server.R
In genBaRcode: Analysis and Visualization Tools for Genetic Barcode Data

## FV1.0

makeReactiveTrigger <- function() {
  rv <- reactiveValues(a = 0)
  list(
    depend = function() {
      rv$a
    },
    trigger = function() {
      rv$a <- isolate(rv$a + 1)
    },
    reset = function() {
      rv$a <- 0
    }
  )
}

makeHistory <- function() {
  hist <- reactiveValues(old = NULL)

  list(
    old = function() {
      hist$old
    },
    update = function(x) {
      hist$old <- x
    }
  )
}

makeGeneralHistory <- function() {
  hist <- reactiveValues(show = NULL, show_sCode = NULL)

  list(
    show = function() {
      hist$show
    },
    update = function(x) {
      hist$show <- x
    },
    show_sCode = function() {
      hist$show_sCode
    },
    update_sCode = function(y) {
      hist$show_sCode <- y
    }
  )
}

shinyServer(
  function(input, output, session) {

    require("genBaRcode")
    require("ggplot2")

    if (is.null(getOption("genBaRcode-shinyDir"))) {
      stopApp("Please use the 'genBaRcode_app' function to start the app!")
    }

    seqL <- NULL

    givenDir <- genBaRcode:::.testDirIdentifier(getOption("genBaRcode-shinyDir"))
    flag <- givenDir != paste0(system.file("extdata", package = "genBaRcode"), .Platform$file.sep)

    fileTrigger <- makeReactiveTrigger()
    history <- makeHistory()
    genHist <- makeGeneralHistory()

    ############################
    ### UI functional linkage
    ############################

    output$selection <- renderUI({
      if (fileTrigger$depend() == 0) {
        processing_UI_choose_file()
      } else {
        options("genBaRcode-info" = "")
        plot_UI()
      }
    })

    output$parameters <- renderUI({
      if (fileTrigger$depend() == 0 & !is.null(input$fileType)) {
        if (input$fileType == "fastq") {
          processing_UI_fastq()
        } else {
          if(input$fileType == "csv") {
            processing_UI_csv()
          } else {
            NULL
          }
        }
      } else {
        NULL
      }
    })

    output$end <- renderUI({
      if (fileTrigger$depend() == 0) {
        processing_UI_end()
      } else {
        NULL
      }
    })


    output$G_and_T <- renderUI({
      if (fileTrigger$depend() == 0) {
        NULL
      } else {
        G_and_T_UI()
      }
    })

    output$caption <- renderText({
      capText()
    })

    ##################
    ### caption
    ##################

    capText <- reactive({
      if (fileTrigger$depend() == 0 | is.null(input$plot_click)) {
        return(getOption("genBaRcode-info"))
      }
    })

    #############################
    ### plot creation
    #############################

    dat <- reactive({
      if (length(input$f_name) == 1) {
        if (input$error_corr & input$plot_type != "HD Graph" & input$plot_type != "interactive HD Graph" & input$backbone != "none") {
          isolate(genHist$update_sCode(rbind(genHist$show_sCode(), sCode_snippets(type = "ec", gDir = givenDir))))
          tmp <- BC()$datEC
          tmp@reads <- slot(BC()$datEC, "reads")[1:input$maxBCs_EC, ]
        } else {
          tmp <- BC()$dat
          tmp@reads <- slot(BC()$dat, "reads")[1:input$maxBCs, ]
        }
      } else {
        if (input$error_corr & input$backbone != "none") {
          tmp <- BC()$datEC
        } else {
          tmp <- BC()$dat
        }
      }
      #}
      return(tmp)
    })

    finalPlot2 <- reactive({
      if (input$plot_type == "interactive HD Graph" & fileTrigger$depend() != 0) {
        isolate(genHist$update_sCode(rbind(genHist$show_sCode(), sCode_snippets(type = "inHD_Graph", gDir = givenDir))))
        return(plotDistanceVisNetwork(dat(), minDist = 1, loga = TRUE, oriBCs(), complete = input$compl, col_type = input$palette))
      }
    })

    finalPlot <-  reactive({

      if (fileTrigger$depend() == 0) {
        return(ggplot2::ggplot() + ggplot2::theme_minimal())
      }

      if (input$plot_type == "Kirchenplot") {
        isolate(genHist$update_sCode(rbind(genHist$show_sCode(), sCode_snippets(type = "kirchenplot", gDir = givenDir))))
        return(generateKirchenplot(dat(), ori_BCs = oriBCs(), loga = input$loga, col_type = input$palette))
      }

      if (input$plot_type == "Read Frequencies") {
        isolate(genHist$update_sCode(rbind(genHist$show_sCode(), sCode_snippets(type = "readFreq", gDir = givenDir))))
        return(plotReadFrequencies(dat(), b = input$bins, show_it = FALSE))
      }

      if (input$plot_type == "SeqLogo") {
        isolate(genHist$update_sCode(rbind(genHist$show_sCode(), sCode_snippets(type = "seqLo", gDir = givenDir))))
        return(plotSeqLogo(as.character(slot(dat(), "reads")$"barcode")))
      }

      if (input$plot_type == "SeqLogo - NGS reads") {
        if (is.null(seqL)) {

          ending <- strsplit(input$f_name, split = "[.]", fixed = FALSE, perl = FALSE, useBytes = FALSE)[[1]][2]
          if (ending == "fasta") {
            seqL <<- ShortRead::readFasta(dirPath = givenDir, pattern = input$f_name)
          } else {
            seqL <<- ShortRead::readFastq(dirPath = givenDir, pattern = input$f_name)
          }
        }

        l <- nchar(as.character(ShortRead::sread(seqL)[1]))
        return(plotSeqLogo(as.character(ShortRead::sread(seqL))) + ggplot2::scale_x_continuous(breaks = c(1, round(l/2), l)))
      }

      if (input$plot_type == "Tree") {
        if (input$tree_est == "Neighbor-Joining") { tEst <- "NJ" }
        if (input$tree_est == "Unweighted Pair Group Method (UPGMA)") { tEst <- "UPGMA" }

        return(plotClusterGgTree(dat(), type = input$tree_style, tree_est = tEst))
      }

      if (input$plot_type == "HD Graph") {
        isolate(genHist$update_sCode(rbind(genHist$show_sCode(), sCode_snippets(type = "HD_Graph", gDir = givenDir))))
        return(ggplotDistanceGraph(dat(), minDist = 1, loga = TRUE, oriBCs(), lay = input$graph_layout, complete = input$compl, col_type = input$palette) + ggplot2::theme(panel.grid.major = ggplot2::element_blank(), panel.grid.minor = ggplot2::element_blank()))
      }

      if (input$plot_type == "Time Series") {
        isolate(genHist$update_sCode(rbind(genHist$show_sCode(), sCode_snippets(type = "timeS_plot"))))
        return(plotTimeSeries(dat()[[2]]))
      }

      if (input$plot_type == "Venn Diagram") {
        isolate(genHist$update_sCode(rbind(genHist$show_sCode(), sCode_snippets(type = "timeS_Venn"))))
        return(plotVennDiagram(dat()[[1]]) + ggplot2::theme(panel.grid.major = ggplot2::element_blank(), panel.grid.minor = ggplot2::element_blank()))
      }

    })

    ####################
    ### table creation
    ####################

    output$table_overview <- renderDataTable({
      if (fileTrigger$depend() == 0) {
        return(NULL)
      }

      if ((length(input$f_name) == 0) | is.null(input$f_name)) {
        d <- NULL
      }

      if (length(input$f_name) == 1) {
        if (input$backbone == "none") {
          d <- data.frame(feature = c("number of barcodes",
                                      "read count min",
                                      "read count median",
                                      "read count mean",
                                      "read count max"),
                          data = c(as.character(dim(slot(BC()$dat, "reads"))[1]),
                                   as.character(round(summary(slot(BC()$dat, "reads")[, 1])[c(1, 3, 4, 6)])))
          )
        } else {
          d <- data.frame(feature = c("number of barcodes",
                                      "number of barcodes (EC)",
                                      "read count min",
                                      "read count median",
                                      "read count mean",
                                      "read count max",
                                      "read count min (EC)",
                                      "read count median (EC)",
                                      "read count mean (EC)",
                                      "read count max (EC)"),
                          data = c(as.character(dim(slot(BC()$dat, "reads"))[1]),
                                   as.character(dim(slot(BC()$datEC, "reads"))[1]),
                                   as.character(round(summary(slot(BC()$dat, "reads")[, 1])[c(1, 3, 4, 6)])),
                                   as.character(round(summary(slot(BC()$datEC, "reads")[, 1])[c(1, 3, 4, 6)])))
          )
        }
      }
      if(length(input$f_name) > 1) {
        if(input$backbone != "none") {
          d <- data.frame(feature = c("number of barcodes",
                                      "number of barcodes (EC)",
                                      paste("time point", 1:dim(BC()$dat[[2]])[2], "(reads)")),
                          data = c(as.character(dim(BC()$dat[[2]])[1]),
                                   as.character(dim(BC()$datEC[[2]])[1]),
                                   as.character(colSums(BC()$dat[[2]])))
          )
        } else {
          d <- data.frame(feature = c("number of barcodes",
                                      paste("time point", 1:dim(BC()$dat[[2]])[2], "(reads)")),
                          data = c(as.character(dim(BC()$dat[[2]])[1]),
                                   as.character(colSums(BC()$dat[[2]])))
          )
        }
      }
      return(d)
    })

    output$table_dat <- renderDataTable({
      if (length(input$f_name) == 1) {
        return(slot(BC()$dat, "reads")) # [, 2:3]
      }
      if (length(input$f_name) > 1) {
        tmp <- data.frame(BC = row.names(BC()$dat[[2]]))
        tmp <- cbind(tmp, as.data.frame(BC()$dat[[2]]))
        colnames(tmp) <- c("BC", paste("tp", 1:dim(BC()$dat[[2]])[2]))
        return(tmp)
      }
    })

    output$table_EC <- renderDataTable({

      if(input$backbone == "none") {
       "no error correction available"
      } else {
        if(length(input$f_name) == 1) {
          return(slot(BC()$datEC, "reads")) # [, 2:3]
        }
        if(length(input$f_name) > 1) {
          tmp <- data.frame(BC = row.names(BC()$datEC[[2]]))
          tmp <- cbind(tmp, as.data.frame(BC()$datEC[[2]]))
          colnames(tmp) <- c("BC", paste("tp", 1:dim(BC()$datEC[[2]])[2]))
          return(tmp)
        }
      }
    })

    output$table_clickHist <- renderDataTable({

      if(length(input$f_name) == 1 & !is.null(genHist$show())) {
        tmp <-  genHist$show()
        colnames(tmp) <- c("barcode", "read counts")
        return(tmp)
      }
      if(length(input$f_name) > 1) {
        return("")
      }

    })

    output$table_sCodeHist <- renderDataTable({

      tmp <- cbind(genHist$show_sCode(), "")
      colnames(tmp) <- c("", "")
      return(tmp)
    })

    ####################
    ### UI design
    ####################

    processing_UI_choose_file <- function() {
      span(
        br(),
        radioButtons("fileType", label = "file type", choices = c("csv", "fastq"), selected = "fastq", inline = TRUE)
      )
    }

    processing_UI_csv <- function() {
      span(
        br(),
        selectInput("f_name", "choose file", choices = c("", list.files(givenDir, pattern = input$fileType)), multiple = TRUE),
        fileInput("file1", "choose known BCs file", accept = c("text/csv",
                                                               "text/comma-separated-values,text/plain",
                                                               "csv")),

        conditionalPanel(
          condition = "input.backbone == 'own Design'",
          textInput("ownDesign", label = "backbone", value = "", width = NULL, placeholder = "N indicates variable positions e.g. ACTNNGCANN")
        ),

        fluidRow(
          column(8,
                 numericInput("minReads", "min. reads:", 3, min = 0)),
          column(8,
                 numericInput("maxHD", "maxHD EC", 1, min = 0))
        )
      )
    }

    processing_UI_fastq <- function(fname) {
      span(
        br(),
        selectInput("f_name", "choose file", choices = c("", list.files(givenDir, pattern = input$fileType)), multiple = TRUE),
        fileInput("file1", "choose known BCs file", accept = c(".fastq", ".fasta")),

        selectInput("backbone", "choose backbone", choices = c("", "BC16-GFP",
                                                               "BC16-Venus",
                                                               "BC16-mCherry",
                                                               "BC16-Cerulean",
                                                               "BC32-GFP",
                                                               "BC32-Venus",
                                                               "BC32-eBFP",
                                                               "BC32-T-Sapphire",
                                                               "none",
                                                               "Own Design")),

        conditionalPanel(
          condition = "input.backbone == 'Own Design'",
          textInput("ownDesign", label = "backbone", value = "", width = NULL, placeholder = "N indicates variable positions e.g. ACTNNGCANN")
        ),

        fluidRow(
          column(8,
                 numericInput("mm", "mismatches", 0, min = 0)),
          column(8,
                 numericInput("minReads", "min. reads", 3, min = 0)),
          column(8,
          conditionalPanel(
            condition = "input.backbone != 'none'",
            numericInput("maxHD", "maxHD EC", 1, min = 0))
          )
        ),
        checkboxInput("quaFil", "quality filtering", TRUE)
      )
    }

    processing_UI_end <- function() {
      span(
        br(),
        actionButton(inputId = "go", label = "Go"),
        actionButton(inputId = "qM", label = "?", width = "40px"),
        actionButton(inputId = "exit", label = "Exit")
      )
    }

    plot_UI <- function() {

      if(length(input$f_name) == 1) {
        cs <- c("", "Kirchenplot", "Read Frequencies", "HD Graph", "interactive HD Graph", "Tree", "SeqLogo")
        if(input$fileType == "fastq" & input$backbone != "none") {
          cs <- c(cs, "SeqLogo - NGS reads")
        }
      } else {
        cs <- c("", "Time Series", "Venn Diagram")
      }

      span(
        fluidRow(
          column(8,
                 selectInput("plot_type", "plot type:",
                             choices = cs)
          ),
          column(4,
                 conditionalPanel(
                   condition = "(((!(input.error_corr)) |
                   input.plot_type == 'HD Graph' |
                   input.plot_type == 'interactive HD Graph')) & input.f_name == 1",
                   numericInput("maxBCs", "max. BCs:",
                                value = ifelse(length(input$f_name) == 1, dim(slot(BC()$dat, "reads"))[1], dim(BC()$dat[[2]])[1]),
                                min = 0,
                                max = ifelse(length(input$f_name) == 1, dim(slot(BC()$dat, "reads"))[1], dim(BC()$dat[[2]])[1])
                   )
                 ),
                 conditionalPanel(
                   condition = "((input.error_corr & input.plot_type != 'HD Graph' & input.plot_type != 'interactive HD Graph') & input.f_name == 1) & input.backbone != 'none'",
                   numericInput("maxBCs_EC", "max. BCs:",
                                value = ifelse(length(input$f_name) == 1, dim(slot(BC()$datEC, "reads"))[1], dim(BC()$datEC[[2]])[1]),
                                min = 0,
                                max = ifelse(length(input$f_name) == 1, dim(slot(BC()$datEC, "reads"))[1], dim(BC()$datEC[[2]])[1])
                   )
                 )
          )
        ),
        conditionalPanel(
          condition = "input.plot_type == 'Read Frequencies'",
          numericInput("bins", "bins:", value = 30, min = 0, max = 100)
        ),

        conditionalPanel(
          condition = "input.plot_type == 'HD Graph'",
          selectInput("graph_layout", "graph layout:",
                      choices = c("fruchtermanreingold", "kamadakawai"))
        ),

        conditionalPanel(
          condition = "input.plot_type == 'Tree'",
          selectInput("tree_est", "tree estimation alg:",
                      choices = c("Neighbor-Joining", "Unweighted Pair Group Method (UPGMA)")),
          selectInput("tree_style", "tree layout:",
                      choices = c('rectangular', 'slanted', 'fan', 'circular', 'radial', 'equal_angle', 'daylight'))
        ),

        if(!is.null(oriBCs())) {
          conditionalPanel(
            condition = "input.plot_type == 'Kirchenplot' | input.plot_type == 'HD Graph' | input.plot_type == 'interactive HD Graph'",
            selectInput("palette", "color palette:",
                        choices = c("rainbow", "heat", "topo.colors"))
          )
        },

        conditionalPanel(
          condition = "input.plot_type != 'SeqLogo - NGS' & input.plot_type != '' & input.plot_type != 'Read Frequencies' & input.plot_type != 'HD Graph' & input.plot_type != 'interactive HD Graph' & input.backbone != 'none'",
          checkboxInput("error_corr", "error correction", FALSE)
        ),

        conditionalPanel(
          condition = "input.plot_type == 'Kirchenplot'",
          checkboxInput("loga", "log values", FALSE)
        ),
        conditionalPanel(
          condition = "input.plot_type == 'HD Graph' | input.plot_type == 'interactive HD Graph'",
          checkboxInput("compl", "complete graph", FALSE)
        ),
        br(),
        fluidRow(
          column(2, actionButton(inputId = "new", label = "New", width = '55px'), offset = 0),
          conditionalPanel(
            condition = "input.plot_type == 'interactive HD Graph'",
            column(2, actionButton(inputId = "save", label = "Save", width = '55px', style = ifelse(flag, "color: black", "color: lightgray")), offset = 0)
          ),
          column(2, actionButton(inputId = "exit2", label = "Exit", width = '55px'), offset = 0),
          column(2, actionButton(inputId = "qM2", label = "?", width = "40px"), offset = 0)
        )
      )
    }

    G_and_T_UI <- function() {
      if (fileTrigger$depend() != 0) {
        span(
          conditionalPanel(
            condition = "input.plot_type != 'interactive HD Graph'",
            plotly::plotlyOutput("final_plot", width = "100%")
          ),
          conditionalPanel(
            condition = "input.plot_type == 'interactive HD Graph'",
            visNetwork::visNetworkOutput("final_plot2", width = "100%")
          ),
          br(),
          tabsetPanel(
            tabPanel("overview", dataTableOutput("table_overview")),
            tabPanel('barcode list', dataTableOutput("table_dat")),
            tabPanel('barcode list (EC)', dataTableOutput("table_EC")),
            tabPanel('source code', dataTableOutput("table_sCodeHist"))
          )
        )
      }
    }

    observe({
      if (!(is.null(input$plot_type)) & fileTrigger$depend() != 0) {
        if (input$plot_type == "interactive HD Graph") {
          output$final_plot2 <- visNetwork::renderVisNetwork({
            finalPlot2()
          })
        } else {
          if (input$plot_type != "") {
            output$final_plot <- plotly::renderPlotly({
              p <- suppressMessages(plotly::ggplotly(finalPlot()))
              p$elementId <- NULL
              if (input$plot_type != "SeqLogo - NGS" & input$plot_type != "SeqLogo" & input$plot_type != "Tree" & input$plot_type != "Venn Diagram" & input$plot_type != "Time Series") {
                content <- paste(paste("BC:", methods::slot(dat(), "reads")$barcode),
                                 paste("reads:", methods::slot(dat(), "reads")$read_count), sep = "<br />")

                if (input$plot_type == "HD Graph") {
                  if (is.null(oriBCs())) {
                    p$x$data[[2]]$text <- content
                  } else {
                    for (p_depth in 2:length(p$x$data)) {
                      tmp_p_x_data <- matrix(unlist(strsplit(p$x$data[[p_depth]]$text, split = "<br />")), ncol = 4, byrow = TRUE)
                      index_p_x_data <- match(tmp_p_x_data[, 2], methods::slot(dat(), "reads")$barcode)

                      p$x$data[[p_depth]]$text <- content[index_p_x_data]
                    }
                  }
                } else {
                  if (input$plot_type == "Kirchenplot") {
                    if (is.null(oriBCs())) {
                      p$x$data[[1]]$text <- content
                    } else {
                      for (p_depth in 2:length(p$x$data)) {
                        tmp_p_x_data <- matrix(unlist(strsplit(p$x$data[[p_depth]]$text, split = "<br />")), ncol = 3, byrow = TRUE)
                        index_p_x_data <- as.numeric(unlist(strsplit(tmp_p_x_data[, 2], split = ":")))
                        index_p_x_data <- index_p_x_data[!is.na(index_p_x_data)]

                        p$x$data[[p_depth]]$text <- content[index_p_x_data]
                      }
                   }
                }
                p$x$layout$margin$l <- p$x$layout$margin$l + 15
                }
              }
              p
            })
          }
        }
      }
    })

    #####################
    ### reactive part
    ####################

    oriBCs <- reactive({
      if (fileTrigger$depend() == 0 | identical(isolate(history$old()), input$file1$datapath)) {
        return(NULL)
      } else {
        if (!is.null(input$file1$name)){
          end <- unlist(strsplit(input$file1$name, split = "[.]"))[2]
          if (end == "csv") {
            s <- ";"
          } else {
            if (end == "txt") {
              s <- ""
            } else {
              warning("invalid file format!")
              return(NULL)
            }
          }
          isolate(history$update(input$file1$datapath))
          isolate(genHist$update_sCode(rbind(genHist$show_sCode(), sCode_snippets(type = "oriBCs", s = s, gDir = givenDir))))
          return(as.character(unlist(read.table(input$file1$datapath, header = FALSE, sep = s, fill = TRUE))))
        }
      }
    })

    observeEvent(input$new, {
      options("genBaRcode-info" = "")
      fileTrigger$reset()
    })

    observeEvent(input$exit, {
      stopApp()
    })
    observeEvent(input$exit2, {
      stopApp()
    })

    observeEvent(input$save, {
      if (flag) {
        if (input$plot_type == "interactive HD Graph") {
          visNetwork::visSave(graph = finalPlot2(), file = paste(givenDir, input$plot_type, "_", slot(BC()$dat, "label"), ".html", sep = ""))
        }
      }
    })

    observeEvent(input$go, {
      req(input$f_name)
      if (unlist(strsplit(input$f_name, split = "[.]"))[2] != "csv") {
        req(input$mm, input$minReads, input$backbone)
      }
      fileTrigger$trigger()
      BC()
    })

    BC <- reactive({

      bcp <- "not defined"
      cpus <- floor(future::availableCores()/2)

      if (input$backbone == "none") {
        bcp <- input$backbone
      } else {
        if (input$ownDesign != "") {
          bcp <- input$ownDesign
        } else {
          if (input$backbone != "") {
            bcp <- getBackboneSelection(input$backbone)
          }
        }
      }

      if (fileTrigger$depend() != 0) {
        if (length(input$f_name) == 1) {
          withProgress(message = 'Data processing', value = 0, {
            if (unlist(strsplit(input$f_name, split = "[.]"))[2] != "csv") {
              incProgress(1/3, detail = "Barcode extraction...")
              tmp <- get_dat_single(bcp, givenDir, cpus)
              incProgress(2/3, detail = "Error Correction...")
              if (input$backbone != "none") {
                tmp_EC <- errorCorrection(tmp, maxDist = input$maxHD, save_it = flag, cpus = cpus)
              } else {
                tmp_EC <- methods::new(Class = "BCdat", reads = data.frame(), results_dir = results_dir,
                                       label = "no EC possible",
                                       BC_backbone = bc_backbone)
              }
              incProgress(3/3, detail = "Finished...")
              isolate(genHist$update_sCode(rbind(genHist$show_sCode(), sCode_snippets(type = "read", gDir = givenDir))))
            } else {
              incProgress(1/3, detail = paste0("Reading ", input$f_name, "..."))
              tmp <- readBCdat(path = givenDir, label = unlist(strsplit(input$f_name, split = "[.]"))[1], BC_backbone = bcp, file_name = input$f_name, s = ";")
              incProgress(2/3, detail = "Error Correction...")
              tmp_EC <- errorCorrection(tmp, maxDist = input$maxHD, save_it = FALSE, cpus = cpus)
              incProgress(3/3, detail = "Finished...")
              isolate(genHist$update_sCode(rbind(genHist$show_sCode(), sCode_snippets(type = "readCsv", bcp = bcp, gDir = givenDir))))
            }
            if(sum(dim(slot(tmp, "reads"))) == 0 & fileTrigger$depend() > 0) {
              options("genBaRcode-info" = "...no barcode sequences detectable...")
              fileTrigger$reset()
            } else {
              list(
                dat = tmp,
                datEC = tmp_EC
              )
            }
          })
        } else {
          withProgress(message = 'Data processing', value = 0, {
            if(unlist(strsplit(input$f_name, split = "[.]"))[2] != "csv") {
              incProgress(1/3, detail = "Barcode extraction...")
              tmp <- get_timeS(bcp, givenDir, cpus)
              incProgress(2/3, detail = "Error Correction...")
              if(input$backbone != "none") {
                tmp_EC <- get_timeS_EC(tmp, givenDir, cpus)
              } else {
                tmp_EC <- methods::new(Class = "BCdat", reads = data.frame(), results_dir = results_dir,
                                       label = "no EC possible",
                                       BC_backbone = bc_backbone)
              }
              incProgress(3/3, detail = "Finished...")
            } else {
              tmp <- tmp_EC <- list()
              incProgress(1/3, detail = "Reading files...")
              tmp <- TMP <- list()
              for(csvFiles in 1:length(input$f_name)) {
                incProgress(1/3 + (1/3 / (length(input$f_name) * csvFiles)), detail = paste("Reading ", input$f_name[csvFiles],"...", sep = ""))
                TMP[[csvFiles]] <- readBCdat(path = givenDir, label = unlist(strsplit(input$f_name[csvFiles], split = "[.]"))[1], BC_backbone = bcp, file_name = input$f_name[csvFiles], s = ";")
              }
              tmp[[1]] <- TMP
              tmp[[2]] <- generateTimeSeriesData(TMP)
              incProgress(2/3, detail = "Error Correction...")
              if(input$backbone != "none") {
                TMP <- errorCorrection(TMP, maxDist = input$maxHD, save_it = FALSE, cpus = cpus)
                tmp_EC[[1]] <- TMP
                tmp_EC[[2]] <- generateTimeSeriesData(TMP)
              } else {
                tmp_EC[[1]] <- methods::new(Class = "BCdat", reads = data.frame(), results_dir = results_dir,
                                            label = "no EC possible",
                                            BC_backbone = ifelse(is.null(BC_backbone), "", BC_backbone))
                tmp_EC[[2]] <- data.frame()
              }
              incProgress(3/3, detail = "Finished...")
            }
          })
          isolate(genHist$update_sCode(rbind(genHist$show_sCode(), sCode_snippets(type = "timeS", bcp = bcp, gDir = givenDir))))
          list(dat = tmp, datEC = tmp_EC)
        }
      }
    })

    ##################
    # basic functions
    ####################

    get_dat_single <- function(bcp, gDir, cpus) {

      processingRawData(file_name = input$f_name, source_dir = gDir,
                        results_dir = gDir,
                        mismatch = input$mm,
                        bc_backbone = bcp,
                        min_score = ifelse(input$quaFil, 30, 0), min_reads = input$minReads,
                        save_it = flag, seqLogo = TRUE, cpus = cpus)
    }

    get_timeS <- function(bcp, gDir, cpus) {

      dat_list <- vector("list", 2)
      dat_list[[1]] <- processingRawData(file_name = input$f_name, source_dir = gDir,
                                         results_dir = gDir,
                                         mismatch = input$mm,
                                         bc_backbone = bcp,
                                         min_score = ifelse(input$quaFil, 30, 0), min_reads = input$minReads,
                                         save_it = flag, cpus = cpus)
      dat_list[[2]] <- generateTimeSeriesData(dat_list[[1]])

      return(dat_list)

    }

    get_timeS_EC <- function(dat_list, gDir, cpus) {
      if(input$maxHD > 0) {
        dat_list[[1]] <- errorCorrection(dat_list[[1]], maxDist = input$maxHD,
                                         save_it = flag,
                                         cpus = cpus)
        dat_list[[2]] <- generateTimeSeriesData(dat_list[[1]])
      }
      return(dat_list)
    }

    sCode_snippets <- function(type, gDir = "", bcp = "", oriBCs = NULL, s = "") {

      return(
        switch(type,
               timeS = matrix(
                 c(
                   paste("nameList <- c(", paste("'", input$f_name, collapse =", ", "'", sep = ""), ")"),
                   paste("dat_list <- processingRawData(file_name = nameList, source_dir = '", gDir, "', results_dir = '", gDir,
                         "', mismatch = ", input$mm, ", bc_backbone = '", bcp, "', min_score = ", ifelse(input$quaFil, 30, 0),", min_reads = ", input$minReads)
                 ), ncol = 1, nrow = 2),
               timeS_plot = matrix(c("dat <- generateTimeSeriesData(dat_list)", "plotTimeSeries(dat)", ncol = 1, nrow = 2)),
               timeS_Venn = "plotVennDiagram(dat_list)",
               read = isolate(paste("BC_dat <- processingRawData(file_name = '", input$f_name, "', source_dir = '", gDir,
                                    "', results_dir = '", gDir, "', mismatch = ", input$mm, ", bc_backbone = '", bcp,
                                    "', min_score = ", ifelse(input$quaFil, 30, 0),", min_reads = ", input$minReads, ", seqLogo = TRUE)", sep = "")),
               readCsv = isolate(paste("BC_dat <- readBCdat(path = '", gDir, "', label = 'csvFile', BC_backbone = 'not_defined', file_name = '", input$f_name, "', s = ';')")),
               ec = isolate(paste("BC_dat_EC <- errorCorrection(BC_dat, maxDist = ", input$maxHD, ")", sep = "")),
               oriBCs = paste("oriBCs <- as.character(unlist(read.table('", input$file1$datapath, "', header = FALSE, sep = ", s, ", fill = TRUE)))", sep = ""),
               kirchenplot = isolate(paste("generateKirchenplot(", ifelse(input$error_corr, "BC_dat_EC", "BC_dat"), ", ", ifelse(identical(isolate(history$old()), input$file1$datapath), " ", "oriBCs = oriBCs,"), " loga = ", input$loga, ", col_type = ", ifelse(is.null(input$palette), "NULL", input$palette), ")", sep = "")),
               HD_Graph = isolate(paste("ggplotDistanceGraph(BC_dat, minDist = 1, ", ifelse(identical(isolate(history$old()), input$file1$datapath), " ", "oriBCs = oriBCs,"), " loga = ", input$loga, ", lay = '", input$graph_layout, "', complete = ", input$compl, ifelse(is.null(oriBCs()), "", paste0(", col_type = ", input$palette)), ")", sep = "")),
               tree = isolate(paste("plotClusterTree(BC_dat, type = ", input$tree_style, ", tipLabel = ", input$show_tip_label, ")", sep = "")),
               readFreq = isolate(paste0("plotReadFrequencies(BC_dat, b = ", input$bins, ", show_it = FALSE, log = FALSE)")),
               seqLo = paste0("plotSeqLogo(", ifelse(input$error_corr, "BC_dat_EC", "BC_dat"), ")"),
               inHD_Graph = isolate(paste0("plotDistanceVisNetwork(BC_dat, minDist = 1, loga = TRUE, oriBCs, complete = ", input$compl, ", col_type = ", input$palette, ")"))
        )
      )
    }

    ##################
    #### Help Page
    ##################

    observeEvent(input$qM, {
      help_text <- "<b>file type</b><br>It is possible to either reanalyse already saved <b>csv</b>-files or <b>raw</b> fastq-files."
      if(fileTrigger$depend() == 0) {
        if(is.null(input$f_name)) {
          help_text <- paste(help_text, "<b>choose file</b><br>Please choose one or multiple files by just clicking on the white area. In order to readjust the corresponding directory you have to restart the app and provide the path via the <i>dat_dir</i> parameter of the genBaRcode::genBaRcode_app() function.", sep = "<br><br>")
        }
        help_text <- paste(help_text,
                           "<b>choose know BCs file</b><br>If there are already known barcodes (e.g. a white list) one can chose a txt file containing those BCs.", sep = "<br><br>")
        if(input$fileType == "fastq" & input$backbone == "") {
          help_text <- paste(help_text,
                             "<b>choose backbone</b><br>Please choose a barcode backbone or enter your own backbone design, in order to extract the corresponding barcode sequences from your fastq file. If there is no backbone structure contained within your barcode construct please choose 'none'.", sep = "<br><br>")
        }
        if(input$fileType == "fastq") {
          if(input$backbone != "none") {
            help_text <- paste(help_text,
                               "<b>mismatches</b><br>The number of mismatches refers to the allowed number of divergent nucleotides while searching for the chosen backbone structure.", sep = "<br><br>")
          } else {
            help_text <- paste(help_text,
                               "<b>mismatches</b><br>If 'none' was choosen as backbone, the number of mismatches refers to the allowed number of divergent nucleotides while clustering the NGS reads.", sep = "<br><br>")
          }
        }
        help_text <- paste(help_text,
                           paste0("<b>min. reads</b><br>The number of minimum reads gives the lower read threshold for all ", ifelse(input$backbone == "none", "sequences", "barcodes"), " which will be analysed. All barcode with less reads than <i>min. reads</i> will be discarded."), sep = "<br><br>")
        if(input$backbone != "none") {
          help_text <- paste(help_text,
                             "<b>maxHD EC</b><br>The maxHD parameter refers to the number of dissimilar nucleotides allowed while clustering highly similar barcodes during error correction.", sep = "<br><br>")
        }
        if(input$fileType == "fastq") {
          help_text <- paste(help_text,
                             "<b>quality filtering</b><br>If the checkbox is checked only NGS reads with an average quality score of 30 will be included within the subsequent analyses.", sep = "<br><br>")
        }
      }

      showModal(modalDialog(
        title = "Help Page",
        HTML(help_text)
      ))
    })

    observeEvent(input$qM2, {
      showModal(
        modalDialog(
          footer = modalButton("Dismiss"), size = ifelse(input$plot_type == '', "s", "l"),
          if(input$plot_type == '') {
            HTML("Just choose one of multiple available visualisations.")
          } else {
            if(input$plot_type == 'Kirchenplot') {
              help_text <- genBaRcode:::get_help_txt("generateKirchenplot")
            }
            if(input$plot_type == 'interactive HD Graph') {
              help_text <- genBaRcode:::get_help_txt("plotDistanceVisNetwork")
            }
            if(input$plot_type == 'Read Frequencies') {
              help_text <- genBaRcode:::get_help_txt("plotReadFrequencies")
            }
            if(input$plot_type == 'SeqLogo' | input$plot_type == 'SeqLogo - NGS reads') {
              help_text <- genBaRcode:::get_help_txt("plotSeqLogo")
            }
            if(input$plot_type == 'HD Graph') {
              help_text <- genBaRcode:::get_help_txt("ggplotDistanceGraph")
            }
            if(input$plot_type == 'Time Series') {
              help_text <- genBaRcode:::get_help_txt("plotTimeSeries")
            }
            if(input$plot_type == 'Venn Diagram') {
              help_text <- genBaRcode:::get_help_txt("plotVennDiagram")
            }
            HTML(help_text)
          }
        )
      )
    })

  })