Shiny Plot Region Based on Number of Plot

Introduction

In this article, we will explore how to create a shiny plot region that adapts its size based on the number of plots. This can be particularly useful when dealing with large datasets or when users need to customize the layout of their plots.

Problem Statement

The problem at hand is to create a UI plot width that changes dynamically based on the number of plots in our dataset. We are given a sample dataset dat containing four genes (A, B, C, D) and six variables (sample1, sample2, etc.) per gene.

Current Solution

The provided solution uses the renderPlot function to generate plots for each row in the data based on the selected gene. The width of the plot region is set dynamically using the uiOutput("boxplot_ui") function, which takes into account the number of rows in the data.

However, this approach has a limitation: when dealing with large datasets, it can lead to performance issues and errors due to the way R handles matrix indexing and plotting.

Alternative Solution

To overcome these limitations, we will use the renderUI function to create an adaptive plot region that adjusts its size based on the number of plots. We will also introduce some additional logic to handle cases where the number of rows is null.

Code

library(shiny)
library(shinydashboard)

dat = data.frame(gene =c(rep("A",3), rep("B",6), rep("C",1), rep("D",10)), sample1 = runif(12, 0, 50), 
                sample2 = runif(12, 0, 50), sample3 = runif(12, 0, 50), sample4 = runif(12, 0, 50))

ui <- dashboardPage(
  dashboardHeader(title = "Title", titleWidth = "300px"),
  dashboardSidebar(
    textInput(inputId = "GoI", label = "Select gene (A,B,C,D)", value ="A")
  ),
  dashboardBody(
    tabsetPanel(
      tabPanel("Differential Variability", uiOutput("boxplot_ui"))
    )
  )
)

server <- function(input, output) {
  output$boxplot <- renderPlot({
    dataGoI = dat[dat$gene == input$GoI,]
    i = nrow(dataGoI)
    g = c(0, 0, 0, 1, 1, 1)

    if (i > 5) {
      if (i == 6) {
        zones = matrix(c(1:6), nrow=2, byrow = T)
      } else if (i == 7) {
        zones = matrix(c(1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6), nrow=2, byrow = T)
      } else if (i == 8) {
        zones = matrix(c(1:8), nrow=2, byrow = T)
      } else if (i == 9) {
        zones = matrix(c(rep(1:5, each=4), rep(6:9,each=5)), nrow = 2, byrow = T)
      } else {
        zones = matrix(c(1:10), nrow=2, byrow = T)
      }
    }

    if (i <= 5) {
      par(mfrow = c(1, i))
      for(j in 1:i){
        boxplot(as.numeric(dataGoI[j,2:7]) ~ g)
      }
    } else {
      layout(zones)
      for(j in 1:i){
        boxplot(as.numeric(dataGoI[j,2:7]) ~ g)
      }
    }
  })

  output$boxplot_ui <- renderUI({
    plotOutput("boxplot", width = ifelse(nrow(dat[dat$gene == input$GoI,]), nrow(dat[dat$gene == input$GoI,])*100, 500))
  })
}

shinyApp(ui = ui, server = server)

Conclusion

In this article, we explored how to create a shiny plot region that adapts its size based on the number of plots. We introduced some additional logic to handle cases where the number of rows is null and used the renderUI function to create an adaptive plot region.

By using this approach, you can create more flexible and dynamic UI plots that adapt to your dataset’s needs.

Last modified on 2024-11-12