geposanui/R/filters.R

# Construct UI for the filter editor.
filters_ui <- function(id) {
  verticalLayout(
    h3("Filter criteria"),
    selectInput(
      NS(id, "method"),
      "Filter method",
      choices = list(
        "Percentile" = "percentile",
        "Cut-off score" = "score",
        "Maximum number of genes" = "rank",
        "None" = "none"
      )
    ),
    tabsetPanel(
      id = NS(id, "sliders"),
      type = "hidden",
      tabPanelBody(
        value = "percentile",
        sliderInput(
          NS(id, "percentile"),
          label = "Minimum percentile",
          post = "%",
          min = 0,
          max = 100,
          step = 1,
          value = 95
        )
      ),
      tabPanelBody(
        value = "score",
        sliderInput(
          NS(id, "score"),
          label = "Cut-off score",
          post = "%",
          min = 0,
          max = 100,
          step = 1,
          value = 75
        )
      ),
      tabPanelBody(
        value = "rank",
        sliderInput(
          NS(id, "rank"),
          label = "Maximum rank",
          min = 0,
          max = 2000,
          step = 10,
          value = 1000
        )
      ),
      tabPanelBody(
        value = "none"
      )
    ),
    sliderInput(
      NS(id, "distance"),
      label = "Distance to telomeres",
      post = " Mbp",
      min = 0,
      max = 150,
      value = c(0, 150)
    )
  )
}

# Construct server for the filter editor.
#
# @param results The results to be filtered.
#
# @return A reactive containing the filtered results.
filters_server <- function(id, results) {
  moduleServer(id, function(input, output, session) {
    observeEvent(input$method, {
      updateTabsetPanel(session, "sliders", selected = input$method)
    })

    reactive({
      results <- results()

      results_prefiltered <- if (input$method == "percentile") {
        n_ranks <- nrow(results)
        results[rank <= (1 - (input$percentile / 100)) * n_ranks]
      } else if (input$method == "score") {
        results[score >= input$score / 100]
      } else if (input$method == "rank") {
        results[rank <= input$rank]
      } else {
        results
      }

      results_prefiltered[
        distance >= 1000000 * input$distance[1] &
          distance <= 1000000 * input$distance[2]
      ]
    })
  })
}