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我刚刚发现了 Shiny 的强大之美。我尝试制作一个简单的应用程序，我可以在其中加载一个 excel 文件并使用 rcmdr 中的 FactoMineR 插件对其执行 PCA（目前，代码只是为这个特定文件编写的）。

我设法构建了一个应用程序，我可以在其中加载我的文件，并用 PCA 的结果显示三个不同的图。在 RStudio 中一切正常，但是当我部署应用程序时，图表没有显示。其他一切似乎都工作正常！

关于这个问题可能来自哪里的任何想法？

最好的问候，

莱奥洛

library(shiny)
library(gdata) 
library(Rcmdr)
library(RcmdrMisc)
library(FactoMineR)

options(shiny.sanitize.errors = FALSE)

# Define UI ----
ui <- fluidPage(
  titlePanel("Introducing PCApp"), 
  p("Lorem ipsum dolor sit amet, consectetur adipiscing elit. 
    Nam augue enim, vestibulum vitae nisi vel, placerat suscipit ipsum.
    Duis eu quam lobortis, tincidunt tellus eget, condimentum est.
    In nibh velit, tempor ac neque et, viverra pretium sapien. 
    Fusce massa sapien, varius eu rutrum at, pharetra sit amet leo. Orci varius.",
    br(), 
  sidebarLayout(position = "left",
    sidebarPanel(position = "left",
                 p("Principal Composant Analysis of PCR data from normal and tumor samples.",
                   br(), br(), "Add your data by importing a valid file.", br(), 
                   span(a("What's a valid file?", target="popup", onclick="window.open('validfile.html','popup','width=505,height=600'); return false;"))),

                 fileInput("means", "Choose a valid file",
                           accept = c(
                             "text/csv",
                             "text/comma-separated-values,text/plain",
                             ".csv",
                             ".xls",
                             ".xlsx")

                 ),
                 tags$hr(),

                 selectInput("var", 
                             label = "Choose a variable to display",
                             choices = c("Factor Map", "Variables Factor map (PCA)", 
                                          "Individuals Factor map (PCA)"),
                             selected = "Factor Map")
                 ),
    mainPanel(
      plotOutput("means"),
      textOutput("selected_var")

    )
  )
)

# Define server logic ----
server <- function(input, output) {


  output$means <- renderPlot({
    # input$file1 will be NULL initially. After the user selects
    # and uploads a file, it will be a data frame with 'name',
    # 'size', 'type', and 'datapath' columns. The 'datapath'
    # column will contain the local filenames where the data can
    # be found.
    inFile <- input$means

    if (is.null(inFile))
      return(NULL)

    means<-readXL(inFile$datapath, 
           rownames=TRUE, header=TRUE, na="",
           stringsAsFactors=TRUE)

    means.PCA<-means[, c("CTNNB1", "LIN28B", "MYC", "SMARCA4", "SOX9", "TERT", 
                         "TP53", "hsa.let.7b")]
    res<-PCA(means.PCA , scale.unit=TRUE, ncp=2, graph = FALSE)
    res.hcpc<-HCPC(res ,nb.clust=-1,consol=FALSE,min=3,max=10,graph=FALSE)

    if(input$var == "Factor Map")
    p<-res.hcpc<-HCPC(res ,nb.clust=-1,consol=FALSE,min=3,max=10,graph=TRUE)
    print(p)

    if(input$var == "Individuals Factor map (PCA)")
      p<-plot.PCA(res, axes=c(1, 2), choix="ind", habillage="none", col.ind="black", 
               col.ind.sup="blue", col.quali="magenta", label=c("ind", "ind.sup", "quali"),
               new.plot=TRUE)
    print(p)

    if(input$var == "Variables Factor map (PCA)")
    p<-plot.PCA(res, axes=c(1, 2), choix="var", new.plot=TRUE, col.var="black", 
             col.quanti.sup="blue", label=c("var", "quanti.sup"), lim.cos2.var=0)
    summary(res, nb.dec = 3, nbelements=10, nbind = 10, ncp = 3, file="")
    remove(means.PCA)
    print(p)

  })

  output$selected_var <- renderText({ 
    inFile <- input$means
    if (is.null(inFile))
      return(paste("Please load a valid file ..."))

    paste("You have selected : ", input$var)
  })

  }

# Run the app ----
shinyApp(ui = ui, server = server)
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