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server.R
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server.R
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shinyServer(function(session, input, output) {
options(shiny.maxRequestSize = 30 * 1024^2)
# Global variables
rv <- reactiveValues(data = list(), sequence = list(), activeFile = NULL, results = list(),
tmpData = NULL, tmpSequence = NULL, choices = NULL, drift_plot_select = 1, info = vector("character"))
userConfirmation <- reactiveVal(FALSE)
disable("upload")
rankings_merge <- data.frame(
name = c("high", "medium", "low"),
priority = c(1, 2, 3)
)
massCorrection <- read.csv("./csvfiles/adducts.csv")
# Window/panel selection
observeEvent(list(c(input$sequence, input$example, input$upload)), {
windowselect("sequence")
}, ignoreInit = T
)
observeEvent(input$explore, {
windowselect("datatable")
})
observeEvent(input$export, {
windowselect("export")
})
observeEvent(input$statistics_button, {
windowselect("statistics")
})
### Functions ###
initializeVariables <- function() {
rv$results[[length(rv$results) + 1]] <- list()
}
createDownloadHandler <- function(type, fileExtension, dataFunc) {
function(x) {
output[[paste0("dwn_", type, x)]] <- downloadHandler(
filename = function() {
paste0(names(rv$data[x]), "_", type, fileExtension)
},
content = function(file) {
dataToWrite <- dataFunc(rv, x) # Pass rv and x to the data function
if(fileExtension == ".csv") {
write.csv(dataToWrite, file, row.names = FALSE)
} else if(fileExtension == ".xlsx") {
write_xlsx(dataToWrite, file)
} else if(fileExtension == ".txt") {
writeLines(dataToWrite, file)
}
}
)
}
}
renderDownloadUI <- function(idPrefix, labelSuffix) {
renderUI({
lapply(seq_len(length(rv$choices)), function(x) {
fluidRow(column(12, downloadLink(paste0(idPrefix, x), paste0(rv$choices[x], labelSuffix))))
})
})
}
updateDataAndSequence <- function(notificationMessage, newFileInput, suffix, additionalInfo = NULL) {
if (is.null(rv$tmpData)) {
showNotification(notificationMessage, type = "error")
} else {
if (newFileInput) {
newIndex <- length(rv$data) + 1
rv$data[[newIndex]] <- rv$tmpData
rv$sequence[[newIndex]] <- rv$tmpSequence
newName <- paste0(names(rv$data)[rv$activeFile], suffix)
names(rv$data)[newIndex] <- newName
if (!is.null(additionalInfo)) {
rv$info[newIndex] <- paste(ifelse(is.na(rv$info[rv$activeFile]), "", rv$info[rv$activeFile]), additionalInfo, "\n")
}
initializeVariables()
rv$activeFile <- newIndex
} else {
rv$data[[rv$activeFile]] <- rv$tmpData
rv$sequence[[rv$activeFile]] <- rv$tmpSequence
names(rv$data)[rv$activeFile] <- paste0(names(rv$data)[rv$activeFile], suffix)
if (!is.null(additionalInfo)) {
rv$info[rv$activeFile] <- paste(ifelse(is.na(rv$info[rv$activeFile]), "", rv$info[rv$activeFile]), additionalInfo, "\n")
}
}
rv$choices <- paste(seq_along(rv$data), ": ", names(rv$data))
rv$tmpData <- NULL
rv$tmpSequence <- NULL
}
}
observeEvent(input$inputFile, { # Ensure file is uploaded before pressing Upload button
inputFile <<- read.csv(input$inputFile$datapath, header = 1, stringsAsFactors = F, check.names = FALSE)
enable("upload")
})
observeEvent(input$upload, {
shinyCatch({
#inputFile <- read.csv(input$inputFile$datapath, header = 1, stringsAsFactors = F, check.names = FALSE)
if(input$fileType == "Samples in rows") {
inputFile <- t(inputFile)
}
},
blocking_level = 'message'
)
if(any(duplicated(names(inputFile)))) {
sendSweetAlert(session, title = "Error", text = paste("Duplicate columns found."), type = "error")
} else {
labels <- identifyLabels(inputFile)
initializeVariables()
rv$sequence[[length(rv$sequence) + 1]] <- data.frame(labels, batch = NA,
order = NA, group = NA,
time = NA, paired = NA,
amount = NA)
rv$data[[length(rv$data) + 1]] <- inputFile
names(rv$data)[length(rv$data)] <- substr(input$inputFile$name, 1, nchar(input$inputFile$name) - 4)
rv$choices <- paste(seq_along(rv$data), ": ", names(rv$data))
rv$activeFile <- length(rv$data)
updateTabItems(session, "tabs", selected = "Datainput")
show("buttons")
}
})
observeEvent(input$inputSequence, {
shinyCatch({
inputSequence <- read.csv(input$inputSequence$datapath, header = 1, stringsAsFactors = FALSE)
colnames(inputSequence) <- tolower(colnames(inputSequence))
inputSequence <- checkSequence(inputSequence)
},
blocking_level = 'message'
)
sequence <- rv$sequence[[rv$activeFile]]
labeledSequence <- data.frame("sample" = row.names(sequence), sequence)
inputSequence["sample"] <- lapply(inputSequence["sample"], as.character)
sequence <- left_join(labeledSequence[, 1:2], inputSequence, by = "sample")
row.names(sequence) <- sequence[, 1]
sequence <- sequence[, -1]
rv$sequence[[rv$activeFile]] <- sequence
if(any(grepl("[^[:alnum:]]", sequence$group))) {
showModal(
modalDialog(
title = "Invalid group names", size = "m", easyClose = TRUE,
footer = list(actionButton("group_name_format", "Format names"), modalButton("Dismiss")),
fluidRow(
column(12, p("Invalid group names found. Group names must be alphanumeric and not include spaces."))
)
)
)
}
})
observeEvent(input$group_name_format, {
sequence <- rv$sequence[[rv$activeFile]]
sequence$group <- gsub("[^[:alnum:]]", "", sequence$group)
rv$sequence[[rv$activeFile]] <- sequence
removeModal()
})
observeEvent(input$reuseSequence, {
inputSequence <- read.csv(input$inputSequence$datapath, header = 1, stringsAsFactors = FALSE)
colnames(inputSequence) <- tolower(colnames(inputSequence))
inputSequence <- checkSequence(inputSequence)
sequence <- rv$sequence[[rv$activeFile]]
labeledSequence <- data.frame("sample" = row.names(sequence), sequence)
inputSequence["sample"] <- lapply(inputSequence["sample"], as.character)
sequence <- left_join(labeledSequence[, 1:2], inputSequence, by = "sample")
row.names(sequence) <- sequence[, 1]
sequence <- sequence[, -1]
rv$sequence[[rv$activeFile]] <- sequence
})
observeEvent(input$editColumns, {
showModal(
modalDialog(
title = "Edit columns", size = "s", easyClose = TRUE,
footer = list(actionButton("edit_cols_confirm", "Confirm"), modalButton("Dismiss")),
fluidRow(
column(width = 9, h4("Column name")),
column(width = 3, style = "text-align: left;", h4("Keep"))
),
lapply(seq(ncol(rv$data[[rv$activeFile]])), function(x) {
fluidRow(
column(
width = 9,
textInput(paste0("column_edit_name", x), NULL, value = colnames(rv$data[[rv$activeFile]])[x])
),
column(
width = 3, style = "text-align: center;",
prettyCheckbox(paste0("columns_to_keep", x), NULL, status = "info", value = T)
),
)
})
)
)
})
observeEvent(input$edit_cols_confirm, {
ncol <- ncol(rv$data[[rv$activeFile]])
column_names <- character()
column_names <- sapply(seq(ncol), function(x) {
input[[paste0("column_edit_name", x)]]
})
if(!checkDuplicates(column_names)) {
isolate(colnames(rv$data[[rv$activeFile]]) <- column_names)
isolate(row.names(rv$sequence[[rv$activeFile]]) <- column_names)
keep <- sapply(seq(ncol), function(x) input[[paste0("columns_to_keep", x)]])
rv$data[[rv$activeFile]] <- rv$data[[rv$activeFile]][, keep]
rv$sequence[[rv$activeFile]] <- rv$sequence[[rv$activeFile]][keep, ]
}
removeModal()
})
observeEvent(input$editGroups, {
sequence <- rv$sequence[[rv$activeFile]]
unique_groups <- unique(na.omit(sequence[, 4]))
# Generate UI elements for each group
group_ui_elements <- lapply(seq(unique_groups), function(x) {
group <- unique_groups[x]
fluidRow(
column(3, h5(group)),
column(9,
textInput(paste0("edit_nickname", group), NULL, value = NULL)
),
)
})
showModal(
modalDialog(
title = "Edit Group Nicknames", size = "s", easyClose = TRUE,
footer = list(actionButton("group_edit_confirm", "Confirm"), modalButton("Dismiss")),
fluidRow(
column(3, h4("Group")),
column(9, h4("Nickname"))
),
do.call(tagList, group_ui_elements)
)
)
})
observeEvent(input$group_edit_confirm, {
sequence <- rv$sequence[[rv$activeFile]]
groups <- sequence[, 4]
for (x in seq_along(groups)) {
if (!is.na(groups[x])) {
input_x <- input[[paste0("edit_nickname", groups[x])]]
if (nchar(input_x) != 0 & isValidName(input_x)) {
sequence[x, 4] <- input_x
}
}
}
rv$sequence[[rv$activeFile]] <- sequence
removeModal()
})
observeEvent(input$example, {
# Load example files
# Negative ion mode
data <- read.csv("./example_files/Liverfetus_lipid_neg1.csv", stringsAsFactors = FALSE)
sequence <- read.csv("./example_files/fetus seq neg.csv", stringsAsFactors = FALSE)
row.names(sequence) <- sequence[, 1]
sequence <- sequence[, -1]
rv$sequence[[length(rv$sequence) + 1]] <- sequence
rv$data[[length(rv$data) + 1]] <- data
names(rv$data)[length(rv$data)] <- "Liverfetus_negative"
initializeVariables()
# Positive ion mode
data <- read.csv("./example_files/Liverfetus_lipid_pos1.csv", stringsAsFactors = FALSE)
sequence <- read.csv("./example_files/fetus seq pos.csv", stringsAsFactors = FALSE)
row.names(sequence) <- sequence[, 1]
sequence <- sequence[, -1]
rv$sequence[[length(rv$sequence) + 1]] <- sequence
rv$data[[length(rv$data) + 1]] <- data
names(rv$data)[length(rv$data)] <- "Liverfetus_positive"
initializeVariables()
rv$choices <- paste(seq_along(rv$data), ": ", names(rv$data))
updateTabItems(session, "tabs", selected = "Datainput")
show("buttons")
updateCollapse(session, "menu", close = "Data input")
disable("example")
})
# Update selected data
observeEvent(input$selectDataset, ignoreInit = TRUE, {
rv$activeFile <- which(rv$choices %in% input$selectDataset)
output$seq_table <- renderDT(rv$sequence[[rv$activeFile]], extensions = 'Responsive', server = F,
editable = T, selection = 'none', options = list(pageLength = nrow(rv$sequence[[rv$activeFile]]),
scrollX = TRUE))
output$diboxtitle <- renderText(names(rv$data[rv$activeFile]))
output$dttable <- renderDT(rv$data[[rv$activeFile]], rownames = FALSE, options = list(scrollX = TRUE, scrollY = "700px"))
output$dt_drift_panel <- renderDT(rv$data[[rv$activeFile]][rv$sequence[[rv$activeFile]][, 1] %in% "Name"], rownames = FALSE,
options = list(autoWidth = TRUE, scrollY = "700px", pageLength = 20))
output$dt_boxplot_panel <- renderDT(rv$data[[rv$activeFile]][rv$sequence[[rv$activeFile]][, 1] %in% "Name"], rownames = FALSE,
options = list(autoWidth = TRUE, scrollY = "700px", pageLength = 20))
data <- rv$data[[rv$activeFile]]
sequence <- rv$sequence[[rv$activeFile]]
output$histogram <- renderPlotly({
samples <- data[, sequence[ , 'labels'] %in% "Sample"]
medians <- apply(samples, 2, median, na.rm = TRUE)
median_data <- data.frame(
Sample = names(medians),
Median = medians
)
ggplot(median_data, aes(x = Sample, y = Median)) +
geom_col(fill = "skyblue", color = "black", width = 0.7) +
labs(x = "Samples", y = "Median") +
theme_minimal() +
theme(axis.text.x = element_blank())
})
output$histogram_qc <- renderUI({
QCs <- data[, sequence[ , 'labels'] %in% "QC"]
if(ncol(QCs) > 0) {
medians <- apply(QCs, 2, median, na.rm = TRUE)
median_QC <- data.frame(
QC = names(medians),
Median = medians
)
plotlyOutput("qc_distribution")
output$qc_distribution <- renderPlotly({
ggplot(median_QC, aes(x = QC, y = Median)) +
geom_col(fill = "skyblue", color = "black") +
labs(x = "Sample", y = "Median") +
theme_minimal()
})
}
else {
textOutput("No columns labeled QC.")
}
})
if (sum(rv$sequence[[rv$activeFile]][, 1] %in% "Name") == 1) { #TODO check if this check is needed
internalStandards <- findInternalStandards(rv$data[[rv$activeFile]][rv$sequence[[rv$activeFile]][, 1] %in% "Name"])
updateCheckboxGroupInput(session, "isChoose", choices = internalStandards, selected = internalStandards)
enable("normalizeIS"); enable("removeIS"); enable("saveIS")
if(length(internalStandards) == 0) {
disable("normalizeIS"); disable("removeIS"); disable("saveIS")
}
}
})
# Observer for list of all the datasets
observeEvent(rv$choices, {
choices <- rv$choices
num_datasets <- length(choices)
output$downloadSequence <- downloadHandler(
filename <- function() {
paste0(names(rv$data[rv$activeFile]), "_seq.csv")
},
content = function(file) {
write.csv(cbind("sample" = rownames(rv$sequence[[rv$activeFile]]), rv$sequence[[rv$activeFile]]), file, row.names = FALSE) # TODO
}
)
# Export panel
output$export_ui <- renderDownloadUI("dwn_general", ".csv")
output$export_metabo <- renderDownloadUI("dwn_metabo", "_metabo.csv")
output$export_stats <- renderDownloadUI("dwn_stats", "_results.xlsx")
output$export_settings <- renderDownloadUI("dwn_settings", ".txt")
# lapply(seq_len(num_datasets), createDownloadHandler("general", ".csv", rv$data[[rv$activeFile]]))
# lapply(seq_len(num_datasets), createDownloadHandler("stats", ".xlsx", rv$results[[rv$activeFile]]))
# lapply(seq_len(num_datasets), createDownloadHandler("settings", ".txt", rv$info[[rv$activeFile]]))
# lapply(seq_len(num_datasets), createDownloadHandler("metabo", ".csv", getMetaboData))
lapply(1:length(rv$choices), function(x) {
output[[paste0("dwn_stats", x)]] <- downloadHandler(
filename = function() {
paste0(names(rv$data[x]), "_results.xlsx")
},
content = function(file) {
write_xlsx(rv$results[[x]], file)
}
)
})
lapply(1:length(rv$choices), function(x) {
output[[paste0("dwn_general", x)]] <- downloadHandler(
filename = function() {
paste0(names(rv$data[x]), ".csv")
},
content = function(file) {
write.csv(rv$data[[x]], file, row.names = FALSE)
}
)
})
lapply(1:length(rv$choices), function(x) {
output[[paste0("dwn_settings", x)]] <- downloadHandler(
filename = function() {
paste0(names(rv$data[x]), ".txt")
},
content = function(file) {
write.csv(rv$info[x], file, row.names = FALSE)
}
)
})
lapply(1:length(rv$choices), function(x) {
dat <- rv$data[[x]]
seq <- rv$sequence[[x]]
seq[seq[, 1] %in% "QC", 4] <- "QC"
group <- c("", seq[seq[, 1] %in% c("Sample", "QC"), 4])
outdat <- data.frame(dat[seq[, 1] %in% "Name"], dat[seq[, 1] %in% c("Sample", "QC")])
outdat <- rbind(group, outdat)
output[[paste0("dwn_metabo", x)]] <- downloadHandler(
filename = function() {
paste0(names(rv$data[x]), "_metabo.csv")
},
content = function(file) {
write.csv(outdat, file, row.names = FALSE)
}
)
})
updateCheckboxGroupInput(session, "export_xml_list", choices = choices, selected = NULL)
updateCheckboxGroupInput(session, "filesToRemove", choices = names(rv$data), selected = NULL)
updateSelectInput(session, "drift_select", choices = c("None", choices))
inputs <- c("selectDataset", "mergeFile", "selectpca1", "selectpca2")
selected <- ifelse(is.null(rv$activeFile), length(choices), rv$activeFile)
for(input in inputs) {
updateSelectInput(session, input, choices = choices, selected = choices[selected])
}
})
observeEvent(input$removeFiles, {
if (is.null(input$filesToRemove)) {
showNotification("No files selected.", type = "error")
} else if(length(input$filesToRemove) == length(rv$choices)) {
showNotification("At least one file must be kept.", type = "error")
} else {
keep <- !names(rv$data) %in% input$filesToRemove
rv$data <- rv$data[keep]
rv$sequence <- rv$sequence[keep]
rv$info <- rv$info[keep]
rv$results <- rv$results[keep]
rv$activeFile <- length(rv$data)
rv$choices <- paste(seq_along(rv$data), ": ", names(rv$data))
showNotification("Files removed.", type = "message")
}
})
observeEvent(input$export_xml_list, {
output$export_xml <- downloadHandler(
filename = function() {
paste0(names(rv$data[rv$choices %in% input$export_xml_list])[1], ".xlsx")
},
content = function(file) {
write_xlsx(rv$data[rv$choices %in% input$export_xml_list], file)
}
)
})
observeEvent(input$seq_table_cell_edit, {
sequence <- rv$sequence[[rv$activeFile]]
info <- input$seq_table_cell_edit
str(info)
i <- info$row
j <- info$col
v <- info$value
if(j == 1) {
sendSweetAlert(session, title = "Warning", text = "Column 'labels' cannot be edited", type = "warning")
} else {
sequence[i, j] <- v
rv$sequence[[rv$activeFile]] <- sequence
}
})
observeEvent(input$updateSequence, {
if (!is.null(rv$activeFile) && !is.null(rv$tmpSequence)) {
rv$sequence[[rv$activeFile]] <- rv$tmpSequence
rv$tmpSequence <- NULL
} else {
showNotification("No changes to update", type = "message")
}
})
## Blank filtration ##
observeEvent(input$blankFiltrate, {
if(is.null(rv$activeFile)) {
showNotification("No data", type = "error")
} else if (!"QC" %in% rv$sequence[[rv$activeFile]][, 1]) {
showNotification("Data must have at least 1 QC", type = "error")
} else if (!"Blank" %in% rv$sequence[[rv$activeFile]][, 1]) {
showNotification("Data must have at least 1 Blank", type = "error")
} else if (sum(rv$sequence[[rv$activeFile]][, 1] %in% "Name") != 1) {
showNotification("Data must have exactly 1 \"Name\" column", type = "error")
} else {
sequence <- rv$sequence[[rv$activeFile]]
data <- rv$data[[rv$activeFile]]
filtered <- blankFiltration(data, sequence, input$signalStrength, input$keepIS)
if(input$discardBlank) {
filtered <- filtered[!sequence[, 1] %in% "Blank"]
sequence <- sequence[!sequence[, 1] %in% "Blank", ]
}
rv$tmpData <- filtered
rv$tmpSequence <- sequence
updateSelectInput(session, "selectpca1", selected = "Unsaved data", choices = c("Unsaved data", rv$choices))
output$dttable <- renderDataTable(rv$tmpData, rownames = FALSE, options = list(scrollX = TRUE, scrollY = "700px", pageLength = 20))
sendSweetAlert(session, "Success", paste0(nrow(rv$data[[rv$activeFile]]) - nrow(rv$tmpData), " features removed"), type = "success")
}
})
observeEvent(input$saveBF, {
additionalInfo <- paste("Blank filtrated with signal strength above blank =", input$signalStrength)
updateDataAndSequence("Blank filtrate first", input$newFileBF, paste("_", input$signalStrength, "xb"), additionalInfo)
})
## IS normalization ##
observeEvent(input$normalizeIS, {
if (is.null(rv$activeFile)) {
showNotification("No data", type = "error")
} else if (sum(rv$sequence[[rv$activeFile]][, 1] %in% "Name") != 1) {
showNotification("Data must have exactly 1 \"Name\" column", type = "error")
} else if (is.null(input$isChoose)) {
showNotification("No internal standards selected", type = "error")
} else {
sequence <- rv$sequence[[rv$activeFile]]
data <- rv$data[[rv$activeFile]]
normalized <- normalizationIS(data, sequence, input$isChoose, input$isMethod, input$normalizeQC)
if(is.null(normalized)) {
sendSweetAlert(session, "Error", "Internal standard normalization failed due to missing values in IS.", type = "error")
}
else {
# Add isnorm column to sequence
isColumn <- c("-", rep(NA, ncol(sequence) - 1))
sequence <- rbind(sequence, isColumn)
rownames(sequence)[nrow(sequence)] <- "isnorm"
rv$tmpData <- normalized
rv$tmpSequence <- sequence
sendSweetAlert(session, title = "Success", text = paste0("Internal standards normalized with ", input$isMethod, " method"), type = "success")
updateSelectInput(session, "selectpca1", selected = "Unsaved data", choices = c("Unsaved data", rv$choices))
output$dttable <- renderDataTable(rv$tmpData, rownames = FALSE, options = list(scrollX = TRUE, scrollY = "700px", pageLength = 20))
}
}
})
observeEvent(input$saveIS, {
additionalInfo <- paste("Internal standards normalized with", input$isMethod, "method")
updateDataAndSequence("IS normalize first", input$newFileIS, "_is", additionalInfo)
})
observeEvent(input$removeIS, {
if (is.null(rv$activeFile)) {
showNotification("No data", type = "error")
} else {
data <- rv$data[[rv$activeFile]]
sequence <- rv$sequence[[rv$activeFile]]
toRemove <- data[sequence[, 1] %in% "Name"]
data <- data[!grepl("\\(IS\\)", toupper(toRemove[ , 1])), ]
rv$data[[rv$activeFile]] <- data
updateCheckboxGroupInput(session, "isChoose", choices = character(0), selected = NULL)
}
})
## Missing value filtration ##
observeEvent(input$runFilterNA, {
if(is.null(rv$activeFile)) {
showNotification("No data", type = "error")
} else {
sequence <- rv$sequence[[rv$activeFile]]
method <- input$filterNAmethod
if(("in group" %in% method) & !any(complete.cases(sequence[, 4]))) {
sendSweetAlert(session, "Error!", "Group information needed.", type = "error")
}
else if(is.null(method)) {
sendSweetAlert(session, "Error!", "No method selected.", type = "error")
}
else {
mvf_dat <- cutoffrm(rv$data[[rv$activeFile]], sequence, input$cutoffNAs, method)
rv$tmpData <- mvf_dat
rv$tmpSequence <- sequence
updateSelectInput(session, "selectpca1", selected = "Unsaved data", choices = c("Unsaved data", rv$choices))
output$dttable <- renderDataTable(rv$tmpData, rownames = FALSE, options = list(scrollX = TRUE, scrollY = "700px", pageLength = 20))
sendSweetAlert(
title = "Success",
text = paste0(nrow(rv$data[[rv$activeFile]]) - nrow(rv$tmpData), " feature(s) removed"),
type = "success"
)
}
}
})
observeEvent(input$saveFilterNA, {
additionalInfo <- paste(
"Missing value filtration using",
input$cutoffNAs,
"% as threshold and method -",
paste(input$filterNAmethod, collapse=", ")
)
updateDataAndSequence("Filtrate first", input$mvf_newsave, "_mvr", additionalInfo)
})
## Imputation ##
observeEvent(input$runImputation, {
if (is.null(rv$activeFile)) {
showNotification("No data", type = "error")
} else if (sum(rv$sequence[[rv$activeFile]][, 1] %in% "Sample") < 1) {
showNotification("Data must have at least one Sample", type = "error")
} else {
data <- rv$data[[rv$activeFile]]
sequence <- rv$sequence[[rv$activeFile]]
imputed <- imputation(data, sequence, input$imputationMethod, input$imputationMinX, input$imp_onlyQC, input$remainingNAs)
rv$tmpData <- imputed
rv$tmpSequence <- sequence
updateSelectInput(session, "selectpca1", selected = "Unsaved data", choices = c("Unsaved data", rv$choices))
output$dttable <- renderDataTable(rv$tmpData, rownames = FALSE, options = list(scrollX = TRUE, scrollY = "700px", pageLength = 20))
sendSweetAlert(
title = "Success",
text = paste0(sum(is.na(rv$data[[rv$activeFile]]) | rv$data[[rv$activeFile]] == 0) - sum(is.na(rv$tmpData) | rv$tmpData == 0), " missing values were imputed."),
type = "success"
)
}
})
observeEvent(list(input$imputationMethod, input$remainingNAs), {
if (input$imputationMethod == "KNN") {
hide("imp_minx_hide")
hide("imp_remaining_hide")
} else {
show("imp_remaining_hide")
}
if (input$imputationMethod == "Min/X" || input$remainingNAs == "Min/X") {
show("imp_minx_hide")
} else {
hide("imp_minx_hide")
}
})
observeEvent(input$saveImputation, {
additionalInfo <- paste("Missing values imputation with", input$imputationMethod)
updateDataAndSequence("Impute first", input$newFileImp, "_imp", additionalInfo)
})
## Drift correction ##
# observeEvent(input$driftMethod, {
# if (input$driftMethod == "QC-RFSC (random forrest)") {
# hide("dc_qcspan_hide")
# hide("dc_degree_hide")
# show("dc_ntree_hide")
# } else {
# hide("dc_ntree_hide")
# show("dc_qcspan_hide")
# show("dc_degree_hide")
# }
# })
observeEvent(input$runDrift, {
if (is.null(rv$activeFile)) {
showNotification("No data", type = "error")
} else if (is.null(rv$sequence[[rv$activeFile]])) { #TODO remove? sequence is never NULL
showNotification("No sequence file", type = "error")
} else if (all(is.na(rv$sequence[[rv$activeFile]][, 'order']))) {
showNotification("No order information, upload sequence", type = "error")
} else {
data <- rv$data[[rv$activeFile]]
sequence <- rv$sequence[[rv$activeFile]]
dat_qc <- data[, sequence[, 1] %in% "QC"]
if(any(colSums(!is.na(dat_qc)) != nrow(dat_qc))) {
sendSweetAlert(session = session, title = "Error", text = "QCs cannot have missing values.", type = "error")
}
else {
corrected <- driftCorrection(data, sequence, input$driftMethod, input$driftTrees, input$driftDegree, input$driftQCspan)
rv$tmpData <- corrected
rv$tmpSequence <- sequence
updateSelectInput(session, "selectpca1", selected = "Unsaved data", choices = c("Unsaved data", rv$choices))
output$dttable <- renderDataTable(rv$tmpData, rownames = FALSE, options = list(scrollX = TRUE, scrollY = "700px", pageLength = 20))
}
}
})
observeEvent(input$saveDrift, {
additionalInfo <- paste(
"Drift correction applied using method: ", input$driftMethod,
"with ", input$driftTrees, " trees."
)
updateDataAndSequence("Drift correct first", input$newFileDrift, "_dc", additionalInfo)
})
## Merge datasets ##
observeEvent(input$editRankings, {
showModal(
modalDialog(
title = "Change the priority of annotations", size = "s", easyClose = TRUE,
footer = list(actionButton("md_edit_rankings", "Save edits"), modalButton("Dismiss")),
lapply(1:10, function(x) {
fluidRow(
column(
width = 8,
textInput(paste0("md_rankings_text", x), NULL, value = rankings_merge[x, 1], placeholder = "Empty")
),
column(
width = 4,
numericInput(paste0("md_rankings_prio", x), NULL, value = rankings_merge[x, 2], min = 0, max = 10)
),
)
})
)
)
})
observeEvent(input$md_edit_rankings, {
sapply(1:10, function(x) {
rankings_merge[x, 1] <<- toupper(input[[paste0("md_rankings_text", x)]])
rankings_merge[x, 2] <<- input[[paste0("md_rankings_prio", x)]]
})
removeModal()
})
observeEvent(input$mergeDatasets, {
if (is.null(rv$activeFile)) {
showNotification("No data", type = "error")
} else {
activeSequence <- rv$sequence[[rv$activeFile]]
activeDataset <- rv$data[[rv$activeFile]]
selected <- which(rv$choices %in% input$mergeFile)
if(is.null(selected)) {
showNotification("No file selected", type = "error")
} else {
sequenceToMerge <- rv$sequence[[selected]]
datasetToMerge <- rv$data[[selected]]
if(names(rv$data)[rv$activeFile] == names(rv$data)[selected]) {
showModal(
modalDialog(
title = "Do you want to merge a dataset with itself?", size = "m",
footer = list(actionButton("mergeSameFile", "Yes"), modalButton("Cancel"))
)
)
} else {
userConfirmation(TRUE)
}
}
}
})
observeEvent(input$mergeSameFile, {
userConfirmation(TRUE)
removeModal()
})
observeEvent(userConfirmation(), {
if(userConfirmation()) {
activeSequence <- rv$sequence[[rv$activeFile]]
activeDataset <- rv$data[[rv$activeFile]]
selected <- which(rv$choices %in% input$mergeFile)
sequenceToMerge <- rv$sequence[[selected]]
datasetToMerge <- rv$data[[selected]]
if (sum(activeSequence[, 1] %in% c("Adduct_pos", "Adduct_neg")) != 1 || sum(sequenceToMerge[, 1] %in% c("Adduct_pos", "Adduct_neg")) != 1) {
sendSweetAlert(session = session, title = "Error", text = "Each dataset must contain exactly one adduct column labeled in the sequence file.", type = "error")
} else if (ncol(activeDataset) != ncol(datasetToMerge)) {
sendSweetAlert(session = session, title = "Error", text = "Datasets must have the same number of columns", type = "error")
} else {
mergedDatasets <<- mergeDatasets(activeDataset, activeSequence,
datasetToMerge, sequenceToMerge, input$merge_ppm, input$merge_rt)
clustn <- data.frame(table(mergedDatasets$mergeID))
dub_clust <- clustn[clustn$Freq > 1, ]
dub_dat <- mergedDatasets[mergedDatasets$mergeID %in% dub_clust[, 1], ]
dub_qc <- dub_dat[, activeSequence[, 1] %in% "QC"]
cov <- cv(dub_qc)
nclust <- sapply(dub_dat$mergeID, function(x) {
table(dub_dat$mergeID)[names(table(dub_dat$mergeID)) == x]
})
colnames(dub_dat)[activeSequence[, 1] %in% c("Adduct_pos", "Adduct_neg")] <- "adduct"
out_dub <- data.frame(
"nClust" = nclust,
"Cluster_ID" = dub_dat$mergeID,
"Ion_mode" = dub_dat$ionmode,
"Adductor" = dub_dat$adduct,
"Name" = dub_dat[, which(activeSequence[, 1] %in% "Name")],
"RT" = dub_dat[, which(activeSequence[, 1] %in% "RT")],
"Mass" = dub_dat[, which(activeSequence[, 1] %in% "Mass")],
"CV" = cov
)
out_dub <- out_dub[order(out_dub[, 1], out_dub[, 2], decreasing = T), ]
md_dup <<- out_dub
cluster_ends <- which(!duplicated(out_dub[, 2]))
output$md_modal_dt <- renderDataTable({
datatable(out_dub,
rownames = F,
options = list(dom = "t", autowidth = T, paging = F),
selection = list(selected = finddup(out_dub, rankings_merge))
) %>% formatStyle(1:8, `border-top` = styleRow(cluster_ends, "solid 2px"))
},
server = T
)
userConfirmation(FALSE)
showModal(
modalDialog(
title = "Select features to keep", size = "l",
p(paste0(length(unique(dub_dat$mergeID))), " duplicate clusters found, of those ", paste0(length(unique(out_dub[out_dub[, 1] > 2, ][, 2]))), " consists of more than 2 features."),
DTOutput("md_modal_dt"),
footer = list(actionButton("confirmMerging", "Remove duplicates"), modalButton("Dismiss"))
)
)
}
}
})
observeEvent(input$confirmMerging, {
duplicates <- as.numeric(rownames(md_dup[-input$md_modal_dt_rows_selected, ]))
merged <<- mergedDatasets[-duplicates, ]
output$dttable <- renderDataTable(merged, rownames = F, options = list(scrollX = TRUE, scrollY = "700px", pageLength = 20))
removeModal()
confirmSweetAlert(session, inputId = "newFileMerge", title = "Merge complete", text = "Save as new file?", btn_labels = c("No", "Yes"), type = "success")
})
observeEvent(input$newFileMerge, {
if (isTRUE(input$newFileMerge)) {
rv$data[[length(rv$data) + 1]] <- merged[, seq(ncol(merged) - 2)]
rv$sequence[[length(rv$sequence) + 1]] <- rv$sequence[[rv$activeFile]]
names(rv$data)[length(rv$data)] <- paste0(names(rv$data)[rv$activeFile], "_merged")
initializeVariables()
} else if (isFALSE(input$newFileMerge)) {
rv$data[[rv$activeFile]] <- merged[, seq(ncol(merged) - 2)]
names(rv$data)[rv$activeFile] <- paste0(names(rv$data)[rv$activeFile], "_merged")
}
rv$info[length(rv$data)] <- paste(ifelse(is.na(rv$info[rv$activeFile]), "", rv$info[rv$activeFile]), "Positive and negative mode merged: M/z tolerance ppm", input$merge_ppm, "and RT tolerance", input$merge_rt, "\n")
rv$choices <- paste(1:length(rv$data), ": ", names(rv$data))
})
## Principal Component Analysis ##
#TODO
observeEvent(input$run_pca1, {
if (!is.null(rv$activeFile)) {
if (input$selectpca1 == "Unsaved data") {
data <- rv$tmpData
seq <- rv$tmpSequence
} else {
selectchoices <- paste(seq_along(rv$data), ": ", names(rv$data))
sd <- which(rv$choices %in% input$selectpca1)
data <- rv$data[[sd]]
seq <- rv$sequence[[sd]]
}
if ("Sample" %in% seq[, 1]) {
if(any(seq[, 1] %in% "QC"))
seq[seq[, 1] %in% "QC", ][, 4] <- "QC"
sdata <- data[seq[, 1] %in% c("Sample", "QC")]
sclass <- seq[seq[, 1] %in% c("Sample", "QC"), ][, 4]
pca <- pcaplot(sdata, sclass, input$pca1_islog)
output$plotpca1 <- renderPlotly(pca)
if (sum(seq[, 1] %in% "QC") > 0) {
qccv <- paste0("CV in QC samples: ", round(cvmean(data[seq[, 1] %in% "QC"]), 2), "</br>")
} else {
qccv <- "No QC in dataset </br>"
}
sclass <- sclass[sclass != "QC"]
if (sum(!is.na(sclass)) > 0) {
classcv <- sapply(sort(unique(sclass)), function(x) {
round(cvmean(sdata[, sclass %in% x]), 2)
})
classcv <- sapply(seq_along(classcv), function(x) {
paste0("CV in group ", sort(unique(sclass))[x], ": ", classcv[x], "</br>")
})
} else {
classcv <- NULL
}
text <- c(qccv, classcv)
output$pca1Details <- renderUI({
HTML(text)
})
}
}
})
observeEvent(input$run_pca2, {
selectchoices <- paste(seq_along(rv$data), ": ", names(rv$data))
sd <- which(rv$choices %in% input$selectpca2)
if ("Sample" %in% rv$sequence[[sd]][, 1]) {
data <- rv$data[[sd]]
seq <- rv$sequence[[sd]]
shinyCatch(
seq[seq[, 1] %in% "QC", ][, 4] <- "QC",
blocking_level = 'message',
shiny = FALSE
)
sdata <- data[seq[, 1] %in% c("Sample", "QC")]
sclass <- seq[seq[, 1] %in% c("Sample", "QC"), ][, 4]
pca <- pcaplot(sdata, sclass, input$pca2_islog)
output$plotpca2 <- renderPlotly(pca)
if (sum(seq$labels %in% "QC") > 0) {
qccv <- paste0("CV in QC samples: ", round(cvmean(data[seq[, 1] %in% "QC"]), 2), "</br>")
} else {
qccv <- "No QC in dataset </br>"
}
sclass <- sclass[sclass != "QC"]
if (sum(!is.na(sclass)) > 0) {
classcv <- sapply(sort(unique(sclass)), function(x) {
round(cvmean(sdata[sclass %in% x]), 2)
})
classcv <- sapply(seq_along(classcv), function(x) {
paste0("CV in group ", sort(unique(sclass))[x], ": ", classcv[x], "</br>")
})
} else {
classcv <- NULL
}
text <- c(qccv, classcv)
output$pca2Details <- renderUI({
HTML(text)
})
}
})
observeEvent(input$select_boxplot_1, { #TODO which rv choices -> function
data <- rv$data[[which(rv$choices %in% input$select_boxplot_1)]]
sequence <- rv$sequence[[which(rv$choices %in% input$select_boxplot_1)]]
group <- input$select_boxplot_1_group
data <- data[sequence[, 1] %in% "Sample" & sequence[, 4] %in% group]
output$boxplot_1 <- renderPlot({
boxplot(log2(data), main = input$select_boxplot_1, xlab = "Analyte", ylab = "Intensity")
})
}, ignoreInit = TRUE)
observeEvent(input$drift_1, {
rv$drift_plot_select <- 1
})
observeEvent(input$drift_2, {
rv$drift_plot_select <- 2
})
observeEvent(input$drift_3, {
rv$drift_plot_select <- 3
})
output$drift_ui <- renderUI({
box(
width = NULL,
if (is.null(rv$activeFile)) {
p("No data")
} else if (input$drift_select != "None" && nrow(rv$data[[rv$activeFile]]) != nrow(rv$data[[which(rv$choices %in% input$drift_select)]])) {
p("Not able to compare the selected datasets")
} else if (input$drift_select == "None" && rv$drift_plot_select == 2) {
p("Need dataset to compare with")
} else if (is.null(input$dt_drift_panel_rows_selected) && rv$drift_plot_select == 1) {
p("Select feature to plot")
} else if (rv$drift_plot_select == 1) {
lapply(seq_along(input$dt_drift_panel_rows_selected), function(i) {
fluidRow(
column(6, plotOutput(paste0("driftplotoutput", i), height = 280, width = "100%")),
column(6, plotOutput(paste0("driftplotoutput2", i), height = 280, width = "100%"))
)
})
} else if (rv$drift_plot_select == 2) {
fluidRow(column(12, plotOutput("cvscatterplot", height = 600, width = "100%")))
} else {
p("Nothing here yet")
}
)
})
output$boxplot_ui <- renderUI({
box(
width = NULL,
if (is.null(rv$activeFile)) {
p("No data")
} else if (is.null(input$dt_boxplot_panel_rows_selected)) {