How to build interactive apps with Bioconductor?

Setup Your Environment

• Install R and RStudio on your computer. These are essential tools for using Bioconductor effectively.

 

• Install Bioconductor by running the following commands in R:

    \`\`\`r
    if (!requireNamespace("BiocManager", quietly = TRUE))
        install.packages("BiocManager")
    BiocManager::install(version = "3.17")
    \`\`\`
    

Choose Appropriate Bioconductor Packages

• Determine the focus of your application, such as genomics, transcriptomics, or proteomics.

 

• Explore Bioconductor packages that align with your application goals. Use BiocManager to install necessary packages:

    \`\`\`r
    BiocManager::install("DESeq2") # for differential expression analysis
    BiocManager::install("GenomicRanges") # for working with genomic ranges
    \`\`\`
    

Create a New Shiny Application

• Open RStudio and start a new Shiny project by going to File > New Project > New Directory > Shiny Web Application.

 

• Name your application and choose a directory to store files.

Design the User Interface

• Use the ui.R file (or the ui section of an app.R file) to build the layout. Use Shiny widgets to create inputs, such as sliders, text boxes, and file uploads.

    \`\`\`r
    shinyUI(fluidPage(
        titlePanel("Bioconductor App"),
        sidebarLayout(
            sidebarPanel(
                fileInput("file", "Upload Data File")
            ),
            mainPanel(plotOutput("plot"))
        )
    ))
    \`\`\`
    

Implement Server Logic

• Write the processing code in the server.R file (or the server section of an app.R file). This code will respond to user inputs and update outputs like charts and tables.

    \`\`\`r
    shinyServer(function(input, output) {
        output$plot <- renderPlot({
            # Read in data using Bioconductor functionality
            if(is.null(input$file)) return(NULL)
            data <- read.csv(input$file$datapath)
            # Example: visualize with a plot
            plot(data)
        })
    })
    \`\`\`
    

Integrate Bioconductor Data Processing

• In your server.R file, incorporate Bioconductor analyses, like genomic analysis or visualization, into your reactive elements.

    \`\`\`r
    shinyServer(function(input, output) {
        output$plot <- renderPlot({
            req(input$file)
            data <- read.csv(input$file$datapath)
            # Example: Use DESeq2 for differential expression analysis
            dds <- DESeqDataSetFromMatrix(countData = data, colData = colData, design = ~ condition)
            dds <- DESeq(dds)
            plotMA(dds, ylim = c(-2, 2))
        })
    })
    \`\`\`
    

Test and Deploy Your Application

• Test the app locally by clicking the 'Run App' button in RStudio to ensure everything operates as expected.

 

• Deploy your app online using ShinyApps.io or a local server setup, which involves creating an account on ShinyApps.io and deploying through RStudio.