如何根据用户在 Shiny 中的输入显示不同的图？

Question

我有这个数据框：

> df
  genes  enst  x  y
1 Gene1 ENST1 25 14
2 Gene1 ENST2 60 25
3 Gene1 ENST3 12  5
4 Gene2 ENST1  9 34
5 Gene2 ENST2 14 12
6 Gene3 ENST1 10  1

我正在尝试创建一个闪亮的应用程序，它允许我选择基因和转录本。如果您选择一个基因（例如，Gene1），您将可以选择您想要的转录本（在本例中为 ENST1、ENST2、ENST3）。

问题是我想绘制 2 个图。如果您单击“基因”（级别：基因），它将对该基因的所有值求和。 例如，对于第一个基因，它有 3 个转录本，x 的总值将为 20+60+12=92，y 的总值将为 14+25+5=44）。所以绘制基因 1 的值将是：x=92 和 y=44。

此外，我想绘制每个成绩单。例如，如果您选择“Gene1”和“Transcript 1”，则绘图将使用 x=25 和 y=14。但是，如果用户决定选择两个成绩单，用户将看到 2 个图。或者如果用户选择 3 个成绩单，用户将看到 3 个不同的图。

现在，使用我的代码： 如果您选择基因，您将获得基因图。

但是，它会在同一个图中显示所有成绩单。而且我只想显示一份成绩单（或更多，如果用户愿意）

我不知道如何继续。

另一方面，有两件事我不知道如何实现。

• “查看情节”操作按钮。 --- 如果你点击它，它会显示你的情节。
• 单选按钮“级别” --- 如果您单击基因，它只会显示基因图。但是，如果您点击成绩单，它会显示成绩单图。

谁能帮帮我？提前致谢

我的代码：

library(shiny)

################ DATA #############################
genes<- c("Gene1", "Gene1", "Gene1", "Gene2", "Gene2", "Gene3")
enst <- c("ENST1", "ENST2", "ENST3", "ENST1", "ENST2", "ENST1")
x <- c(25, 60, 12, 9, 14, 10)
y <- c(14, 25, 5, 34, 12, 1)
df<- data.frame(genes, enst, x, y)

###################################################

ui <- fluidPage(
  
  # Application title
  titlePanel("Barplot"),
  
  sidebarLayout(
    sidebarPanel(
      uiOutput("selected_gene"),
      uiOutput("selected_transcript"),
      radioButtons("level", "Level:",
                   c("Gene" = "Gene",
                     "Transcript" = "Transcript")),
      h5(strong("If you want to see the plot, you have to click the button")),
      actionButton("add_plot", "See the plot"),
    ),
    
    mainPanel(
      plotOutput("plot"),
      plotOutput("plot2"),
  
      tableOutput("table1"),
      tableOutput("table2")
    )
  )
)


server <- function(session, input, output) {
  
  
  # This function gives us the list of genes.
  genes_list <- reactive({
    df$genes
    })
  
  transcripts_list <- reactive({
    
    transcripts <- subset(df, df$genes==input$gene)
    transcripts <- transcripts[,2]
    return(transcripts)
  })
  
  # This function give us a select list input, in order to be able to select the gene that we want to see
  output$selected_gene <- renderUI({
    selectizeInput(inputId = "gene", "Select one gene", choices=genes_list(), options=list(maxOptions = length(genes_list())))
  })
  
  output$selected_transcript <- renderUI({
    selectizeInput(inputId = "transcript", "Select one transcript", choices=transcripts_list(), options=list(maxOptions = length(transcripts_list())), multiple=T)
  })
  
  
  gene_values <- reactive({
    
    values <- subset(df, df[1]==input$gene)
    values$enst <- NULL
    
    if(nrow(values)>1){ #for those genes who have more than 1 transcript
      values_new <- values[2:length(values)] 
      values_new <- as.data.frame(t(colSums(values_new))) # sum the columns, transpose and transform into a dataframe
      
      gene <- values[1,] #we take the first row, only one gene but all the info.
      
      values <- cbind(values_new, gene[1]) # we bind both dataframes, however, we only want the gene name
      values <- values[,c("genes",setdiff(names(values),"genes"))] # we move the last column at the beginning
    }
    return(values)
    
  })
    
  transc_values <- reactive({

    values <- subset(df, df[1]==input$gene)
    values$genes <- NULL
  
    return(values)
  })
  
  plot_genes <- reactive({
    gene_values <- gene_values()
    barplot(c(gene_values$x, gene_values$y))
    
  })
  
  plot_transc <- reactive({
    transc_values <- transc_values()
    barplot(c(transc_values$x, transc_values$y))
    
  })
  
  
  v <- reactiveValues(plot = NULL)
  
  observeEvent(input$add_plot, {
    if(input$level == "Gene"){
      v$plot <- plot_genes()
    }
    if(input$level == "Transcript"){
      v$plot <- plot_transc()
    }
  })
  
  # This function will draw the plot
  # output$plot <- renderPlot({
  #   if (is.null(v$plot)){
  #     return()
  #   }
  #   v$plot
  # })
  
  

  output$table1 <- renderTable(gene_values())
  output$table2 <- renderTable(transc_values())
  
  output$plot <- renderPlot(plot_genes())
  output$plot2 <- renderPlot(plot_transc())
  
  
}

shinyApp(ui, server)

Answer 1

也许你可以从这个开始，根据你的需要进行修改。

library(shiny)
library(ggplot2)
library(DT)
################ DATA #############################
genes<- c("Gene1", "Gene1", "Gene1", "Gene2", "Gene2", "Gene3")
enst <- c("ENST1", "ENST2", "ENST3", "ENST1", "ENST2", "ENST1")
x <- c(25, 60, 12, 9, 14, 10)
y <- c(14, 25, 5, 34, 12, 1)
df<- data.frame(genes, enst, x, y)

###################################################

ui <- fluidPage(
  
  # Application title
  titlePanel("Histogram"),
  
  sidebarLayout(
    sidebarPanel(
      uiOutput("selected_gene"),
      uiOutput("selected_transcript"),
      radioButtons("level", "Level:",
                   c("Gene" = "Gene",
                     "Transcript" = "Transcript")),
      h5(strong("If you want to see the plot, you have to click the button")),
      div(actionButton("add_plot", "See the plot"), 
          actionButton("table", "See the table"),
          actionButton("clear", "Clear All")
          )
    ),
    
    mainPanel(
      plotOutput("plot"),
      DTOutput("table")
    )
  )
)


server <- function(input, output, session) {
  
  
  ## This function gives us the list of genes.
  genes_list <- reactive({
    unique(df$genes)
  })
  
  transcripts_list <- reactive({
    req(input$gene)
    transcripts <- subset(df, df$genes==input$gene)
    transcripts <- transcripts[,2]
    return(unique(transcripts))
  })
  
  # This function give us a select list input, in order to be able to select the gene that we want to see
  output$selected_gene <- renderUI({
    selectizeInput(inputId = "gene", "Select one gene", choices=genes_list(), options=list(maxOptions = length(genes_list())))
  })
  
  output$selected_transcript <- renderUI({
    selectizeInput(inputId = "transcript", "Select one transcript", choices=transcripts_list(), options=list(maxOptions = length(transcripts_list())), multiple=F)
  })
  
  
  gene_values <- reactive({
    req(input$gene)
    values <- subset(df, df[1]==input$gene)
    values$enst <- NULL
    
    if(nrow(values)>1){ #for those genes who have more than 1 transcript
      values_new <- values[2:length(values)] 
      values_new <- as.data.frame(t(colSums(values_new))) # sum the columns, transpose and transform into a dataframe
      
      gene <- values[1,] #we take the first row, only one gene but all the info.
      
      values <- cbind(values_new, gene[1]) # we bind both dataframes, however, we only want the gene name
      values <- values[,c("genes",setdiff(names(values),"genes"))] # we move the last column at the beginning
    }
    return(values)
    
  })
  
  transc_values <- reactive({
    req(input$transcript)
    values <- subset(df, df[2]==input$transcript)
    values$genes <- NULL
    
    return(values)
  })
  
  mydata <- reactive({
    req(input$level)
    if(input$level == "Gene"){
      df <- req(gene_values())
    }else if(input$level == "Transcript"){
      df <- req(transc_values())
    }else df <- NULL
    df
  })
  
  # plot_genes <- reactive({
  #   gene_values <- req(gene_values())
  #   barplot(c(gene_values$x, gene_values$y))
  #   
  # })
  # 
  # plot_transc <- reactive({
  #   transc_values <- req(transc_values())
  #   barplot(c(transc_values$x, transc_values$y))
  #   
  # })
  
  
  v <- reactiveValues(plot = NULL, table=NULL)
  
  observeEvent(input$add_plot, {
    v$plot <- ggplot(mydata(), aes(x=x,y=y)) + geom_bar(stat = "identity")
    v$table <- NULL  ### display only plot
  },ignoreInit = TRUE)
  
  observeEvent(input$table, {
    v$table <- req(mydata())
    v$plot <- NULL   ### display only table
  },ignoreInit = TRUE)
  
  observeEvent(input$clear, {
    v$table <- NULL
    v$plot <- NULL
  },ignoreInit = TRUE)
  
  ##  This function will draw the plot
  output$plot <- renderPlot({ v$plot })
  output$table <- renderDT({ v$table })
  
}

shinyApp(ui, server)