inst/shinyapp/modules/modules-pancan-search-cancer.R

ui.modules_cancer_dist <- function(id) {
  ns <- NS(id)
  fluidPage(
    fluidRow(column(3,
                    wellPanel(
        shinyWidgets::prettyRadioButtons(
          inputId = ns("profile"), label = "Select a genomic profile:",
          choiceValues = c("mRNA", "transcript", "methylation", "protein", "miRNA", "cnv_gistic2"),
          choiceNames = c("mRNA Expression", "Transcript Expression", "DNA Methylation", "Protein Expression", "miRNA Expression", "Copy Number Variation"),
          animation = "jelly"
        ),
        selectizeInput(
          inputId = ns("Pancan_search"),
          label = "Input a gene or formula (as signature)",
          choices = NULL,
          width = "100%",
          options = list(
            create = TRUE,
            maxOptions = 5,
            placeholder = "Enter a gene symbol, e.g. TP53",
            plugins = list("restore_on_backspace")
          )
        ),
        shinyBS::bsPopover(ns("Pancan_search"),
          title = "Tips",
          content = "Enter a gene symbol to show its distribution, e.g. TP53",
          placement = "right", options = list(container = "body")
        ),
        materialSwitch(ns("pdist_mode"), "Show Dot plot", inline = TRUE),
        materialSwitch(ns("pdist_show_p_value"), "Show P value", inline = FALSE),
        materialSwitch(ns("pdist_show_p_label"), "Show P label", inline = FALSE),
        materialSwitch(ns("pdist_dataset"), "TCGA Dataset only", inline = FALSE),
        colourpicker::colourInput(inputId = ns("tumor_col"), "Tumor sample color", "#DF2020"),
        colourpicker::colourInput(inputId = ns("normal_col"), "Normal sample color", "#DDDF21"),
        selectInput(
          inputId = ns("Cancer"),
          label = "Filter Cancer",
          choices = tcga_cancer_choices,
          selected = "ACC", multiple = TRUE
        ),
        tags$hr(style = "border:none; border-top:2px solid #5E81AC;"),
        shinyWidgets::actionBttn(
          inputId = ns("search_bttn"),
          label = "Go!",
          style = "gradient",
          icon = icon("search"),
          color = "primary",
          block = TRUE,
          size = "sm"
        )
      ),
      wellPanel(
        numericInput(inputId = ns("height"), label = "Height", value = 5),
        numericInput(inputId = ns("width"), label = "Width", value = 5),
        prettyRadioButtons(
          inputId = ns("device"),
          label = "Choose plot format",
          choices = c("pdf", "png"),
          selected = "pdf",
          inline = TRUE,
          icon = icon("check"),
          animation = "jelly",
          fill = TRUE
        ),
        downloadBttn(
          outputId = ns("download"),
          style = "gradient",
          color = "default",
          block = TRUE,
          size = "sm"
        )
      ),
    ),
    column(
      9,
      plotOutput(ns("gene_cancer_dist"), height = "600px"),
      hr(),
      h5("NOTEs:"),
      p("1. The data query may take some time based on your network. Wait until a plot shows"),
      p("2. You have to turn on both 'Show P value' and 'Show P label' to show significant labels"),
      p("3. If a void plot shows, please check your input"),
      p("4. ", tags$a(href = "https://pancanatlas.xenahubs.net/", "Genomic profile data source")),
      tags$br(),
      DT::DTOutput(outputId = ns("tbl")),
      shinyjs::hidden(
        wellPanel(
          id = ns("save_csv"),
          downloadButton(ns("downloadTable"), "Save as csv")
        )
      )
    )
  )
  )
}

server.modules_cancer_dist <- function(input, output, session) {
  ns <- session$ns

  profile_choices <- reactive({
    switch(input$profile,
      mRNA = list(all = pancan_identifiers$gene, default = "TP53"),
      methylation = list(all = pancan_identifiers$gene, default = "TP53"),
      protein = list(all = pancan_identifiers$protein, default = "P53"),
      transcript = list(all = load_data("transcript_identifier"), default = "ENST00000000233"),
      miRNA = list(all = pancan_identifiers$miRNA, default = "hsa-miR-769-3p"),
      cnv_gistic2 = list(all = pancan_identifiers$gene, default = "TP53"),
      list(all = "NONE", default = "NONE")
    )
  })

  observe({
    updateSelectizeInput(
      session,
      "Pancan_search",
      choices = profile_choices()$all,
      selected = profile_choices()$default,
      server = TRUE
    )
  })

  colors <- reactive({
    c(input$tumor_col, input$normal_col)
  })

  # Show waiter for plot
  w <- waiter::Waiter$new(id = ns("gene_cancer_dist"), html = waiter::spin_hexdots(), color = "white")

  plot_func <- eventReactive(input$search_bttn, {
    if (nchar(input$Pancan_search) >= 1) {
      p <- vis_toil_TvsN_cancer(
        Gene = input$Pancan_search,
        Cancer = input$Cancer,
        Mode = ifelse(input$pdist_mode, "Dotplot", "Violinplot"),
        Show.P.value = input$pdist_show_p_value,
        Show.P.label = input$pdist_show_p_label,
        TCGA.only = input$pdist_dataset,
        values = colors(),
        data_type = input$profile
      )
    }
    return(p)
  })


  output$gene_cancer_dist <- renderPlot({
    w$show() # Waiter add-ins
    plot_func()
  })

  output$downloadTable <- downloadHandler(
    filename = function() {
      paste0(input$Pancan_search, "_", input$profile, "_", input$Cancer, "_pancan_dist.csv")
    },
    content = function(file) {
      write.csv(plot_func()$data, file, row.names = FALSE)
    }
  )

  output$download <- downloadHandler(
    filename = function() {
      paste0(input$Pancan_search, "_", input$profile, "_cancer_dist.", input$device)
    },
    content = function(file) {
      p <- plot_func()
      if (input$device == "pdf") {
        pdf(file, width = input$width, height = input$height)
        print(p)
        dev.off()
      } else {
        png(file, width = input$width, height = input$height, res = 600, units = "in")
        print(p)
        dev.off()
      }
    }
  )

  observeEvent(input$search_bttn, {
    if (nchar(input$Pancan_search) >= 1) {
      shinyjs::show(id = "save_csv")
    } else {
      shinyjs::hide(id = "save_csv")
    }
  })


  output$tbl <- renderDT(
    plot_func()$data,
    options = list(lengthChange = FALSE)
  )
}

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UCSCXenaShiny documentation built on March 7, 2023, 7 p.m.