An example of using ggVis selectize with multiple=TRUE in Shiny.

ggVis_selectize_multiple.R

library(ggvis)
library(shiny)


#Example of Selectize, with Multiple = TRUE
ui = shinyUI(pageWithSidebar(
  div(),
  sidebarPanel(
    sliderInput("n", "Number of points", min = 1, max = nrow(mtcars),
                value = 10, step = 1),
    selectizeInput(
      'e2', 'Select Num Cylinders', choices = c(4,6,8), multiple = TRUE
    ),
    textOutput("ex_out")
    ),
  mainPanel(
    ggvisOutput("plot"),
    tableOutput("mtc_table")
  )
))


server = shinyServer(function(input, output, session) {

  #This is done to fix the colors for each level
  mtcars$cyl<-factor(mtcars$cyl, levels=c(4,6,8))
  
  
  # A reactive subset of mtcars
  mtc <- reactive({ 
    mtcars %>% filter(cyl %in% as.integer(input$e2))
  })
  
  output$ex_out <- renderPrint({as.integer(input$e2)    })

  # A simple visualisation. In shiny apps, need to register observers
  # and tell shiny where to put the controls
  mtc %>%
    ggvis(~wt, fill = ~cyl) %>% 
    group_by(cyl) %>%
    layer_densities() %>%
    bind_shiny("plot", "plot_ui")
    
  output$mtc_table <- renderTable({
    
    #Make the reactives wait until the minimum needed inputs have 
    #been entered.
    validate(
      need(input$e2, 'Please select at least one group')
    )
    mtc()[]
  })
})

shinyApp(ui = ui, server = server)

shiny_need_validate.R

### Second example, showing how validate and need can be used.
## This example is from Stack OVerflow. The idea of validate and need() is clearly illustrated

library(shiny)
library(ggplot2)
myData <- data.frame(group = sample(letters[1:4], 100, TRUE)
                     , cohort = sample(0:4, 100, TRUE)
                     , value = runif(100))
runApp(
  list(ui = fluidPage(
    column(4,
           checkboxGroupInput('group', 'Pick a group', choices = letters[1:4]),
           selectizeInput('cohort', 'Pick a cohort', choices = 0:4)),
    column(8, plotOutput('myplot'))
  )
  , server = function(input, output, session) {
    appData <- reactive({
      myData[myData$group %in% input$group & myData$cohort == input$cohort,]
    })
    output$myplot <- renderPlot({
      validate(
        need(input$group, 'Please select at least one group'),
        need(input$cohort > 0, 'Please choose a cohort greater than zero')
      )
      g <-ggplot(appData(),aes(x=group, y=value)) +
        stat_summary(fun.y=sum, geom="bar") +
        ggtitle(paste('cohort', input$cohort))
      g
    })
  }
  )