGenes) | is.null(useCells)) {
# return(NULL)
# }
# useGenes <- !useGenes
#
# if (.schnappsEnv$DEBUGSAVE) {
# save(file = "~/SCHNAPPsDebug/removedGenesTable.RData",
# list = c("normaliztionParameters", ls())
# )
# }
# # load("~/SCHNAPPsDebug/removedGenesTable.RData")
# scEx <- assays(dataTables$scEx)[[1]]
# fd <- rowData(dataTables$scEx)
# dt <- fd[useGenes, c("symbol", "Description")]
# dt$rowSums <- Matrix::rowSums(scEx[useGenes, useCells])
# dt$rowSamples <- Matrix::rowSums(scEx[useGenes, useCells] > 0)
#
# dt <- dt[dt$rowSums < minGenes, ]
# exportTestValues(removedGenesTable = {
# as.data.frame(dt)
# })
# DT::datatable(as.data.frame(dt))
# })
# gsSelectedGenes ---------------------------
# TODO module of DT with selected names above Print names of selected genes for gene
# selection above table
# gsSelectedGenesMod ----
callModule(
tableSelectionServer,
"gsSelectedGenesMod",
gsSelectedGenesTable, caption = "Tables with used genes"
)
callModule(
tableSelectionServer,
"gsRMGenesMod",
gsRMGenesTable, caption = "Tables with removed genes"
)
callModule(
tableSelectionServer,
"PCAloadingsMod",
PCAloadingsTable, caption = "Tables with PCA loadings"
)
callModule(
tableSelectionServer,
"HVAinfoMod",
HVAinfoTable, caption = "Tables with variable feature info"
)
# DEBUGSAVEstring ----
output$DEBUGSAVEstring <- renderText({
if (DEBUG) {
.schnappsEnv$DEBUGSAVE <- input$DEBUGSAVE
DEBUGSAVE <- input$DEBUGSAVE
} else {
NULL
}
})
# output$currentTabInfo <- renderText({
# # deepDebug()
# str(input$sideBarID)
# })
# output$save2Historystring <- renderText({
# if (DEBUG) {
# .schnappsEnv$saveHistorycheckbox <- input$save2History
# saveHistorycheckbox <- input$save2History
# } else {
# NULL
# }
# })
# cellSelectionMod ----
callModule(tableSelectionServer,
"cellSelectionMod",
inputSample, caption = "Table with input cells")
# normalizationResult ----
callModule(
tableSelectionServer,
"normalizationResult",
scExLogMatrixDisplay, caption = "Tables with normalization results"
)
# descriptionOfWork ----
output$descriptOfWorkOutput <- renderPrint({
input$descriptionOfWork
})
# # sampleColorSelection ----
# output$sampleColorSelection <- renderUI({
# scEx <- scEx()
# sampCol <- projectionColors$sampleNames
# prFct = projFactors()
# projections = projections()
#
# if (is.null(scEx)) {
# return(NULL)
# }
# if (.schnappsEnv$DEBUGSAVE) {
# save(file = "~/SCHNAPPsDebug/sampleColorSelection.RData",
# list = c("normaliztionParameters", ls())
# )
# }
# # cp = load("~/SCHNAPPsDebug/sampleColorSelection.RData")
#
# lev <- levels(colData(scEx)$sampleNames)
# # cols <- gg_fill_hue(length(lev))
#
# # New IDs "colX1" so that it partly coincide with input$select...
# lapply(seq_along(lev), function(i) {
# colourpicker::colourInput(
# inputId = paste0("sampleNamecol", lev[i]),
# label = paste0("Choose colour for sample ", "\"", lev[i], "\""),
# # value = "#762A83"
# # ,
# value = sampCol[i],
# allowedCols = allowedColors,
# palette = "limited"
# )
# })
# })
#
#
# sampleColorSelection ----
output$ColorSelection <- renderUI({
scEx <- scEx()
# sampCol <- projectionColors$sampleNames
# prFct = projFactors()
projections = projections()
# clusterCol <- projectionColors$dbCluster
if (is.null(scEx)) {
return(NULL)
}
if (.schnappsEnv$DEBUGSAVE) {
save(file = normalizePath("~/SCHNAPPsDebug/sampleColorSelection.RData"),
list = c("normaliztionParameters", ls())
)
}
# cp = load("~/SCHNAPPsDebug/sampleColorSelection.RData")
lev <- levels(colData(scEx)$sampleNames)
# cols <- gg_fill_hue(length(lev))
lev1 <- levels(projections$dbCluster)
lev2 <- levels(colData(scEx)$sampleNames)
# deepDebug()
# function for selecting colors for a factorial
tmpFun <- function(name = "Sample", value = "SampleColorPanel", lev = lev2, idStr = "sampleNamecol", sampCol, allowedColors){
tabPanel(
name, value = value,
fluidRow(
column(
width = 6,
lapply(seq_along(lev), function(i) {
colourpicker::colourInput(
inputId = paste0(idStr, lev[i]),
label = paste0("Choose color for ",name, "\"", lev[i], "\""),
# value = "#762A83"
# ,
value = sampCol[i],
allowedCols = allowedColors,
palette = "limited"
)
})
)))
}
tmpFunCont <- function(name = "Sample", value = "SampleColorPanel", sampCol, allowedColors){
tabPanel(
name, value = value,
fluidRow(
column(
width = 6,
lapply(c("min","max"), function(i) {
cnames = c("min","max")
colourpicker::colourInput(
inputId = paste0(name, ".col.",i),
label = paste0("Choose color for ",i),
# value = "#762A83"
# ,
value = sampCol[which(cnames == i)],
allowedCols = allowedColors,
palette = "limited"
)
})
)))
}
# browser()
# where and how to store the colors
tabs= lapply(names(projections), FUN = function(name){
if(is.factor(projections[,name])){
if(length(levels(projections[,name]))>100) {
showNotification(
paste(name," has more than 100 levels\n"),
type = "error",
duration = 10
)
return(NULL)
}
return(tmpFun(name = name, value = paste0(name, "ColorPanel"), lev = levels(projections[,name]), idStr = paste0(name, ".col."),
sampCol = defaultValue(paste0(name, ".colVec"), allowedColors[seq(levels(projections[,name]))]),
allowedColors = allowedColors)
)
} else {
return(tmpFunCont(name = name, value = paste0(name, "ColorPanel"),
sampCol = defaultValue(paste0(name, ".colVec"), c("#FAF4F5", "#2D96FA")),
allowedColors = allowedColors)
)
}
})
# tabs = list(
# tmpFun(name = "Sample", value = "SampleColorPanel", lev = lev2, idStr = "sampleNamecol", sampCol, allowedColors),
# tmpFun(name = "Cluster", value = "ClusterColorPanel", lev = lev1, idStr = "clusterNamecol", clusterCol, allowedColors)
# )
do.call(tabsetPanel, tabs)
})
# ensure this is executed even if not visible
outputOptions(output, "ColorSelection", suspendWhenHidden = FALSE)
# ids = dbCluster.col.0, sampleNames.col.1, sampleNames.col.test2
# # clusterColorSelection ----
# output$clusterColorSelection <- renderUI({
# scEx <- scEx()
# projections <- projections()
# clusterCol <- projectionColors$dbCluster
#
# if (is.null(scEx) || is.null(projections)) {
# return(NULL)
# }
# if (.schnappsEnv$DEBUGSAVE) {
# save(file = "~/SCHNAPPsDebug/clusterColorSelection.RData",
# list = c("normaliztionParameters", ls())
# )
# }
# # load("~/SCHNAPPsDebug/clusterColorSelection.RData")
#
# lev <- levels(projections$dbCluster)
# # cols <- gg_fill_hue(length(lev))
#
# # New IDs "colX1" so that it partly coincide with input$select...
# lapply(seq_along(lev), function(i) {
# colourpicker::colourInput(
# inputId = paste0("clusterNamecol", lev[i]),
# label = paste0("Choose colour for cluster ", "\"", lev[i], "\""),
# # value = "#762A83"
# # ,
# value = clusterCol[i],
# allowedCols = allowedColors,
# palette = "limited"
# )
# })
# })
# history store to file ----
#'
# askComment <- function(failed = FALSE) {
# modalDialog(
# sc_textInput("HistComment", "add a comment", value = paste("created at ",date())),
# footer = tagList(
# modalButton("Cancel"),
# actionButton("HistCommentok", "OK")
# )
# )
# }
# observeEvent(input$HistCommentok, {
# if (DEBUG) {
# cat(file = stderr(), "writing history.\n")
# }
# start.time <- base::Sys.time()
# on.exit({
# printTimeEnd(start.time, "HistCommentok")
# if (!is.null(getDefaultReactiveDomain())) {
# removeNotification(id = "HistCommentok")
# }
# })
# if (!is.null(getDefaultReactiveDomain())) {
# showNotification("writing history", id = "HistCommentok", duration = NULL)
# }
#
# panelLinkHistory = list("coexpressionSelected" = "coE")
# id <- input$sideBarID
# cat(file = stderr(), paste0("observeEvent input$save2History\n"))
# save(file = "~/SCHNAPPsDebug/save2History.RData", list = c(ls()))
# # cp =load(file="~/SCHNAPPsDebug/save2History.RData")
# lsS = ls(envir = .schnappsEnv)
# for (pl in lsS[grep(paste0("^historyPlot-",panelLinkHistory[[id]]), lsS)]) {
# cat(file = stderr(), paste0("writing to history: ",pl ,"\n"))
# sp <- strsplit( pl, "-" )[[1]]
# recHistory(sp[[length(sp)]], .schnappsEnv[[pl]], envir = .schnappsEnv)
#
# }
#
# removeModal()
#
# })
#
# observeEvent(input$save2History, {
# showModal(askComment())
# })
observe({
gmtData = gmtData()
add2history(type = "save", input=isolate( reactiveValuesToList(input)), comment = "gmtData", gmtData = gmtData)
})
# # observe: input$updateColors ----
# observeEvent(
# label = "ob22",
# eventExpr = input$updateColors,
# handlerExpr = {
# deepDebug()
# cat(file = stderr(), paste0("observeEvent input$updateColors\n"))
# scExx <- scEx()
# projections <- projections()
#
# if (is.null(scExx) || is.null(projections)) {
# return(NULL)
# }
# # sample colors
# scols <- projectionColors$sampleNames
#
# inCols <- list()
# lev <- levels(colData(scExx)$sampleNames)
#
# inCols <- lapply(seq_along(lev), function(i) {
# input[[paste0("sampleNamecol", lev[i])]]
# })
# names(inCols) <- lev
# if (.schnappsEnv$DEBUGSAVE) {
# save(file = "~/SCHNAPPsDebug/updateColors.RData", list = c(ls()))
# cat(file = stderr(), paste0("observeEvent save done\n"))
# }
# # load(file="~/SCHNAPPsDebug/updateColors.RData")
#
# # isolate({
# projectionColors$sampleNames <- unlist(inCols)
# add2history(type = "save", input=isolate( reactiveValuesToList(input)), comment = "scol", scol = projectionColors$sampleNames)
# # })
#
# # cluster colors
# ccols <- projectionColors$dbCluster
#
# inCols <- list()
# lev <- levels(projections$dbCluster)
#
# inCols <- lapply(seq_along(lev), function(i) {
# input[[paste0("clusterNamecol", lev[i])]]
# })
# names(inCols) <- lev
# if (.schnappsEnv$DEBUGSAVE) {
# save(file = "~/SCHNAPPsDebug/updateColors2.RData", list = c(ls()))
# cat(file = stderr(), paste0("observeEvent 2 save done\n"))
# }
# # load(file="~/SCHNAPPsDebug/updateColors2.RData")
#
# # isolate({
# projectionColors$dbCluster <- unlist(inCols)
# add2history(type = "save", input=isolate( reactiveValuesToList(input)), comment = "ccol", ccol = projectionColors$dbCluster)
#
# # })
# setRedGreenButton(
# vars = list(
# c("sampleNamecol", projectionColors$sampleNames),
# c("clusterCols", projectionColors$dbCluster)
# ),
# button = "updateColors"
# )
# }
# )
# # while we still have these reactive values specific for sampleNames and dbCluster...
# observeEvent(projectionColors$sampleNames,{
# cat(file = stderr(), "========observe projectionColors\n")
# pc = projectionColors %>% reactiveValuesToList()
# if("sampleNames" %in% names(pc)){
# projectionColors$sampleNames = projectionColors[["sampleNames"]]
# }
# if("dbCluster" %in% names(pc)){
# projectionColors$dbCluster = projectionColors[["dbCluster"]]
# }
# })
obscolorParamsChanger <- reactive({
input$updateColors
projections()
})
# observe: color selection----
# observeEvent(eventExpr = input$updateColors | projections(), label = "ob_colorParams", {
observeEvent(eventExpr = obscolorParamsChanger() , label = "ob_colorParams", {
deepDebug()
if (DEBUG) cat(file = stderr(), "observe color Vars\n")
scEx <- scEx()
projections <- projections()
pc = projectionColors %>% reactiveValuesToList()
if (is.null(scEx) || is.null(projections)) {
return(NULL)
}
# ids = dbCluster.col.0, sampleNames.col.1, sampleNames.col.test2
if (.schnappsEnv$DEBUGSAVE) {
# browser()
inputList = input %>% reactiveValuesToList()
save(file = normalizePath("~/SCHNAPPsDebug/ob_colorParams.RData"), list = c(ls()))
cat(file = stderr(), paste0("observeEvent save done\n"))
}
# cp = load(file="~/SCHNAPPsDebug/ob_colorParams.RData")
# input = inputList
# browser()
lapply(names(projections), FUN = function(name){
if(is.factor(projections[,name])){
if(length(levels(projections[,name]))>100) {
cat(file = stderr(), paste0("\n\n\t", name, " factor", ">100 levels\n\n"))
return(NULL)
}
# browser()
ccols <- lapply(levels(projections[,name]), function(i) {
input[[paste0(name, ".col.", i)]]
})
ccols[ccols==""] = "#000000"
nullCol = lapply(ccols,is.null) %>% unlist()
if(any(nullCol)){
ccols[nullCol] = allowedColors[!allowedColors %in% unlist(ccols)][1:sum(nullCol)]
}
# if not initialized
if(any(is.null(ccols %>% unlist()))){
if(!paste0(name, ".colVec") %in% names(.schnappsEnv$defaultValues))
.schnappsEnv$defaultValues[[paste0(name, ".colVec")]] = allowedColors[seq(levels(projections[,name]))]
if(!length(names(.schnappsEnv$defaultValues[[paste0(name, ".colVec")]])) == length(levels(projections[,name]))){
# browser()
.schnappsEnv$defaultValues[[paste0(name, ".colVec")]] = allowedColors[seq(levels(projections[,name]))]
}
names(.schnappsEnv$defaultValues[[paste0(name, ".colVec")]]) = levels(projections[,name])
projectionColors[[name]] = .schnappsEnv$defaultValues[[paste0(name, ".colVec")]]
} else {
if(!length(ccols) == length(levels(projections[,name]))){
browser()
}
names(ccols) = levels(projections[,name])
projectionColors[[name]] = unlist(ccols)
.schnappsEnv$defaultValues[[paste0(name, ".colVec")]] = unlist(ccols)
}
} else{
# browser()
minMax = c("min","max")
ccols <- lapply(minMax, function(i) {
input[[paste0(name, ".col.", i)]]
})
if(any(is.null(ccols %>% unlist()))){
if(!paste0(name, ".colVec") %in% names(.schnappsEnv$defaultValues))
.schnappsEnv$defaultValues[[paste0(name, ".colVec")]] = c("#D4070F", "#1C1AAF")
# if vector is named then complexheatmap thinks it is a factorial
names(.schnappsEnv$defaultValues[[paste0(name, ".colVec")]] ) = NULL
projectionColors[[name]] = .schnappsEnv$defaultValues[[paste0(name, ".colVec")]]
} else {
names(ccols) = NULL
projectionColors[[name]] = unlist(ccols)
.schnappsEnv$defaultValues[[paste0(name, ".colVec")]] = unlist(ccols)
}
}
})
#
# lev <- levels(projections$dbCluster)
# ccols <- lapply(seq_along(lev), function(i) {
# input[[paste0("clusterNamecol", lev[i])]]
# })
# lev <- levels(colData(scEx)$sampleNames)
# scols <- lapply(seq_along(lev), function(i) {
# input[[paste0("sampleNamecol", lev[i])]]
# })
pc = projectionColors %>% reactiveValuesToList()
setRedGreenButtonCurrent(
vars = list(c("pc", pc %>% unlist()))
)
add2history(type = "save", input=isolate( reactiveValuesToList(input)), comment = "Colors", projectionColors = pc)
updateButtonColor(buttonName = "updateColors", parameters = c(
names(pc)
))
if (DEBUG) cat(file = stderr(), "observe color Vars done\n")
})
# Nclusters ----
output$Nclusters <- renderText({
dbCluster <- dbCluster()
if (is.null(dbCluster)) {
return(NULL)
}
if (.schnappsEnv$DEBUGSAVE) {
save(file = normalizePath("~/SCHNAPPsDebug/Nclusters.RData"), list = c(ls()))
cat(file = stderr(), paste0("observeEvent save done\n"))
}
# load(file="~/SCHNAPPsDebug/Nclusters.RData")
retVal <- paste(levels(dbCluster))
exportTestValues(Nclusters = {
retVal
})
return(retVal)
})
# download handler countscsv ----
output$countscsv <- downloadHandler(
filename = paste0("counts.", Sys.Date(), ".csv"),
content = function(file) {
if (DEBUG) {
cat(file = stderr(), "RDSsave started.\n")
}
start.time <- base::Sys.time()
on.exit({
printTimeEnd(start.time, "RDSsave")
if (!is.null(getDefaultReactiveDomain())) {
removeNotification(id = "RDSsave")
}
})
if (!is.null(getDefaultReactiveDomain())) {
showNotification("RDSsave", id = "RDSsave", duration = NULL)
}
if (!is.null(getDefaultReactiveDomain())) {
removeNotification(id = "RDSsave")
}
scEx_log <- scEx_log()
if (is.null(scEx_log)) {
return(NULL)
}
write.csv(as.matrix(assays(scEx_log)[[1]]), file)
}
)
# download RDS ----
output$RDSsave <- downloadHandler(
filename = paste0("project.", Sys.Date(), ".RData"),
content = function(file) {
if (DEBUG) {
cat(file = stderr(), "RDSsave started.\n")
}
start.time <- base::Sys.time()
on.exit({
printTimeEnd(start.time, "RDSsave")
if (!is.null(getDefaultReactiveDomain())) {
removeNotification(id = "RDSsave")
}
})
if (!is.null(getDefaultReactiveDomain())) {
showNotification("RDSsave", id = "RDSsave", duration = NULL)
}
if (!is.null(getDefaultReactiveDomain())) {
removeNotification(id = "RDSsave")
}
# umaps???
scEx <- scEx()
projections <- projections()
scEx_log <- scEx_log()
pca <- pcaReact()
# TODO should be taken from projections
tsne <- tsne()
pc = projectionColors %>% reactiveValuesToList()
namesDF = groupNames$namesDF
if (is.null(scEx)) {
return(NULL)
}
if (.schnappsEnv$DEBUGSAVE) {
save(file = normalizePath("~/SCHNAPPsDebug/RDSsave.RData"), list = c(ls()))
}
# load(file='~/SCHNAPPsDebug/RDSsave.RData')
deepDebug()
scEx <- consolidateScEx(scEx, projections, scEx_log, pca, tsne)
# we save the pca separately because I don't know how to store the rotation otherwise.
# mostly done to make the lite version work.
saveList = c("scEx" , "pc" , "namesDF")
if(!is.null(pca)){
saveList = c(saveList, "pca")
}
# deepDebug()
# save projections that shouldn't be recalculated in lite version
if (length(.schnappsEnv$projectionFunctions) > 0){
for (idx in 1:length(.schnappsEnv$projectionFunctions) ){
assign(.schnappsEnv$projectionFunctions[[idx]][2],
eval(parse(text = paste0(.schnappsEnv$projectionFunctions[[idx]][2],"()"))))
saveList = c(saveList, .schnappsEnv$projectionFunctions[[idx]][2])
}
}
save(file = file, list = saveList)
# write.csv(as.matrix(exprs(scEx)), file)
}
)
# download Rmd ----
output$RmdSave <- downloadHandler(
filename = "report.zip",
content = function(outZipFile) {
if (DEBUG) {
cat(file = stderr(), "RmdSave started.\n")
}
start.time <- base::Sys.time()
on.exit({
if (!is.null(getDefaultReactiveDomain())) {
removeNotification(id = "RmdSave")
}
})
if (!is.null(getDefaultReactiveDomain())) {
showNotification("RmdSave", id = "RmdSave", duration = NULL)
}
if (!is.null(getDefaultReactiveDomain())) {
removeNotification(id = "RmdSave")
}
if (is.null(.schnappsEnv$historyPath) ) {
return(NULL)
}
# if (is.null(scEx)) {
# return(NULL)
# }
if (.schnappsEnv$DEBUGSAVE) {
save(file = normalizePath("~/SCHNAPPsDebug/RmdSave.RData"), list = c(ls(), ".schnappsEnv"))
}
# cp = load(file='~/SCHNAPPsDebug/RmdSave.RData')
tempReport = .schnappsEnv$historyFile
outReport = paste0(.schnappsEnv$historyPath, .Platform$file.sep,"report.html")
# tempReport = "~/SCHNAPPsDebug/tmpReport.Rmd"
# file.copy("contributions/gQC_generalQC//report.Rmd",
# '/var/folders/tf/jwlc7r3d48z7pkq0w38_v7t40000gp/T//RtmpTx4l4G/file1a6e471a698.Rmd', overwrite = TRUE)
tryCatch(
callr::r(
function(inputFP, output_file, params, envir) {
rmarkdown::render(
input = inputFP,
output_file = output_file,
params = params,
envir = envir
)
},
args = list(
inputFP = tempReport,
output_file = outReport,
# params = params,
envir = new.env()
),
stderr = stderr(),
stdout = stderr()
),
error = function(e) {
cat(file = stderr(), paste("==== An error occurred during the creation of the report\n", e, "\n"))
}
)
# file.copy(from = "contributions/sCA_subClusterAnalysis/report.Rmd",
# to = "/var/folders/_h/vtcnd09n2jdby90zkb6wyd740000gp/T//Rtmph1SRTE/file69aa37a47206.Rmd", overwrite = TRUE)
# rmarkdown::render(input = tempReport, output_file = "report.html",
# params = params, envir = new.env())
# outZipFile <- paste0(tempdir(), .Platform$file.sep, "report.zip")
# tDir <- paste0(.schnappsEnv$reportTempDir, .Platform$file.sep)
# zippedReportFiles <- c(paste0(tDir, zippedReportFiles))
zip(outZipFile, paste0(path.expand(.schnappsEnv$historyPath), .Platform$file.sep), flags = "-9jr")
if (DEBUG) {
end.time <- Sys.time()
cat(
file = stderr(),
"===Report:done",
difftime(end.time, start.time, units = "min"),
"\n"
)
}
return(outZipFile)
}
)
# Report creation ------------------------------------------------------------------
output$report <- downloadHandler(
filename = "report.zip",
content = function(outZipFile) {
outrepFile <- reacativeReport()
file.copy(from = outrepFile, to = outZipFile)
}
)
# dummy function to return NULL
returnNull <- function() {
return(NULL)
}
# commented out because it is corrently not used
# # forceCalc -----# handling expensive calcualtions
# forceCalc <- shiny::observe({
# if (DEBUG) cat(file = stderr(), paste0("observe: goCalc\n"))
# go <- input$goCalc
# start.time <- base::Sys.time()
# if (go) {
# isolate({
# if (DEBUG) {
# base::cat(file = stderr(), "forceCalc\n")
# }
# # list of output variable and function name
#
# withProgress(message = "Performing heavy calculations", value = 0, {
# n <- length(heavyCalculations)
# for (calc in heavyCalculations) {
# shiny::incProgress(1 / n, detail = base::paste("Creating ", calc[1]))
# if (DEBUG) {
# cat(file = stderr(), base::paste("forceCalc ", calc[1], "\n"))
# }
# assign(calc[1], eval(parse(text = base::paste0(
# calc[2], "()"
# ))))
# }
# })
# })
#
# printTimeEnd(start.time, "forceCalc")
# }
# })
scranWarning <- function() {
cat(file = stderr(), paste0("scranWarning\n"))
modalDialog(
span(
"The parameters clusterSource=normData and/or clusterMethod=hclust can ",
"can result in very long wait times (>6hrs). Do you really want to do this?"
),
footer = tagList(
actionButton("scranWarning_cancel", "Cancel"),
actionButton("scranWarning_ok", "OK")
)
)
}
# handle long executions ----
observeEvent(
label = "ob23",
eventExpr = input$clusterMethod,
handlerExpr = {
deepDebug()
if (DEBUG) cat(file = stderr(), paste0("observe: input$clusterMethod\n"))
if (input$clusterMethod == "hclust") {
showModal(scranWarning())
} else {
clusterMethodReact$clusterMethod <- "igraph"
}
}
)
observeEvent(
label = "ob24",
eventExpr = input$clusterSource,
handlerExpr = {
deepDebug()
if (DEBUG) cat(file = stderr(), paste0("observe: input$clusterSource\n"))
# if (input$clusterSource == "logcounts") {
# showModal(scranWarning())
# } else {
# clusterMethodReact$clusterSource <- "counts"
# }
clusterMethodReact$clusterSource <- input$clusterSource
}
)
observeEvent(
label = "ob25",
eventExpr = input$scranWarning_cancel,
handlerExpr = {
deepDebug()
updateSelectInput(session, "clusterMethod",
selected = "igraph"
)
# updateSelectInput(session, "clusterSource",
# selected = "counts"
# )
removeModal()
}
)
observeEvent(
label = "ob26",
eventExpr = input$scranWarning_ok,
handlerExpr = {
deepDebug()
if (input$clusterMethod == "hclust") {
clusterMethodReact$clusterMethod <- "hclust"
}
# if (input$clusterSource == "normData") {
# clusterMethodReact$clusterSource <- "normData"
# }
removeModal()
}
)
observe(label = "ob_pca",
{
deepDebug()
if (DEBUG) cat(file = stderr(), "observe ob_pca\n")
# out <- pcaReact()
# if (is.null(out)) {
# .schnappsEnv$calculated_gQC_tsneDim <- "NA"
# }
input$updatePCAParameters
setRedGreenButtonCurrent(
vars = list(
c("pcaRank", input$pcaRank),
c("pcaN", input$pcaN),
c("pcaCenter", input$pcaCenter),
c("pcaScale", input$pcaScale),
c("hvgSelection", input$hvgSelection),
c("genes4PCA", input$genes4PCA)
)
)
updateButtonColor(
buttonName = "updatePCAParameters",
parameters = c(
"pcaRank", "pcaN",
"pcaCenter", "pcaScale", "genes4PCA"
)
)
}
)
ob_clusterParams <- observe(label = "ob_clusterParams", {
if (DEBUG) cat(file = stderr(), "observe ob_clusterParams\n")
input$updateClusteringParameters
tabsetCluster = input$tabsetCluster
# this happens when the lite version is used
if (is.null(tabsetCluster)){
ob_clusterParams$destroy()
return(NULL)
}
if (tabsetCluster == "seurat_Clustering") {
setRedGreenButtonCurrent(
vars = list(
c("tabsetCluster", input$tabsetCluster),
c("seurClustDims", input$seurClustDims),
c("seurClustk.param", input$seurClustk.param),
c("seurClustresolution", input$seurClustresolution)
)
)
updateButtonColor(buttonName = "updateClusteringParameters", parameters = c(
"seurClustDims", "seurClustk.param",
"seurClustresolution", "tabsetCluster"
))
}
if (tabsetCluster == "scran_Cluster") {
setRedGreenButtonCurrent(
vars = list(
c("useRanks", input$useRanks),
c("clusterSource", clusterMethodReact$clusterSource),
c("geneSelectionClustering", input$geneSelectionClustering),
c("minClusterSize", input$minClusterSize),
c("clusterMethod", input$clusterMethod),
c("tabsetCluster", input$tabsetCluster)
)
)
updateButtonColor(buttonName = "updateClusteringParameters", parameters = c(
"useRanks", "clusterSource","geneSelectionClustering",
"minClusterSize", "clusterMethod", "tabsetCluster"
))
}
if (tabsetCluster == "snnGraph") {
setRedGreenButton(
vars = list(
# c("snnClusterSource", isolate(input$snnClusterSource)),
c("snnType", isolate(input$snnType)),
c("tabsetCluster", isolate(input$tabsetCluster))
),
button = "updateClusteringParameters"
)
updateButtonColor(buttonName = "updateClusteringParameters", parameters = c(
"snnType", "tabsetCluster"
))
}
if (tabsetCluster == "simlrFunc") {
setRedGreenButton(
vars = list(
# c("snnClusterSource", isolate(input$snnClusterSource)),
c("snnType", isolate(input$snnType)),
c("tabsetCluster", isolate(input$tabsetCluster)),
c("simlr_nClust", isolate(input$simlr_nClust)),
c("simlr_maxClust", isolate(input$simlr_maxClust))
),
button = "updateClusteringParameters"
)
updateButtonColor(buttonName = "updateClusteringParameters", parameters = c(
"snnType", "simlr_nClust", "simlr_maxClust", "tabsetCluster"
))
}
})
# about modal ----
observeEvent(input$AboutApp,{
deepDebug()
showModal(modalDialog(
title = "About SCHNAPPs",
tags$a(tags$b("When using SCHNAPPs, please cite Journal of Immunological Methods doi: 10.1016/j.jim.2021.113176")),
p("the github repository can be found here: https://github.com/C3BI-pasteur-fr/UTechSCB-SCHNAPPs"),
p("The software is patented under IDDN1 .FR2 .0013 .3600164 .0005 .S6 .P7 .20208 .0009 .3123510"),
p("further documentation including FAQs, and example workflows can be found here: https://c3bi-pasteur-fr.github.io/UTechSCB-SCHNAPPs/"),
p("some youtube presentations can be found here: https://www.youtube.com/playlist?list=PL__mZTR-JcdOpa8Llz2Dfcu_mCk8iBCpC"),
easyClose = TRUE,
footer = NULL
))
})
inputHelpIJS <- tryCatch(read.delim(system.file("extdata", "inputHelpIJS.txt",package = "SCHNAPPs"), sep=";", stringsAsFactors = FALSE),
error = function(e) {
cat(file = stderr(), "There is an installation problem: inputHelpIJS.txt not in extdata of package SCHNAPPs.\n")
stop(e)
})
# inputHelpIJS<- read.delim("inst/extdata/inputHelpIJS.txt", sep=";", stringsAsFactors = FALSE)
observeEvent(input$inputHelp, {
deepDebug()
cat(file = stderr(), paste("inputHelp started\n"))
cat(file = stderr(), apply(inputHelpIJS, 1, FUN = function(x) if(length(x)>0)cat(file = stderr(), paste(x, "\n"))))
introjs(session,
options = list(steps = inputHelpIJS)
)
})
twoDselectedAddOptHelpIJS <- read.delim(system.file("extdata", "twoDselectedAddOptHelpIJS.txt",package = "SCHNAPPs"), sep=";", stringsAsFactors = FALSE)
# twoDselectedAddOptHelpIJS <- read.delim("inst/extdata/twoDselectedAddOptHelpIJS.txt", sep=";", stringsAsFactors = FALSE)
observeEvent(input$twoDselectedAddOpt, {
cat(file = stderr(), paste("twoDselectedAddOpt started\n"))
# cat(file = stderr(), apply(twoDselectedAddOptHelpIJS, 1, FUN = function(x) if(length(x)>0)cat(file = stderr(), paste(x, "\n"))))
introjs(session,
options = list(steps = twoDselectedAddOptHelpIJS,
"showBullets" = "false",
"showProgress" = "true",
"showStepNumbers" = "false",
"nextLabel" = "Next",
"prevLabel" = "Prev",
"skipLabel" = "Skip",
"highlightClass" = 'berndTest')
)
})
# Heatmap for scran clustering ----
# All clusters heatmap ------
callModule(
pHeatMapModule,
"clusterBootstrap",
clusterBootstrapReactive
)
source(paste0(packagePath, .Platform$file.sep, "shortCuts.R"), local = TRUE)
source(paste0(packagePath, .Platform$file.sep, "controlbarObservers.R"), local = TRUE)
if (DEBUG) {
cat(file = stderr(), paste("end: outputs.R\n"))
}
C3BI-pasteur-fr/UTechSCB-SCHNAPPs documentation built on Jan. 12, 2025, 1:16 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
# inst/app.outputs.R
#
if (DEBUG) cat(file = stderr(), "outputs.R started.\n")
suppressMessages(require(shinyTree))
suppressMessages(require(stringr))
# require(rintrojs)
# SUMMARY STATS ----------------------------------------------------------------
base::source(paste0(packagePath, .Platform$file.sep, "moduleServer.R"), local = TRUE)
DEBUGSAVE <- get(".SCHNAPPs_DEBUGSAVE", envir = .schnappsEnv)
# normalizationRadioButtonValue --------------------------------
# Parameters / normalization
output$normalizationRadioButtonValue <- renderPrint({
input$normalizationRadioButton
})
library(profvis)
callModule(profvis_server, "profiler")
normaliztionParameters <- list(raw = "no Parameters needed")
# localContributionDir <- .SCHNAPPs_locContributionDir
parFiles <-
dir(
path = c(paste0(packagePath, .Platform$file.sep, "contributions"), localContributionDir),
pattern = "parameters.R",
full.names = TRUE,
recursive = TRUE
)
for (fp in parFiles) {
myNormalizationParameters <- list()
source(fp, local = TRUE)
if (.schnappsEnv$DEBUGSAVE) {
save(file = normalizePath("~/SCHNAPPsDebug/normalizationsParameters.RData"),
list = c("normaliztionParameters", ls())
)
}
# load(file = '~/SCHNAPPsDebug/normalizationsParameters.RData')
if (length(myNormalizationParameters) > 0) {
for (li in 1:length(myNormalizationParameters)) {
lVal <- myNormalizationParameters[[li]]
if (length(lVal) > 0) {
# if (DEBUG) {
# cat(
# file = stderr(),
# paste(
# "normalization Choice: ",
# names(myNormalizationParameters)[li],
# " ",
# lVal,
# "\n"
# )
# )
# cat(file = stderr(), paste(
# "class: ",
# class(myNormalizationParameters[[li]]),
# " ",
# lVal,
# "\n"
# ))
# }
oldNames <- names(normaliztionParameters)
normaliztionParameters[[length(normaliztionParameters) + 1]] <-
lVal
names(normaliztionParameters) <-
c(oldNames, names(myNormalizationParameters)[li])
}
}
}
}
observe(label ="obs_pcaRank", x = {
.schnappsEnv$defaultValues[["pcaRank"]] = input$pcaRank
})
observe(label ="obs_normalizationRadioButton", x = {
.schnappsEnv$defaultValues[["normalizationRadioButton"]] = input$normalizationRadioButton
})
observe(label ="obs_cellSelectionComment", x = {
.schnappsEnv$defaultValues[["cellSelectionComment"]] = input$cellSelectionComment
})
observe(label ="obs_cellsFiltersOut", x = {
.schnappsEnv$defaultValues[["cellsFiltersOut"]] = input$cellsFiltersOut
})
observe(label ="obs_cellKeepOnly", x = {
.schnappsEnv$defaultValues[["cellKeepOnly"]] = input$cellKeepOnly
})
observe(label ="obs_cellKeep", x = {
.schnappsEnv$defaultValues[["cellKeep"]] = input$cellKeep
})
observe(label ="obs_cellPatternRM", x = {
.schnappsEnv$defaultValues[["cellPatternRM"]] = input$cellPatternRM
})
observe(label ="obs_maxGenes", x = {
.schnappsEnv$defaultValues[["maxGenes"]] = input$maxGenes
})
observe(label ="obs_minGenes", x = {
.schnappsEnv$defaultValues[["minGenes"]] = input$minGenes
})
observe(label ="obs_minNonExpGenes", x = {
.schnappsEnv$defaultValues[["minNonExpGenes"]] = input$minNonExpGenes
})
observe(label ="obs_minExpGenes", x = {
.schnappsEnv$defaultValues[["minExpGenes"]] = input$minExpGenes
})
observe(label ="obs_genesKeep", x = {
.schnappsEnv$defaultValues[["genesKeep"]] = input$genesKeep
})
observe(label ="obs_minGenesGS", x = {
.schnappsEnv$defaultValues[["minGenesGS"]] = input$minGenesGS
})
observe(label ="obs_selectIds", x = {
.schnappsEnv$defaultValues[["selectIds"]] = input$selectIds
})
observe(label ="obs_whichscLog", x = {
.schnappsEnv$defaultValues[["whichscLog"]] = input$whichscLog
})
observe(label ="obs_subsampleNum", x = {
.schnappsEnv$defaultValues[["subsampleNum"]] = input$subsampleNum
})
observe(label ="obs_sampleInput", x = {
.schnappsEnv$defaultValues[["sampleInput"]] = input$sampleInput
})
observe(label ="obs_simlr_maxClust", x = {
.schnappsEnv$defaultValues[["simlr_maxClust"]] = input$simlr_maxClust
})
observe(label ="obs_simlr_nClust", x = {
.schnappsEnv$defaultValues[["simlr_nClust"]] = input$simlr_nClust
})
observe(label ="obs_snnType", x = {
.schnappsEnv$defaultValues[["snnType"]] = input$snnType
})
observe(label ="obs_snnClusterSource", x = {
.schnappsEnv$defaultValues[["snnClusterSource"]] = input$snnClusterSource
})
observe(label ="obs_geneSelectionClustering", x = {
.schnappsEnv$defaultValues[["geneSelectionClustering"]] = input$geneSelectionClustering
})
observe(label ="obs_useRanks", x = {
.schnappsEnv$defaultValues[["useRanks"]] = input$useRanks
})
observe(label ="obs_minClusterSize", x = {
.schnappsEnv$defaultValues[["minClusterSize"]] = input$minClusterSize
})
observe(label ="obs_clusterMethod", x = {
.schnappsEnv$defaultValues[["clusterMethod"]] = input$clusterMethod
})
observe(label ="obs_clusterSource", x = {
.schnappsEnv$defaultValues[["clusterSource"]] = input$clusterSource
})
observe(label ="obs_seurClustresolution", x = {
.schnappsEnv$defaultValues[["seurClustresolution"]] = input$seurClustresolution
})
observe(label ="obs_seurClustk.param", x = {
.schnappsEnv$defaultValues[["seurClustk.param"]] = input$seurClustk.param
})
observe(label ="obs_seurClustDims", x = {
.schnappsEnv$defaultValues[["seurClustDims"]] = input$seurClustDims
})
observe(label ="obs_tabsetCluster", x = {
.schnappsEnv$defaultValues[["tabsetCluster"]] = input$tabsetCluster
})
observe(label ="obs_genesRMPCA", x = {
.schnappsEnv$defaultValues[["genesRMPCA"]] = input$genesRMPCA
})
observe(label ="obs_genes4PCA", x = {
.schnappsEnv$defaultValues[["genes4PCA"]] = input$genes4PCA
})
observe(label ="obs_useSeuratPCA", x = {
.schnappsEnv$defaultValues[["useSeuratPCA"]] = input$useSeuratPCA
})
observe(label ="obs_hvgSelection", x = {
.schnappsEnv$defaultValues[["hvgSelection"]] = input$hvgSelection
})
observe(label ="obs_pcaScale", x = {
.schnappsEnv$defaultValues[["pcaScale"]] = input$pcaScale
})
observe(label ="obs_pcaN", x = {
.schnappsEnv$defaultValues[["pcaN"]] = input$pcaN
})
# # check gene names ----
# observe({
# scEx = scEx()
# req(scEx)
# if(any(stringr::str_detect( rownames(scEx), "_"))){
# showNotification(
# "gene names contain '_', which will be replaced by Seurat by '.', which can cause artefacts",
# type = "error",
# duration = NULL
# )
# }
# })
output$noLogWarning <- renderText({
logCalc <- input$whichscLog
if(logCalc != "calcLog") return("Warning normalization not being calculated due to input page selection of Compute normalizations?")
return("")
})
# dimPlotPCA ----
# <- reactive({
output$dimPlotPCA <- renderPlot({
if (DEBUG) {
cat(file = stderr(), "dimPlotPCA started.\n")
}
start.time <- base::Sys.time()
on.exit({
printTimeEnd(start.time, "dimPlotPCA")
if (!is.null(getDefaultReactiveDomain())) {
removeNotification(id = "dimPlotPCA")
}
})
if (!is.null(getDefaultReactiveDomain())) {
showNotification("dimPlotPCA", id = "dimPlotPCA", duration = NULL)
}
input$updateDimPlot
scEx_log <- isolate(scEx_log())
scEx <- isolate(scEx())
pca <- isolate(pcaReact())
if (is.null(scEx_log)) {
if (DEBUG) {
cat(file = stderr(), "dimPlotPCA:NULL\n")
}
return(0)
}
if (.schnappsEnv$DEBUGSAVE) {
save(file = normalizePath("~/SCHNAPPsDebug/dimPlotPCA.RData"), list = c(ls()))
}
# cp =load(file='~/SCHNAPPsDebug/dimPlotPCA.RData')
# return NuLL because it is not working correctly
# return(NULL)
scEx = scEx[rownames(pca$rotation),]
scEx_log = scEx_log[rownames(pca$rotation),]
cellMeta = colData(scEx_log)
rData = rowData(scEx)
meta.data = cellMeta[,"sampleNames", drop = FALSE]
dat = assays(scEx)[[1]][rownames(scEx_log),]
rownames(dat) = rData[rownames(scEx_log),"symbol"]
rownames(pca$rotation) = rData[rownames(pca$rotation),"symbol"]
seurDat <- CreateSeuratObject(
counts = dat,
meta.data = meta.data
)
# TODO use scEx_log
logDat = assays(scEx_log)[[1]]
rData = rowData(scEx_log)
rownames(logDat) = rData$symbol
seurDat@assays$RNA$counts = as(logDat,"CsparseMatrix")
# seurDat <- NormalizeData(seurDat, normalization.method = "LogNormalize", scale.factor = 10000)
# seurDat <- FindVariableFeatures(seurDat, selection.method = "vst", nfeatures = 2000)
# recalculating because createDimReducObject is not working
all.genes <- rownames(seurDat)
# seurDat <- ScaleData(seurDat, features = all.genes)
# seurDat <- RunPCA(seurDat, features = VariableFeatures(object = seurDat))
colnames(pca$x) = str_replace(colnames(pca$x), "PC", "PC_")
ndim = min(15,ncol(pca$x))
# pca.res = irlba(A=t(x=seurDat@assays$RNA@data), nv=50)
# not working
seurDat[["pca"]] = CreateDimReducObject(embeddings = pca$x[colnames(seurDat),],
loadings = pca$rotation,
stdev = pca$var_pcs,
key = "PC_",
assay = "RNA")
# seurDat <- ProjectDim(object = seurDat, reduction = "pca", assay = "RNA")
# DimPlot(seurDat, reduction = "pca")
# seurDat <- ProjectDim(seurDat, reduction = "pca", assay = 'RNA')
d = DimHeatmap(seurDat, dims = 1:ndim, slot = 'counts',
balanced = TRUE, fast = TRUE, projected = FALSE,
reduction = "pca")
d
})
# normalizationsParametersDynamic -------------------------
output$normalizationsParametersDynamic <- renderUI({
if (is.null(input$normalizationRadioButton)) {
return(NULL)
}
selectedChoice <- input$normalizationRadioButton
if (.schnappsEnv$DEBUGSAVE) {
save(file = normalizePath("~/SCHNAPPsDebug/normalizationsParametersDynamic.RData"),
list = c("normaliztionParameters", ls())
)
}
# load(file = '~/SCHNAPPsDebug/normalizationsParametersDynamic.RData')
do.call("switch",
args = c(
selectedChoice,
normaliztionParameters,
h3("no parameters provided")
)
)
})
cellSelectionValues <- reactiveVal(
list(
minExpGenes = defaultValue("minExpGenes", defaultValueRegExGene),
minGenes = defaultValue("minGenes", 20),
maxGenes = defaultValue("maxGenes", 1000000),
cellPatternRM = defaultValue("cellPatternRM", ""),
cellKeep = defaultValue("cellKeep", ""),
cellKeepOnly = defaultValue("cellKeepOnly", ""),
cellsFiltersOut = defaultValue("cellsFiltersOut", ""),
minNonExpGenes = defaultValue("minNonExpGenes", "")
)
)
geneSelectionValues <- reactiveVal(
{
list(
selectIds = defaultValue("selectIds", "^MT-|^RP|^MRP"),
geneListSelection = defaultValue("geneListSelection", NULL),
minGenesGS = defaultValue("minGenesGS", 2),
genesKeep = defaultValue("genesKeep", "")
)
}
)
observeEvent(
label = "ob20",
eventExpr = input$updateCellSelectionParameters,
handlerExpr = {
deepDebug()
if (DEBUG) cat(file = stderr(), "observe updateCellSelectionParameters\n")
cellSelectionValues(list(
minExpGenes = input$minExpGenes,
minGenes = input$minGenes,
maxGenes = input$maxGenes,
cellPatternRM = input$cellPatternRM,
cellKeep = input$cellKeep,
cellKeepOnly = input$cellKeepOnly,
cellsFiltersOut = input$cellsFiltersOut,
minNonExpGenes = input$minNonExpGenes
))
if (DEBUG) cat(file = stderr(), "\nCellSelectionValues\n")
updateButtonColor(buttonName = "updateCellSelectionParameters", parameters = c(
"minExpGenes", "minGenes", "minNonExpGenes",
"maxGenes", "cellPatternRM", "cellKeep", "cellKeepOnly", "cellsFiltersOut"
))
}
)
observe(label = "ob_cellSelection",
{
deepDebug()
if (DEBUG) cat(file = stderr(), "observe ob_cellSelection\n")
setRedGreenButtonCurrent(
vars = list(
c("minExpGenes", input$minExpGenes),
c("minGenes", input$minGenes),
c("maxGenes", input$maxGenes),
c("cellPatternRM", input$cellPatternRM),
c("cellKeep", input$cellKeep),
c("cellKeepOnly", input$cellKeepOnly),
c("cellsFiltersOut", input$cellsFiltersOut),
c("minNonExpGenes", input$minNonExpGenes)
)
)
updateButtonColor(buttonName = "updateCellSelectionParameters", parameters = c(
"minExpGenes", "minGenes", "minNonExpGenes",
"maxGenes", "cellPatternRM", "cellKeep", "cellKeepOnly", "cellsFiltersOut"
))
})
# observe: clustering Button ----
ob_clusteringParams <- observe(label = "ob_clusteringParams", {
deepDebug()
if (DEBUG) cat(file = stderr(), "observe ob_clusteringParams\n")
# this happens when the lite version is used
if (is.null(input$tabsetCluster)){
ob_clusteringParams$destroy()
return(NULL)
}
input$updateClusteringParameters
whichClustering = isolate(input$tabsetCluster)
req(whichClustering)
if ( whichClustering == "scran_Cluster"){
setRedGreenButtonCurrent(
vars = list(
c("seed", input$seed),
c("useRanks", input$useRanks),
c("clusterSource", clusterMethodReact$clusterSource),
c("geneSelectionClustering", input$geneSelectionClustering),
c("minClusterSize", input$minClusterSize),
c("clusterMethod", clusterMethodReact$clusterMethod)
)
)
updateButtonColor(buttonName = "updateClusteringParameters", parameters = c(
"seed", "useRanks", "minClusterSize", "clusterMethod",
"clusterSource", "geneSelectionClustering"
))
}
})
observeEvent(
label = "ob21",
eventExpr = input$updateGeneSelectionParameters,
handlerExpr = {
deepDebug()
geneSelectionValues(list(
selectIds = input$selectIds,
geneListSelection = input$geneListSelection,
minGenesGS = input$minGenesGS,
genesKeep = input$genesKeep
))
if (DEBUG) cat(file = stderr(), "\ngeneSelectionValues\n")
updateButtonColor(buttonName = "updateGeneSelectionParameters", parameters = c(
"selectIds", "geneListSelection",
"minGenesGS", "genesKeep"
))
}
)
observe(label = "ob_geneSelection",
{
deepDebug()
if (DEBUG) cat(file = stderr(), "observe ob_geneSelection\n")
setRedGreenButtonCurrent(
vars = list(
c("selectIds", input$selectIds),
c("geneListSelection", input$geneListSelection),
c("minGenesGS", input$minGenesGS),
c("genesKeep", input$genesKeep)
)
)
updateButtonColor(buttonName = "updateGeneSelectionParameters", parameters = c(
"selectIds", "geneListSelection",
"minGenesGS", "genesKeep"
))
})
# summaryStatsSideBar -----------------------------
output$summaryStatsSideBar <- renderUI({
if (DEBUG) {
cat(file = stderr(), "output$summaryStatsSideBar\n")
}
scEx <- scEx()
scEx_log <- scEx_log()
if (is.null(scEx)) {
if (DEBUG) {
cat(file = stderr(), "output$summaryStatsSideBar:NULL\n")
}
return(NULL)
}
# if (input$noStats) {
# if (DEBUG) {
# cat(file = stderr(), "output$summaryStatsSideBar:off\n")
# }
# return(NULL)
# }
annFile <- inputFile$annFile
medianUMI <- medianUMI()
medianENSG <- medianENSG()
memoryUsed <- getMemoryUsed()
infile <- inputFile$inFile
normalizationRadioButton <- input$normalizationRadioButton
if (.schnappsEnv$DEBUGSAVE) {
save(file = normalizePath("~/SCHNAPPsDebug/summaryStatsSideBar.RData"),
list = c("normaliztionParameters", ls())
)
}
# cp = load("~/SCHNAPPsDebug/summaryStatsSideBar.RData")
line0 <- paste(infile, " _ ", annFile)
line0a <- paste("Number of samples: ", length(levels(scEx$sampleNames)), sep = "\t")
line1 <- paste("No. of cells: ", dim(scEx)[2], sep = "\t")
line2 <- paste("No. of genes: ", dim(scEx)[1], sep = "\t")
line1a <- paste("No. of cells (log): ", dim(scEx_log)[2], sep = "\t")
line2a <- paste("No. of genes (log): ", dim(scEx_log)[1], sep = "\t")
line3 <- paste("Median UMIs per cell: ", medianUMI, sep = "\t")
line4 <-
paste("Median Genes with min 1 UMI: ", medianENSG, sep = "\t")
line5 <-
paste("Total number of reads: ", sum(assays(scEx)[["counts"]]))
line6 <- paste("Memory used:", memoryUsed)
line7 <-
paste("Normalization selected:", normalizationRadioButton)
htmlOut <- paste0(
"<br/>",
"<br/>",
"<br/>",
"Summary statistics of this dataset:",
"<br/>",
"<br/>",
line0,
"<br/>",
line0a,
"<br/>",
line1,
"<br/>",
line2,
"<br/>",
line1a,
"<br/>",
line2a,
"<br/>",
line3,
"<br/>",
line4,
"<br/>",
line5,
"<br/>",
# line6,
# "<br/>",
line7,
"<br/>",
"<br/>"
)
exportTestValues(summaryStatsSideBar = {
htmlOut
})
HTML(htmlOut)
})
if ("shinyBS" %in% rownames(installed.packages())) {
addPopover(
session = session, id = "summaryStatsSideBar", title = "Data summary",
content = "<ul><li>medium UMI: shows how many genes are expressed in log2 space of normalized data</li> </ul> ",
trigger = "click", options = list(container = "body")
)
}
# Select Genes ----
# this is part of the basic functionality from this
# tools and thus, can stay in this file.
output$geneListSelection <- shinyTree::renderTree({
geneLists
})
# selectedGenesTable ----
# ONOFF TAB RENDER TABLE ALL CELLS
# TODO module for DT this is part
# of the basic functionality from this tools and thus, can stay in this file.
# output$selectedGenesTable <- DT::renderDataTable({
# if (DEBUG) {
# cat(file = stderr(), "output$selectedGenesTable\n")
# }
# dataTables <- inputData()
# useGenes <- useGenes()
# useCells <- useCells()
# minGenes <- input$minGenesGS
#
# if (is.null(dataTables) | is.null(useGenes) | is.null(useCells)) {
# return(NULL)
# }
# if (.schnappsEnv$DEBUGSAVE) {
# save(file = "~/SCHNAPPsDebug/selectedGenesTable.RData",
# list = c("normaliztionParameters", ls())
# )
# }
# # load("~/SCHNAPPsDebug/selectedGenesTable.RData")
#
# scEx <- assays(dataTables$scEx)[[1]]
# fd <- rowData(dataTables$scEx)
# dt = fd[useGenes,]
# dt$rowSums <- Matrix::rowSums(scEx[useGenes, useCells])
# dt$rowSamples <- Matrix::rowSums(scEx[useGenes, useCells] > 0)
# # get the order of the frist two columns correct
# firstCol = which(colnames(dt) == "symbol")
# firstCol = c(firstCol, which(colnames(dt) == "Description"))
# # those we created so we know they are there
# firstCol = firstCol = c(firstCol,which (colnames(dt) %in% c("rowSums", "rowSamples")))
# colOrder = c(firstCol, (1:ncol(dt))[-firstCol])
# dt <- dt[, colOrder]
# dt <- dt[dt$rowSums >= minGenes, ]
# exportTestValues(selectedGenesTable = {
# as.data.frame(dt)
# })
# DT::datatable(as.data.frame(dt),
# options = list(scrollX = TRUE))
# })
# removedGenesTable --------------------------
# TODO module for DT TODO move to were it belongs
# output$removedGenesTable <- DT::renderDataTable({
# if (DEBUG) {
# cat(file = stderr(), "output$removedGenesTable\n")
# }
# dataTables <- inputData()
# useGenes <- useGenes()
# useCells <- useCells()
# minGenes <- input$minGenesGS
#
# if (is.null(dataTables) | is.null(useGenes) | is.null(useCells)) {
# return(NULL)
# }
# useGenes <- !useGenes
#
# if (.schnappsEnv$DEBUGSAVE) {
# save(file = "~/SCHNAPPsDebug/removedGenesTable.RData",
# list = c("normaliztionParameters", ls())
# )
# }
# # load("~/SCHNAPPsDebug/removedGenesTable.RData")
# scEx <- assays(dataTables$scEx)[[1]]
# fd <- rowData(dataTables$scEx)
# dt <- fd[useGenes, c("symbol", "Description")]
# dt$rowSums <- Matrix::rowSums(scEx[useGenes, useCells])
# dt$rowSamples <- Matrix::rowSums(scEx[useGenes, useCells] > 0)
#
# dt <- dt[dt$rowSums < minGenes, ]
# exportTestValues(removedGenesTable = {
# as.data.frame(dt)
# })
# DT::datatable(as.data.frame(dt))
# })
# gsSelectedGenes ---------------------------
# TODO module of DT with selected names above Print names of selected genes for gene
# selection above table
# gsSelectedGenesMod ----
callModule(
tableSelectionServer,
"gsSelectedGenesMod",
gsSelectedGenesTable, caption = "Tables with used genes"
)
callModule(
tableSelectionServer,
"gsRMGenesMod",
gsRMGenesTable, caption = "Tables with removed genes"
)
callModule(
tableSelectionServer,
"PCAloadingsMod",
PCAloadingsTable, caption = "Tables with PCA loadings"
)
callModule(
tableSelectionServer,
"HVAinfoMod",
HVAinfoTable, caption = "Tables with variable feature info"
)
# DEBUGSAVEstring ----
output$DEBUGSAVEstring <- renderText({
if (DEBUG) {
.schnappsEnv$DEBUGSAVE <- input$DEBUGSAVE
DEBUGSAVE <- input$DEBUGSAVE
} else {
NULL
}
})
# output$currentTabInfo <- renderText({
# # deepDebug()
# str(input$sideBarID)
# })
# output$save2Historystring <- renderText({
# if (DEBUG) {
# .schnappsEnv$saveHistorycheckbox <- input$save2History
# saveHistorycheckbox <- input$save2History
# } else {
# NULL
# }
# })
# cellSelectionMod ----
callModule(tableSelectionServer,
"cellSelectionMod",
inputSample, caption = "Table with input cells")
# normalizationResult ----
callModule(
tableSelectionServer,
"normalizationResult",
scExLogMatrixDisplay, caption = "Tables with normalization results"
)
# descriptionOfWork ----
output$descriptOfWorkOutput <- renderPrint({
input$descriptionOfWork
})
# # sampleColorSelection ----
# output$sampleColorSelection <- renderUI({
# scEx <- scEx()
# sampCol <- projectionColors$sampleNames
# prFct = projFactors()
# projections = projections()
#
# if (is.null(scEx)) {
# return(NULL)
# }
# if (.schnappsEnv$DEBUGSAVE) {
# save(file = "~/SCHNAPPsDebug/sampleColorSelection.RData",
# list = c("normaliztionParameters", ls())
# )
# }
# # cp = load("~/SCHNAPPsDebug/sampleColorSelection.RData")
#
# lev <- levels(colData(scEx)$sampleNames)
# # cols <- gg_fill_hue(length(lev))
#
# # New IDs "colX1" so that it partly coincide with input$select...
# lapply(seq_along(lev), function(i) {
# colourpicker::colourInput(
# inputId = paste0("sampleNamecol", lev[i]),
# label = paste0("Choose colour for sample ", "\"", lev[i], "\""),
# # value = "#762A83"
# # ,
# value = sampCol[i],
# allowedCols = allowedColors,
# palette = "limited"
# )
# })
# })
#
#
# sampleColorSelection ----
output$ColorSelection <- renderUI({
scEx <- scEx()
# sampCol <- projectionColors$sampleNames
# prFct = projFactors()
projections = projections()
# clusterCol <- projectionColors$dbCluster
if (is.null(scEx)) {
return(NULL)
}
if (.schnappsEnv$DEBUGSAVE) {
save(file = normalizePath("~/SCHNAPPsDebug/sampleColorSelection.RData"),
list = c("normaliztionParameters", ls())
)
}
# cp = load("~/SCHNAPPsDebug/sampleColorSelection.RData")
lev <- levels(colData(scEx)$sampleNames)
# cols <- gg_fill_hue(length(lev))
lev1 <- levels(projections$dbCluster)
lev2 <- levels(colData(scEx)$sampleNames)
# deepDebug()
# function for selecting colors for a factorial
tmpFun <- function(name = "Sample", value = "SampleColorPanel", lev = lev2, idStr = "sampleNamecol", sampCol, allowedColors){
tabPanel(
name, value = value,
fluidRow(
column(
width = 6,
lapply(seq_along(lev), function(i) {
colourpicker::colourInput(
inputId = paste0(idStr, lev[i]),
label = paste0("Choose color for ",name, "\"", lev[i], "\""),
# value = "#762A83"
# ,
value = sampCol[i],
allowedCols = allowedColors,
palette = "limited"
)
})
)))
}
tmpFunCont <- function(name = "Sample", value = "SampleColorPanel", sampCol, allowedColors){
tabPanel(
name, value = value,
fluidRow(
column(
width = 6,
lapply(c("min","max"), function(i) {
cnames = c("min","max")
colourpicker::colourInput(
inputId = paste0(name, ".col.",i),
label = paste0("Choose color for ",i),
# value = "#762A83"
# ,
value = sampCol[which(cnames == i)],
allowedCols = allowedColors,
palette = "limited"
)
})
)))
}
# browser()
# where and how to store the colors
tabs= lapply(names(projections), FUN = function(name){
if(is.factor(projections[,name])){
if(length(levels(projections[,name]))>100) {
showNotification(
paste(name," has more than 100 levels\n"),
type = "error",
duration = 10
)
return(NULL)
}
return(tmpFun(name = name, value = paste0(name, "ColorPanel"), lev = levels(projections[,name]), idStr = paste0(name, ".col."),
sampCol = defaultValue(paste0(name, ".colVec"), allowedColors[seq(levels(projections[,name]))]),
allowedColors = allowedColors)
)
} else {
return(tmpFunCont(name = name, value = paste0(name, "ColorPanel"),
sampCol = defaultValue(paste0(name, ".colVec"), c("#FAF4F5", "#2D96FA")),
allowedColors = allowedColors)
)
}
})
# tabs = list(
# tmpFun(name = "Sample", value = "SampleColorPanel", lev = lev2, idStr = "sampleNamecol", sampCol, allowedColors),
# tmpFun(name = "Cluster", value = "ClusterColorPanel", lev = lev1, idStr = "clusterNamecol", clusterCol, allowedColors)
# )
do.call(tabsetPanel, tabs)
})
# ensure this is executed even if not visible
outputOptions(output, "ColorSelection", suspendWhenHidden = FALSE)
# ids = dbCluster.col.0, sampleNames.col.1, sampleNames.col.test2
# # clusterColorSelection ----
# output$clusterColorSelection <- renderUI({
# scEx <- scEx()
# projections <- projections()
# clusterCol <- projectionColors$dbCluster
#
# if (is.null(scEx) || is.null(projections)) {
# return(NULL)
# }
# if (.schnappsEnv$DEBUGSAVE) {
# save(file = "~/SCHNAPPsDebug/clusterColorSelection.RData",
# list = c("normaliztionParameters", ls())
# )
# }
# # load("~/SCHNAPPsDebug/clusterColorSelection.RData")
#
# lev <- levels(projections$dbCluster)
# # cols <- gg_fill_hue(length(lev))
#
# # New IDs "colX1" so that it partly coincide with input$select...
# lapply(seq_along(lev), function(i) {
# colourpicker::colourInput(
# inputId = paste0("clusterNamecol", lev[i]),
# label = paste0("Choose colour for cluster ", "\"", lev[i], "\""),
# # value = "#762A83"
# # ,
# value = clusterCol[i],
# allowedCols = allowedColors,
# palette = "limited"
# )
# })
# })
# history store to file ----
#'
# askComment <- function(failed = FALSE) {
# modalDialog(
# sc_textInput("HistComment", "add a comment", value = paste("created at ",date())),
# footer = tagList(
# modalButton("Cancel"),
# actionButton("HistCommentok", "OK")
# )
# )
# }
# observeEvent(input$HistCommentok, {
# if (DEBUG) {
# cat(file = stderr(), "writing history.\n")
# }
# start.time <- base::Sys.time()
# on.exit({
# printTimeEnd(start.time, "HistCommentok")
# if (!is.null(getDefaultReactiveDomain())) {
# removeNotification(id = "HistCommentok")
# }
# })
# if (!is.null(getDefaultReactiveDomain())) {
# showNotification("writing history", id = "HistCommentok", duration = NULL)
# }
#
# panelLinkHistory = list("coexpressionSelected" = "coE")
# id <- input$sideBarID
# cat(file = stderr(), paste0("observeEvent input$save2History\n"))
# save(file = "~/SCHNAPPsDebug/save2History.RData", list = c(ls()))
# # cp =load(file="~/SCHNAPPsDebug/save2History.RData")
# lsS = ls(envir = .schnappsEnv)
# for (pl in lsS[grep(paste0("^historyPlot-",panelLinkHistory[[id]]), lsS)]) {
# cat(file = stderr(), paste0("writing to history: ",pl ,"\n"))
# sp <- strsplit( pl, "-" )[[1]]
# recHistory(sp[[length(sp)]], .schnappsEnv[[pl]], envir = .schnappsEnv)
#
# }
#
# removeModal()
#
# })
#
# observeEvent(input$save2History, {
# showModal(askComment())
# })
observe({
gmtData = gmtData()
add2history(type = "save", input=isolate( reactiveValuesToList(input)), comment = "gmtData", gmtData = gmtData)
})
# # observe: input$updateColors ----
# observeEvent(
# label = "ob22",
# eventExpr = input$updateColors,
# handlerExpr = {
# deepDebug()
# cat(file = stderr(), paste0("observeEvent input$updateColors\n"))
# scExx <- scEx()
# projections <- projections()
#
# if (is.null(scExx) || is.null(projections)) {
# return(NULL)
# }
# # sample colors
# scols <- projectionColors$sampleNames
#
# inCols <- list()
# lev <- levels(colData(scExx)$sampleNames)
#
# inCols <- lapply(seq_along(lev), function(i) {
# input[[paste0("sampleNamecol", lev[i])]]
# })
# names(inCols) <- lev
# if (.schnappsEnv$DEBUGSAVE) {
# save(file = "~/SCHNAPPsDebug/updateColors.RData", list = c(ls()))
# cat(file = stderr(), paste0("observeEvent save done\n"))
# }
# # load(file="~/SCHNAPPsDebug/updateColors.RData")
#
# # isolate({
# projectionColors$sampleNames <- unlist(inCols)
# add2history(type = "save", input=isolate( reactiveValuesToList(input)), comment = "scol", scol = projectionColors$sampleNames)
# # })
#
# # cluster colors
# ccols <- projectionColors$dbCluster
#
# inCols <- list()
# lev <- levels(projections$dbCluster)
#
# inCols <- lapply(seq_along(lev), function(i) {
# input[[paste0("clusterNamecol", lev[i])]]
# })
# names(inCols) <- lev
# if (.schnappsEnv$DEBUGSAVE) {
# save(file = "~/SCHNAPPsDebug/updateColors2.RData", list = c(ls()))
# cat(file = stderr(), paste0("observeEvent 2 save done\n"))
# }
# # load(file="~/SCHNAPPsDebug/updateColors2.RData")
#
# # isolate({
# projectionColors$dbCluster <- unlist(inCols)
# add2history(type = "save", input=isolate( reactiveValuesToList(input)), comment = "ccol", ccol = projectionColors$dbCluster)
#
# # })
# setRedGreenButton(
# vars = list(
# c("sampleNamecol", projectionColors$sampleNames),
# c("clusterCols", projectionColors$dbCluster)
# ),
# button = "updateColors"
# )
# }
# )
# # while we still have these reactive values specific for sampleNames and dbCluster...
# observeEvent(projectionColors$sampleNames,{
# cat(file = stderr(), "========observe projectionColors\n")
# pc = projectionColors %>% reactiveValuesToList()
# if("sampleNames" %in% names(pc)){
# projectionColors$sampleNames = projectionColors[["sampleNames"]]
# }
# if("dbCluster" %in% names(pc)){
# projectionColors$dbCluster = projectionColors[["dbCluster"]]
# }
# })
obscolorParamsChanger <- reactive({
input$updateColors
projections()
})
# observe: color selection----
# observeEvent(eventExpr = input$updateColors | projections(), label = "ob_colorParams", {
observeEvent(eventExpr = obscolorParamsChanger() , label = "ob_colorParams", {
deepDebug()
if (DEBUG) cat(file = stderr(), "observe color Vars\n")
scEx <- scEx()
projections <- projections()
pc = projectionColors %>% reactiveValuesToList()
if (is.null(scEx) || is.null(projections)) {
return(NULL)
}
# ids = dbCluster.col.0, sampleNames.col.1, sampleNames.col.test2
if (.schnappsEnv$DEBUGSAVE) {
# browser()
inputList = input %>% reactiveValuesToList()
save(file = normalizePath("~/SCHNAPPsDebug/ob_colorParams.RData"), list = c(ls()))
cat(file = stderr(), paste0("observeEvent save done\n"))
}
# cp = load(file="~/SCHNAPPsDebug/ob_colorParams.RData")
# input = inputList
# browser()
lapply(names(projections), FUN = function(name){
if(is.factor(projections[,name])){
if(length(levels(projections[,name]))>100) {
cat(file = stderr(), paste0("\n\n\t", name, " factor", ">100 levels\n\n"))
return(NULL)
}
# browser()
ccols <- lapply(levels(projections[,name]), function(i) {
input[[paste0(name, ".col.", i)]]
})
ccols[ccols==""] = "#000000"
nullCol = lapply(ccols,is.null) %>% unlist()
if(any(nullCol)){
ccols[nullCol] = allowedColors[!allowedColors %in% unlist(ccols)][1:sum(nullCol)]
}
# if not initialized
if(any(is.null(ccols %>% unlist()))){
if(!paste0(name, ".colVec") %in% names(.schnappsEnv$defaultValues))
.schnappsEnv$defaultValues[[paste0(name, ".colVec")]] = allowedColors[seq(levels(projections[,name]))]
if(!length(names(.schnappsEnv$defaultValues[[paste0(name, ".colVec")]])) == length(levels(projections[,name]))){
# browser()
.schnappsEnv$defaultValues[[paste0(name, ".colVec")]] = allowedColors[seq(levels(projections[,name]))]
}
names(.schnappsEnv$defaultValues[[paste0(name, ".colVec")]]) = levels(projections[,name])
projectionColors[[name]] = .schnappsEnv$defaultValues[[paste0(name, ".colVec")]]
} else {
if(!length(ccols) == length(levels(projections[,name]))){
browser()
}
names(ccols) = levels(projections[,name])
projectionColors[[name]] = unlist(ccols)
.schnappsEnv$defaultValues[[paste0(name, ".colVec")]] = unlist(ccols)
}
} else{
# browser()
minMax = c("min","max")
ccols <- lapply(minMax, function(i) {
input[[paste0(name, ".col.", i)]]
})
if(any(is.null(ccols %>% unlist()))){
if(!paste0(name, ".colVec") %in% names(.schnappsEnv$defaultValues))
.schnappsEnv$defaultValues[[paste0(name, ".colVec")]] = c("#D4070F", "#1C1AAF")
# if vector is named then complexheatmap thinks it is a factorial
names(.schnappsEnv$defaultValues[[paste0(name, ".colVec")]] ) = NULL
projectionColors[[name]] = .schnappsEnv$defaultValues[[paste0(name, ".colVec")]]
} else {
names(ccols) = NULL
projectionColors[[name]] = unlist(ccols)
.schnappsEnv$defaultValues[[paste0(name, ".colVec")]] = unlist(ccols)
}
}
})
#
# lev <- levels(projections$dbCluster)
# ccols <- lapply(seq_along(lev), function(i) {
# input[[paste0("clusterNamecol", lev[i])]]
# })
# lev <- levels(colData(scEx)$sampleNames)
# scols <- lapply(seq_along(lev), function(i) {
# input[[paste0("sampleNamecol", lev[i])]]
# })
pc = projectionColors %>% reactiveValuesToList()
setRedGreenButtonCurrent(
vars = list(c("pc", pc %>% unlist()))
)
add2history(type = "save", input=isolate( reactiveValuesToList(input)), comment = "Colors", projectionColors = pc)
updateButtonColor(buttonName = "updateColors", parameters = c(
names(pc)
))
if (DEBUG) cat(file = stderr(), "observe color Vars done\n")
})
# Nclusters ----
output$Nclusters <- renderText({
dbCluster <- dbCluster()
if (is.null(dbCluster)) {
return(NULL)
}
if (.schnappsEnv$DEBUGSAVE) {
save(file = normalizePath("~/SCHNAPPsDebug/Nclusters.RData"), list = c(ls()))
cat(file = stderr(), paste0("observeEvent save done\n"))
}
# load(file="~/SCHNAPPsDebug/Nclusters.RData")
retVal <- paste(levels(dbCluster))
exportTestValues(Nclusters = {
retVal
})
return(retVal)
})
# download handler countscsv ----
output$countscsv <- downloadHandler(
filename = paste0("counts.", Sys.Date(), ".csv"),
content = function(file) {
if (DEBUG) {
cat(file = stderr(), "RDSsave started.\n")
}
start.time <- base::Sys.time()
on.exit({
printTimeEnd(start.time, "RDSsave")
if (!is.null(getDefaultReactiveDomain())) {
removeNotification(id = "RDSsave")
}
})
if (!is.null(getDefaultReactiveDomain())) {
showNotification("RDSsave", id = "RDSsave", duration = NULL)
}
if (!is.null(getDefaultReactiveDomain())) {
removeNotification(id = "RDSsave")
}
scEx_log <- scEx_log()
if (is.null(scEx_log)) {
return(NULL)
}
write.csv(as.matrix(assays(scEx_log)[[1]]), file)
}
)
# download RDS ----
output$RDSsave <- downloadHandler(
filename = paste0("project.", Sys.Date(), ".RData"),
content = function(file) {
if (DEBUG) {
cat(file = stderr(), "RDSsave started.\n")
}
start.time <- base::Sys.time()
on.exit({
printTimeEnd(start.time, "RDSsave")
if (!is.null(getDefaultReactiveDomain())) {
removeNotification(id = "RDSsave")
}
})
if (!is.null(getDefaultReactiveDomain())) {
showNotification("RDSsave", id = "RDSsave", duration = NULL)
}
if (!is.null(getDefaultReactiveDomain())) {
removeNotification(id = "RDSsave")
}
# umaps???
scEx <- scEx()
projections <- projections()
scEx_log <- scEx_log()
pca <- pcaReact()
# TODO should be taken from projections
tsne <- tsne()
pc = projectionColors %>% reactiveValuesToList()
namesDF = groupNames$namesDF
if (is.null(scEx)) {
return(NULL)
}
if (.schnappsEnv$DEBUGSAVE) {
save(file = normalizePath("~/SCHNAPPsDebug/RDSsave.RData"), list = c(ls()))
}
# load(file='~/SCHNAPPsDebug/RDSsave.RData')
deepDebug()
scEx <- consolidateScEx(scEx, projections, scEx_log, pca, tsne)
# we save the pca separately because I don't know how to store the rotation otherwise.
# mostly done to make the lite version work.
saveList = c("scEx" , "pc" , "namesDF")
if(!is.null(pca)){
saveList = c(saveList, "pca")
}
# deepDebug()
# save projections that shouldn't be recalculated in lite version
if (length(.schnappsEnv$projectionFunctions) > 0){
for (idx in 1:length(.schnappsEnv$projectionFunctions) ){
assign(.schnappsEnv$projectionFunctions[[idx]][2],
eval(parse(text = paste0(.schnappsEnv$projectionFunctions[[idx]][2],"()"))))
saveList = c(saveList, .schnappsEnv$projectionFunctions[[idx]][2])
}
}
save(file = file, list = saveList)
# write.csv(as.matrix(exprs(scEx)), file)
}
)
# download Rmd ----
output$RmdSave <- downloadHandler(
filename = "report.zip",
content = function(outZipFile) {
if (DEBUG) {
cat(file = stderr(), "RmdSave started.\n")
}
start.time <- base::Sys.time()
on.exit({
if (!is.null(getDefaultReactiveDomain())) {
removeNotification(id = "RmdSave")
}
})
if (!is.null(getDefaultReactiveDomain())) {
showNotification("RmdSave", id = "RmdSave", duration = NULL)
}
if (!is.null(getDefaultReactiveDomain())) {
removeNotification(id = "RmdSave")
}
if (is.null(.schnappsEnv$historyPath) ) {
return(NULL)
}
# if (is.null(scEx)) {
# return(NULL)
# }
if (.schnappsEnv$DEBUGSAVE) {
save(file = normalizePath("~/SCHNAPPsDebug/RmdSave.RData"), list = c(ls(), ".schnappsEnv"))
}
# cp = load(file='~/SCHNAPPsDebug/RmdSave.RData')
tempReport = .schnappsEnv$historyFile
outReport = paste0(.schnappsEnv$historyPath, .Platform$file.sep,"report.html")
# tempReport = "~/SCHNAPPsDebug/tmpReport.Rmd"
# file.copy("contributions/gQC_generalQC//report.Rmd",
# '/var/folders/tf/jwlc7r3d48z7pkq0w38_v7t40000gp/T//RtmpTx4l4G/file1a6e471a698.Rmd', overwrite = TRUE)
tryCatch(
callr::r(
function(inputFP, output_file, params, envir) {
rmarkdown::render(
input = inputFP,
output_file = output_file,
params = params,
envir = envir
)
},
args = list(
inputFP = tempReport,
output_file = outReport,
# params = params,
envir = new.env()
),
stderr = stderr(),
stdout = stderr()
),
error = function(e) {
cat(file = stderr(), paste("==== An error occurred during the creation of the report\n", e, "\n"))
}
)
# file.copy(from = "contributions/sCA_subClusterAnalysis/report.Rmd",
# to = "/var/folders/_h/vtcnd09n2jdby90zkb6wyd740000gp/T//Rtmph1SRTE/file69aa37a47206.Rmd", overwrite = TRUE)
# rmarkdown::render(input = tempReport, output_file = "report.html",
# params = params, envir = new.env())
# outZipFile <- paste0(tempdir(), .Platform$file.sep, "report.zip")
# tDir <- paste0(.schnappsEnv$reportTempDir, .Platform$file.sep)
# zippedReportFiles <- c(paste0(tDir, zippedReportFiles))
zip(outZipFile, paste0(path.expand(.schnappsEnv$historyPath), .Platform$file.sep), flags = "-9jr")
if (DEBUG) {
end.time <- Sys.time()
cat(
file = stderr(),
"===Report:done",
difftime(end.time, start.time, units = "min"),
"\n"
)
}
return(outZipFile)
}
)
# Report creation ------------------------------------------------------------------
output$report <- downloadHandler(
filename = "report.zip",
content = function(outZipFile) {
outrepFile <- reacativeReport()
file.copy(from = outrepFile, to = outZipFile)
}
)
# dummy function to return NULL
returnNull <- function() {
return(NULL)
}
# commented out because it is corrently not used
# # forceCalc -----# handling expensive calcualtions
# forceCalc <- shiny::observe({
# if (DEBUG) cat(file = stderr(), paste0("observe: goCalc\n"))
# go <- input$goCalc
# start.time <- base::Sys.time()
# if (go) {
# isolate({
# if (DEBUG) {
# base::cat(file = stderr(), "forceCalc\n")
# }
# # list of output variable and function name
#
# withProgress(message = "Performing heavy calculations", value = 0, {
# n <- length(heavyCalculations)
# for (calc in heavyCalculations) {
# shiny::incProgress(1 / n, detail = base::paste("Creating ", calc[1]))
# if (DEBUG) {
# cat(file = stderr(), base::paste("forceCalc ", calc[1], "\n"))
# }
# assign(calc[1], eval(parse(text = base::paste0(
# calc[2], "()"
# ))))
# }
# })
# })
#
# printTimeEnd(start.time, "forceCalc")
# }
# })
scranWarning <- function() {
cat(file = stderr(), paste0("scranWarning\n"))
modalDialog(
span(
"The parameters clusterSource=normData and/or clusterMethod=hclust can ",
"can result in very long wait times (>6hrs). Do you really want to do this?"
),
footer = tagList(
actionButton("scranWarning_cancel", "Cancel"),
actionButton("scranWarning_ok", "OK")
)
)
}
# handle long executions ----
observeEvent(
label = "ob23",
eventExpr = input$clusterMethod,
handlerExpr = {
deepDebug()
if (DEBUG) cat(file = stderr(), paste0("observe: input$clusterMethod\n"))
if (input$clusterMethod == "hclust") {
showModal(scranWarning())
} else {
clusterMethodReact$clusterMethod <- "igraph"
}
}
)
observeEvent(
label = "ob24",
eventExpr = input$clusterSource,
handlerExpr = {
deepDebug()
if (DEBUG) cat(file = stderr(), paste0("observe: input$clusterSource\n"))
# if (input$clusterSource == "logcounts") {
# showModal(scranWarning())
# } else {
# clusterMethodReact$clusterSource <- "counts"
# }
clusterMethodReact$clusterSource <- input$clusterSource
}
)
observeEvent(
label = "ob25",
eventExpr = input$scranWarning_cancel,
handlerExpr = {
deepDebug()
updateSelectInput(session, "clusterMethod",
selected = "igraph"
)
# updateSelectInput(session, "clusterSource",
# selected = "counts"
# )
removeModal()
}
)
observeEvent(
label = "ob26",
eventExpr = input$scranWarning_ok,
handlerExpr = {
deepDebug()
if (input$clusterMethod == "hclust") {
clusterMethodReact$clusterMethod <- "hclust"
}
# if (input$clusterSource == "normData") {
# clusterMethodReact$clusterSource <- "normData"
# }
removeModal()
}
)
observe(label = "ob_pca",
{
deepDebug()
if (DEBUG) cat(file = stderr(), "observe ob_pca\n")
# out <- pcaReact()
# if (is.null(out)) {
# .schnappsEnv$calculated_gQC_tsneDim <- "NA"
# }
input$updatePCAParameters
setRedGreenButtonCurrent(
vars = list(
c("pcaRank", input$pcaRank),
c("pcaN", input$pcaN),
c("pcaCenter", input$pcaCenter),
c("pcaScale", input$pcaScale),
c("hvgSelection", input$hvgSelection),
c("genes4PCA", input$genes4PCA)
)
)
updateButtonColor(
buttonName = "updatePCAParameters",
parameters = c(
"pcaRank", "pcaN",
"pcaCenter", "pcaScale", "genes4PCA"
)
)
}
)
ob_clusterParams <- observe(label = "ob_clusterParams", {
if (DEBUG) cat(file = stderr(), "observe ob_clusterParams\n")
input$updateClusteringParameters
tabsetCluster = input$tabsetCluster
# this happens when the lite version is used
if (is.null(tabsetCluster)){
ob_clusterParams$destroy()
return(NULL)
}
if (tabsetCluster == "seurat_Clustering") {
setRedGreenButtonCurrent(
vars = list(
c("tabsetCluster", input$tabsetCluster),
c("seurClustDims", input$seurClustDims),
c("seurClustk.param", input$seurClustk.param),
c("seurClustresolution", input$seurClustresolution)
)
)
updateButtonColor(buttonName = "updateClusteringParameters", parameters = c(
"seurClustDims", "seurClustk.param",
"seurClustresolution", "tabsetCluster"
))
}
if (tabsetCluster == "scran_Cluster") {
setRedGreenButtonCurrent(
vars = list(
c("useRanks", input$useRanks),
c("clusterSource", clusterMethodReact$clusterSource),
c("geneSelectionClustering", input$geneSelectionClustering),
c("minClusterSize", input$minClusterSize),
c("clusterMethod", input$clusterMethod),
c("tabsetCluster", input$tabsetCluster)
)
)
updateButtonColor(buttonName = "updateClusteringParameters", parameters = c(
"useRanks", "clusterSource","geneSelectionClustering",
"minClusterSize", "clusterMethod", "tabsetCluster"
))
}
if (tabsetCluster == "snnGraph") {
setRedGreenButton(
vars = list(
# c("snnClusterSource", isolate(input$snnClusterSource)),
c("snnType", isolate(input$snnType)),
c("tabsetCluster", isolate(input$tabsetCluster))
),
button = "updateClusteringParameters"
)
updateButtonColor(buttonName = "updateClusteringParameters", parameters = c(
"snnType", "tabsetCluster"
))
}
if (tabsetCluster == "simlrFunc") {
setRedGreenButton(
vars = list(
# c("snnClusterSource", isolate(input$snnClusterSource)),
c("snnType", isolate(input$snnType)),
c("tabsetCluster", isolate(input$tabsetCluster)),
c("simlr_nClust", isolate(input$simlr_nClust)),
c("simlr_maxClust", isolate(input$simlr_maxClust))
),
button = "updateClusteringParameters"
)
updateButtonColor(buttonName = "updateClusteringParameters", parameters = c(
"snnType", "simlr_nClust", "simlr_maxClust", "tabsetCluster"
))
}
})
# about modal ----
observeEvent(input$AboutApp,{
deepDebug()
showModal(modalDialog(
title = "About SCHNAPPs",
tags$a(tags$b("When using SCHNAPPs, please cite Journal of Immunological Methods doi: 10.1016/j.jim.2021.113176")),
p("the github repository can be found here: https://github.com/C3BI-pasteur-fr/UTechSCB-SCHNAPPs"),
p("The software is patented under IDDN1 .FR2 .0013 .3600164 .0005 .S6 .P7 .20208 .0009 .3123510"),
p("further documentation including FAQs, and example workflows can be found here: https://c3bi-pasteur-fr.github.io/UTechSCB-SCHNAPPs/"),
p("some youtube presentations can be found here: https://www.youtube.com/playlist?list=PL__mZTR-JcdOpa8Llz2Dfcu_mCk8iBCpC"),
easyClose = TRUE,
footer = NULL
))
})
inputHelpIJS <- tryCatch(read.delim(system.file("extdata", "inputHelpIJS.txt",package = "SCHNAPPs"), sep=";", stringsAsFactors = FALSE),
error = function(e) {
cat(file = stderr(), "There is an installation problem: inputHelpIJS.txt not in extdata of package SCHNAPPs.\n")
stop(e)
})
# inputHelpIJS<- read.delim("inst/extdata/inputHelpIJS.txt", sep=";", stringsAsFactors = FALSE)
observeEvent(input$inputHelp, {
deepDebug()
cat(file = stderr(), paste("inputHelp started\n"))
cat(file = stderr(), apply(inputHelpIJS, 1, FUN = function(x) if(length(x)>0)cat(file = stderr(), paste(x, "\n"))))
introjs(session,
options = list(steps = inputHelpIJS)
)
})
twoDselectedAddOptHelpIJS <- read.delim(system.file("extdata", "twoDselectedAddOptHelpIJS.txt",package = "SCHNAPPs"), sep=";", stringsAsFactors = FALSE)
# twoDselectedAddOptHelpIJS <- read.delim("inst/extdata/twoDselectedAddOptHelpIJS.txt", sep=";", stringsAsFactors = FALSE)
observeEvent(input$twoDselectedAddOpt, {
cat(file = stderr(), paste("twoDselectedAddOpt started\n"))
# cat(file = stderr(), apply(twoDselectedAddOptHelpIJS, 1, FUN = function(x) if(length(x)>0)cat(file = stderr(), paste(x, "\n"))))
introjs(session,
options = list(steps = twoDselectedAddOptHelpIJS,
"showBullets" = "false",
"showProgress" = "true",
"showStepNumbers" = "false",
"nextLabel" = "Next",
"prevLabel" = "Prev",
"skipLabel" = "Skip",
"highlightClass" = 'berndTest')
)
})
# Heatmap for scran clustering ----
# All clusters heatmap ------
callModule(
pHeatMapModule,
"clusterBootstrap",
clusterBootstrapReactive
)
source(paste0(packagePath, .Platform$file.sep, "shortCuts.R"), local = TRUE)
source(paste0(packagePath, .Platform$file.sep, "controlbarObservers.R"), local = TRUE)
if (DEBUG) {
cat(file = stderr(), paste("end: outputs.R\n"))
}
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