Allow using all species for processing

process.R

@@ -7,16 +7,10 @@ library(rlog)
 #' account when regarding them as TPE-OLD candidates.
 #'
 #' @param input Data from [`load_input()`].
-process_input <- function(input) {
+#' @param species_ids IDs of species to include in the analysis.
+process_input <- function(input, species_ids) {
     results <- data.table(gene = input$genes$id)
 
-    # Exclude species with naturally or artificially short chromosomes as well
-    # as non-replicatively aging species.
-    species_ids <- input$species[
-        median_distance >= 7500000 & group == "replicative",
-        id
-    ]
-
     gene_ids <- input$genes[, id]
     gene_count <- length(gene_ids)
 

scatter_plot.R

@@ -5,18 +5,12 @@ library(ggplot2)
 #'
 #' @param input Input data from [`load_input()`].
 #' @param results Results from [`process_input()`].
-scatter_plot <- function(gene_ids, input, results) {
+#' @param species Species to be displayed.
+scatter_plot <- function(gene_ids, input, results, species) {
     if (length(gene_ids) < 1) {
         return(ggplot())
     }
 
-    # Exclude species with naturally or artificially short chromosomes as well
-    # as non-replicatively aging species.
-    # TODO: Sync with process_input().
-    species <- input$species[
-        median_distance >= 7500000 & group == "replicative"
-    ]
-
     species_ids <- species[, id]
 
     data <- merge(
@@ -60,5 +54,6 @@ scatter_plot <- function(gene_ids, input, results) {
                 shape = in_cluster
             ),
             size = 5
-        )
+        ) +
+        theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1))
 }

server.R

@@ -7,14 +7,65 @@ source("process.R")
 source("scatter_plot.R")
 source("util.R")
 
-data <- run_cached("input", load_input, "input")
-results <- run_cached("results", process_input, data)
-merged <- merge(results, data$genes, by.x = "gene", by.y = "id")
-setorder(merged, -cluster_length)
+# Initialize global static data
+
+inputs <- run_cached("input", load_input, "input")
+
+#' All species excluding species with naturally or artificially short
+#' chromosomes.
+species_qualified <- inputs$species[median_distance >= 7500000]
+
+#' All known replicatively aging species with long enough chromosomes.
+species_replicative <- species_qualified[group == "replicative"]
+
+#' Results computed from [`species_qualified`].
+results_all <- run_cached(
+    "results_all",
+    process_input,
+    inputs,
+    species_qualified[, id]
+)
+
+#' Results computed from [`species_replicative`].
+results_replicative <- run_cached(
+    "results_replicative",
+    process_input,
+    inputs,
+    species_replicative[, id]
+)
+
+# Add gene information to results for display.
+
+results_all <- merge(
+    results_all,
+    inputs$genes,
+    by.x = "gene",
+    by.y = "id"
+)
+
+results_replicative <- merge(
+    results_replicative,
+    inputs$genes,
+    by.x = "gene",
+    by.y = "id"
+)
+
+# Order results by cluster length descendingly.
+# TODO: Once other methods have been added, this has to be dynamic.
+setorder(results_all, -cluster_length)
+setorder(results_replicative, -cluster_length)
 
 server <- function(input, output) {
-    filtered <- reactive({
-        merged[
+    #' This expression applies all user defined filters to the available
+    #' results.
+    results <- reactive({
+        results <- if (input$species == "all") {
+            results_all
+        } else {
+            results_replicative
+        }
+
+        results[
             cluster_length >= input$length &
                 cluster_mean >= input$range[1] * 1000000 &
                 cluster_mean <= input$range[2] * 1000000
@@ -23,7 +74,7 @@ server <- function(input, output) {
 
     output$genes <- renderDT({
         datatable(
-            filtered()[, .(.I, name, chromosome, cluster_length, cluster_mean)],
+            results()[, .(.I, name, chromosome, cluster_length, cluster_mean)],
             rownames = FALSE,
             colnames = c(
                 "Rank",
@@ -37,7 +88,16 @@ server <- function(input, output) {
     })
 
     output$scatter <- renderPlot({
-        gene_ids <- filtered()[input$genes_rows_selected, gene]
-        scatter_plot(gene_ids, data, results)
+        results <- results()
+
+        gene_ids <- results[input$genes_rows_selected, gene]
+
+        species <- if (input$species == "all") {
+            species_qualified
+        } else {
+            species_replicative
+        }
+
+        scatter_plot(gene_ids, inputs, results, species)
     })
 }

ui.R

@@ -7,6 +7,14 @@ ui <- fluidPage(
         position = "right",
         sidebarPanel(
             h3("Candidate selection"),
+            selectInput(
+                "species",
+                "Species to include",
+                choices = list(
+                    "All qualified" = "all",
+                    "Replicatively aging" = "replicative"
+                )
+            ),
             sliderInput(
                 "range",
                 "Gene position (Mbp)",