下面是我的答案的修改（一般化）版本，它读入csv文件并允许将其保存回磁盘。

library(DT)
library(shiny)

# Prepare mock data
wd <- getwd()
Factors <- c("Experiment", "Condition", "Replicate", "Genotype")
ExpMapNm <- "dummy_data"
ExpMapPath <- paste0(wd, "/", ExpMapNm, ".csv")
ExpMap <- data.frame(Experiment = "Exp1",
                     Sample = paste0("Sample", 1:20),
                     Condition = as.character(sapply(c("Treated", "Mock"), function(x) { rep(x, 10) })),
                     Genotype = as.character(sapply(c("KO", "WT"), function(x) { rep(x, 5) })),
                     Replicate = 1:5)
FactorsList <- setNames(lapply(Factors, function(x) { unique(ExpMap[[x]]) }), Factors)

if (!file.exists(ExpMapPath)) { write.csv(ExpMap, ExpMapPath, row.names = FALSE) }

ui <- fluidPage(
  shiny::actionButton("saveBtn", "Save"),
  DT::dataTableOutput(outputId = 'my_table'),
)

server <- function(input, output, session) {
  
  resultDF <- displayHTMLDF <- initHTMLDF <- initData <- read.csv(ExpMapPath)
  
  dropdownCols <- names(initData)[3:5]
  dropdownIDs <- setNames(lapply(dropdownCols, function(x){paste0(x, seq_len(nrow(initData)))}), dropdownCols)
  
  for(dropdownCol in dropdownCols){
    colDropdownIDs <- dropdownIDs[[dropdownCol]]
    initHTMLDF[[dropdownCol]] <- sapply(seq_along(colDropdownIDs), function(i){as.character(selectInput(inputId = colDropdownIDs[i], label = "", choices = unique(initData[[dropdownCol]]), selected = initData[[dropdownCol]][i]))})
  }
  
  reactiveHTMLDF <- reactive({
    for(dropdownCol in dropdownCols){
      colDropdownIDs <- dropdownIDs[[dropdownCol]]
      displayHTMLDF[[dropdownCol]] <- sapply(seq_along(colDropdownIDs), function(i){as.character(selectInput(inputId = colDropdownIDs[i], label = "", choices = unique(initData[[dropdownCol]]), selected = input[[colDropdownIDs[i]]]))})
    }
    return(displayHTMLDF)
  })
  
  reactiveResultDF <- reactive({
    for(dropdownCol in dropdownCols){
      colDropdownIDs <- dropdownIDs[[dropdownCol]]
      resultDF[[dropdownCol]] <- sapply(seq_along(colDropdownIDs), function(i){input[[colDropdownIDs[i]]]})
    }
    return(resultDF)
  })
  
  output$my_table = DT::renderDataTable({
    DT::datatable(
      initHTMLDF, escape = FALSE, selection = 'none', rownames = FALSE,
      options = list(paging = FALSE, ordering = FALSE, scrollx = TRUE, dom = "t",
                     preDrawCallback = JS('function() { Shiny.unbindAll(this.api().table().node()); }'),
                     drawCallback = JS('function() { Shiny.bindAll(this.api().table().node()); } ')
      )
    )
  }, server = TRUE)
  
  my_table_proxy <- dataTableProxy(outputId = "my_table", session = session)
  
  observeEvent({sapply(unlist(dropdownIDs), function(x){input[[x]]})}, {
    replaceData(proxy = my_table_proxy, data = reactiveHTMLDF(), rownames = FALSE) # must repeat rownames = FALSE see ?replaceData and ?dataTableAjax
  }, ignoreInit = TRUE)
  
  shiny::observeEvent(input$saveBtn, {
    write.csv(reactiveResultDF(), ExpMapPath, row.names = FALSE)
    stopApp()
  })
}

shinyApp(ui = ui, server = server)

您可能需要调整一些东西以满足您的需要，但是，它们并不需要显示原理。

我想我现在解决了，非常感谢ismirsehregal！
澄清我的原始问题：

• 多水平因子（Fact 2）列应为下拉选择。
• 非因子（Others）列应该允许自由的单元格编辑。（下面的代码有点复杂，因为我也很难覆盖单元格中单个水平因子或Fact 1的最终手动编辑。）

所提出的解决方案的问题是，从多水平因子列中进行的任何选择都会将之前的任何自由编辑还原为“其他”。为了解决此问题，我重写了代码，以便在定义了每列中允许的编辑类型后，由同一行代码处理这两个编辑。

library(DT)
library(shiny)

# Prepare mock data
wd <- getwd()
Factors <- c("Experiment", "Condition", "Replicate", "Genotype")
ExpMapNm <- "dummy_data"
ExpMapPath <- paste0(wd, "/", ExpMapNm, ".csv")
ExpMap <- data.frame(Experiment = "Exp1",
                     Sample = paste0("Sample", 1:20),
                     Condition = as.character(sapply(c("Treated", "Mock"), function(x) { rep(x, 10) })),
                     Genotype = as.character(sapply(c("KO", "WT"), function(x) { rep(x, 5) })),
                     Replicate = 1:5)
FactorsList <- setNames(lapply(Factors, function(x) { unique(ExpMap[[x]]) }), Factors)

if (!file.exists(ExpMapPath)) { write.csv(ExpMap, ExpMapPath, row.names = FALSE) }

ui <- fluidPage(
  shiny::titlePanel(ExpMapNm), # This is the name of the table
  shiny::mainPanel(shiny::br(),
                   shiny::actionButton("saveBtn", "Save"),
                   DT::dataTableOutput('my_table'))
)
server <- function(input, output, session) {
  initData <- read.csv(ExpMapPath)
  
  tst <- sapply(FactorsList, length)
  Fact1 <- Factors[which(tst == 1)]
  Fact2 <- Factors[which(tst > 1)]
  Others <- colnames(initData)[which(!colnames(initData) %in% Factors)]
  Editables <- c(Others, Fact2)
  nr <- nrow(initData)
  OtherIDs <- setNames(lapply(Others, function(x) { paste0(x, seq_len(nr))} ), Others)
  Fact2IDs <- setNames(lapply(Fact2, function(x) { paste0(x, seq_len(nr))} ), Fact2)
  AllIDs <- append(OtherIDs, Fact2IDs)
  for (Fact in Fact1) {
    # (Since the table can be manually edited too, we want to make sure to correct any typos in our single level factor columns)
    initData[[Fact]] <- FactorsList[[Fact]]
  }
  # ... before creating 3 copies of that datatable:
  resultDF <- displayHTMLDF <- initHTMLDF <- initData
  # initHTMLDF
  for (Oth in Others) {
    IDs <- OtherIDs[[Oth]]
    initHTMLDF[[Oth]] <- sapply(seq_along(IDs), function(i) {
      val <- initData[[Oth]][i]
      return(as.character(textInput(IDs[i], "", val)))
    })
  }
  for (Fact in Fact2) {
    IDs <- Fact2IDs[[Fact]]
    lvls <- FactorsList[[Fact]]
    initHTMLDF[[Fact]] <- sapply(seq_along(IDs), function(i) {
      val <- initData[[Fact]][i]
      dflt <- c(NA, val)[(val %in% lvls)+1] # If the current value is not a valid level, revert to NA
      return(as.character(selectInput(IDs[i], "", c(lvls, NA), dflt)))
    })
  }
  # displayHTMLDF
  reactiveHTMLDF <- reactive({
    for (Col in Editables) {
      IDs <- AllIDs[[Col]]
      if (Col %in% Others) {
        displayHTMLDF[[Col]] <- sapply(seq_along(IDs), function(i) {
          val <- initData[[Col]][i]
          return(as.character(textInput(IDs[i], "", input[[IDs[i]]])))
        })  
      } else {
        lvls <- FactorsList[[Col]]
        displayHTMLDF[[Col]] <- sapply(seq_along(IDs), function(i) { as.character(selectInput(IDs[i], "", lvls, input[[IDs[i]]])) })
      }
    }
    return(displayHTMLDF)
  })
  # resultDF
  reactiveResultDF <- reactive({
    for (Col in Editables) {
      IDs <- AllIDs[[Col]]
      resultDF[[Col]] <- sapply(seq_along(IDs), function(i) { input[[IDs[i]]] })
    }
    return(resultDF)
  })
  # Let's make sure we explicitly link row.names in multiple calls below 
  rwNms <- FALSE
  #
  output$my_table = DT::renderDataTable({
    DT::datatable(
      initHTMLDF, escape = FALSE, selection = "none", rownames = rwNms,
      editable = list(target = "cell", disable = list(columns = match(Fact1, colnames(initData))-1)), # Factors with 1 level should not be editable; indices appear to start at 0 (JS convention?)
      options = list(paging = FALSE, ordering = FALSE, scrollx = TRUE, dom = "t",
                     preDrawCallback = JS('function() { Shiny.unbindAll(this.api().table().node()); }'),
                     drawCallback = JS('function() { Shiny.bindAll(this.api().table().node()); } ')
      )
    )
  }, server = TRUE)
  my_table_proxy <- dataTableProxy("my_table", session)
  observeEvent({ sapply(unlist(AllIDs), function(x) { input[[x]] }) }, {
    replaceData(proxy = my_table_proxy, data = reactiveHTMLDF(), rownames = rwNms) # must repeat rownames = FALSE see ?replaceData and ?dataTableAjax
  }, ignoreInit = TRUE)
  shiny::observeEvent(input$saveBtn, {
    write.csv(reactiveResultDF(), ExpMapPath, row.names = FALSE)
    stopApp()
  })
}
print(shiny::shinyApp(ui, server, options = list(launch.browser = TRUE)))