inst/shinyapp/modules/modules-pancan-genecor.R

In UCSCXenaShiny: Interactive Analysis of UCSC Xena Data

ui.modules_pancan_gene_cor <- function(id) {
  ns <- NS(id)
  fluidPage(
    fluidRow(
      column(
        3,
        wellPanel(
          shinyWidgets::prettyRadioButtons(
            inputId = ns("profile1"), 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_search1"),
            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. CSF1R",
              plugins = list("restore_on_backspace")
            )
          ),
          shinyWidgets::prettyRadioButtons(
            inputId = ns("profile2"), 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_search2"),
            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. JAK3",
              plugins = list("restore_on_backspace")
            )
          ))),
      column(
        3,wellPanel(
          materialSwitch(ns("purity_adj"), "Adjust Purity", inline = TRUE),
          selectInput(inputId = ns("use_all"), label = "Use All Cancer Types", choices = c("TRUE", "FALSE"), selected = "FALSE"),
          selectInput(
            inputId = ns("Cancer"), label = "Filter Cancer",
            choices = tcga_cancer_choices,
            selected = "ACC", multiple = TRUE
          ),
          materialSwitch(ns("use_regline"), "Use regression line", inline = TRUE),
          selectInput(
            inputId = ns("cor_method"),
            label = "Select Correlation method",
            choices = c("spearman", "pearson"),
            selected = "spearman"
          ),
          sliderTextInput(
            inputId = ns("alpha"),
            label = "Choose a transparent value",
            choices = seq(
              from = 0,
              to = 1,
              by = 0.1
            ),
            selected = "0.5",
            grid = TRUE
          ),
          colourpicker::colourInput(inputId = ns("color"), "Point color", "#000000"),
          tags$hr(style = "border:none; border-top:2px solid #5E81AC;"),
          shinyWidgets::actionBttn(
            inputId = ns("search_bttn"),
            label = "Go!",
            style = "gradient",
            icon = icon("search"),
            color = "primary",
            block = TRUE,
            size = "sm"
          )
        ),
        wellPanel(
          numericInput(inputId = ns("height"), label = "Height", value = 8),
          numericInput(inputId = ns("width"), label = "Width", value = 8),
          prettyRadioButtons(
            inputId = ns("device"),
            label = "Choose plot format",
            choices = c("pdf", "png"),
            selected = "pdf",
            inline = TRUE,
            icon = icon("check"),
            animation = "jelly",
            fill = TRUE
          ),
          downloadBttn(
            outputId = ns("download"),
            style = "gradient",
            color = "default",
            block = TRUE,
            size = "sm"
          )
        )
      ),
      column(
        6,
        plotOutput(ns("gene_cor"), height = "600px"),
        hr(),
        h5("NOTEs:"),
        p("1. The data query may take some time based on your network. Wait until a plot shows"),
        p("2. You could choose correlation method or whether adjust tumor purity when calculating"),
        p("3. ", tags$a(href = "https://pancanatlas.xenahubs.net/", "Genomic profile data source")),
        p("4. ", tags$a(href = "https://www.nature.com/articles/ncomms9971", "Tumor purity data source")),
        tags$br(),
        DT::DTOutput(outputId = ns("tbl")),
        shinyjs::hidden(
          wellPanel(
            id = ns("save_csv"),
            downloadButton(ns("downloadTable"), "Save as csv")
          )
        )
      )
    )
  )
}

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

  profile_choices1 <- reactive({
    switch(input$profile1,
      mRNA = list(all = pancan_identifiers$gene, default = "CSF1R"),
      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_search1",
      choices = profile_choices1()$all,
      selected = profile_choices1()$default,
      server = TRUE
    )
  })

  profile_choices2 <- reactive({
    switch(input$profile2,
      mRNA = list(all = pancan_identifiers$gene, default = "JAK3"),
      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_search2",
      choices = profile_choices2()$all,
      selected = profile_choices2()$default,
      server = TRUE
    )
  })



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

  plot_func <- eventReactive(input$search_bttn, {
    if (nchar(input$Pancan_search1) >= 1 & nchar(input$Pancan_search2) >= 1) {
      p <- vis_gene_cor_cancer(
        Gene1 = input$Pancan_search1,
        Gene2 = input$Pancan_search2,
        data_type1 = input$profile1,
        data_type2 = input$profile2,
        purity_adj = input$purity_adj,
        cancer_choose = input$Cancer,
        cor_method = input$cor_method,
        use_regline = input$use_regline,
        color = input$color,
        alpha = input$alpha,
        use_all = as.logical(input$use_all)
      )
    }
    p <- p + theme_classic(base_size = 20) +
      ggplot2::theme(legend.position = "none")

    return(p)
  })

  ## downloadTable
  output$downloadTable <- downloadHandler(
    filename = function() {
      paste0(input$Pancan_search1, "_", input$profile1, "_", input$Pancan_search2, "_", input$profile2, "_pancan_gene_cor.csv")
    },
    content = function(file) {
      write.csv(plot_func()$data, file, row.names = FALSE)
    }
  )

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

  # download module
  output$download <- downloadHandler(
    filename = function() {
      paste0(input$Pancan_search1, "_", input$profile1, "_", input$Pancan_search2, "_", input$profile2, "_pancan_gene_cor.", input$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()
      }
    }
  )

  ## return data
  observeEvent(input$search_bttn, {
    if (nchar(input$Pancan_search1) >= 1 & nchar(input$Pancan_search2) >= 1) {
      shinyjs::show(id = "save_csv")
    } else {
      shinyjs::hide(id = "save_csv")
    }
  })


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