inst/src/tabs/bias/svr_bias.R

In LUMC/dgeAnalysis: dgeAnalysis

## GC bias plot
output[["gc_bias"]] <- renderPlotly({
  tryCatch({
    checkReload()
    
    ## Only plot if UI is loaded
    if(is.null(input$selectGC)) {
      break
    }
    
    ## Get input data
    index <- round(seq(1, nrow(inUse_deTab), length.out = 1000))
    plot_data <- bias_gc(inUse_deTab, input$selectGC)
    text <- 'paste("Gene:", gene,
                  "\nAverage Log2FC:", round(avgLog2FC, 2),
                  "\nPercentage:", round(get(y), 2),
                  "\nFDR:", round(FDR, 5))'
    
    ## Create plot
    toWebGL(
      ggplotly(
        scatter_plot(
          df = plot_data,
          x = input$selectGC,
          y = "avgLog2FC",
          text = text,
          group = "FDR",
          index = index,
          key = "gene",
          title = paste("Bias based on", input$selectGC),
          xlab = paste(input$selectGC, "(%)"),
          ylab = "Average Log2FC"
        ) + labs(color = "FDR"),
        source = "biasGC",
        tooltip = "text"
      ) %>% layout(dragmode = "select", clickmode = "event+select") %>%
        style(hoverinfo = "text")
    )
  }, error = function(err) {
    return(NULL)
  })
})

## GC bias table
output[["selected_biasgc"]] <- DT::renderDataTable({
  tryCatch({
    s <- event_data(event = "plotly_selected", source = "biasGC")
    if (is.null(s)) {
      throw()
    }
    
    DT::datatable(inUse_deTab[s$key, ], options = list(pageLength = 15, scrollX = TRUE))
  }, error = function(err) {
    return(DT::datatable(data.frame(c(
      "No data available in table"
    )), rownames = FALSE, colnames = ""))
  })
})

## Dropdown with all gc choices
output[["selectGC"]] <- renderUI({
  tryCatch({
    checkReload()
    selectInput(
      inputId = "selectGC",
      label = "Show bias based on:",
      choices = grep(
        'gc$',
        colnames(inUse_deTab),
        value = TRUE,
        ignore.case = TRUE
      )
    )
  }, error = function(err) {
    return(NULL)
  })
})

## feature length bias plot
output[["len_bias"]] <- renderPlotly({
  tryCatch({
    checkReload()
    
    ## Only plot if UI is loaded
    if(is.null(input$selectLength)) {
      break
    }
    
    ## Get input data
    index <- round(seq(1, nrow(inUse_deTab), length.out = 1000))
    plot_data <- bias_gc(inUse_deTab, input$selectLength)
    text <- 'paste("Gene:", gene,
                  "\nAverage Log2FC:", round(avgLog2FC, 2),
                  "\nLength:", round(get(x), 2),
                  "\nFDR:", round(FDR, 5))'
    
    ## Create plot
    toWebGL(
      ggplotly(
        scatter_plot(
          df = plot_data,
          x = input$selectLength,
          y = "avgLog2FC",
          text = text,
          group = "FDR",
          scale = TRUE,
          index = index,
          key = "gene",
          title = paste("Bias based on", input$selectLength),
          xlab = input$selectLength,
          ylab = "Average Log2FC"
        ) + labs(color = "FDR"),
        source = "biasLength",
        tooltip = "text"
      ) %>% layout(dragmode = "select", clickmode = "event+select") %>%
        style(hoverinfo = "text")
    )
  }, error = function(err) {
    return(NULL)
  })
})

## feature length bias table
output[["selected_biaslength"]] <- DT::renderDataTable({
  tryCatch({
    s <- event_data(event = "plotly_selected", source = "biasLength")
    if (is.null(s)) {
      throw()
    }
    
    DT::datatable(inUse_deTab[s$key, ], options = list(pageLength = 15, scrollX = TRUE))
  }, error = function(err) {
    return(DT::datatable(data.frame(c(
      "No data available in table"
    )), rownames = FALSE, colnames = ""))
  })
})

## dropdown with all length choices
output[["selectLength"]] <- renderUI({
  tryCatch({
    checkReload()
    selectInput(
      inputId = "selectLength",
      label = "Show bias based on:",
      choices = grep(
        'length$',
        colnames(inUse_deTab),
        value = TRUE,
        ignore.case = TRUE
      )
    )
  }, error = function(err) {
    return(NULL)
  })
})

## feature length bias plot
output[["geneStrand_bias"]] <- renderPlotly({
  tryCatch({
    checkReload()
    
    ## Get input data
    index <- round(seq(1, nrow(inUse_deTab), length.out = 1000))
    plot_data <- gene_strand(inUse_deTab)
    text <- 'paste("Strand:", strand,
                  "\nRegulation:", DE,
                  "\nGenes:", Freq,
                  "\nPercentage:", round(perc, 2))'
    
    ## Create plot
    ggplotly(
      bar_plot(
        df = plot_data,
        x = "DE",
        y = "perc",
        text = text,
        group = "strand",
        fill = "DE",
        facet = TRUE,
        plot = "ratio",
        title = "Gene strand ratio",
        xlab = "",
        ylab = "Percentage of genes"
      ),
      tooltip = "text"
    )
  }, error = function(err) {
    return(NULL)
  })
})

## INFORMATION BOXES

output[["gc_bias_info"]] <- renderUI({
  infoText <-
    "The GC bias plots are generated based on the mean change of the logFC on the Y-axis. The bias plots
        can only be used if an annotation is used to perform the analysis. If annotation values are
        is present, a column can be selected using a drop-down button. The columns must
        contain the text: 'GC', otherwise they will not be recognized as a suitable column
        for GC bias calculations."
  informationBox(infoText)
})

output[["len_bias_info"]] <- renderUI({
  infoText <-
    "The feature-length bias plots are generated from the mean change of the logFC on the Y-axis. The bias plots
        can only be used if an annotation is used to perform the analysis. If annotation values are
        is present, a column can be selected using a drop-down button. The columns must
        contain the text: 'length', otherwise they will not be recognized as a suitable column
        for length bias calculations."
  informationBox(infoText)
})

output[["geneStrand_info"]] <- renderUI({
  infoText <-
    "The gene strand bias plots are generated based on strand info (+ or -) and number
        genes (DE or not). It shows the distribution of genes between strands. The Gene Strand Plot can only
        be generated using the gene strand information annotation file."
  informationBox(infoText)
})