added violin plot to visualize gene expression of the individual clusters; cosmetics

sc_workflow/sc_apps/clustering_explorer

@@ -152,6 +152,7 @@ app <- shinyApp(
                     tabPanel("TSNE",
                     radioButtons("vis_method", label = "", choiceNames = c("expression", "cluster"), choiceValues = c("expression", "cluster"), inline = TRUE, selected = "expression"),
                     plotOutput(outputId = "tsne", height = "auto")),
+                    tabPanel("Violin plot", plotOutput(outputId = "violin", height = "auto")),
                     tabPanel("Heatmap", plotOutput(outputId = "heatmap", height = 800))
                 )
             )
@@ -307,6 +308,27 @@ app <- shinyApp(
 
 
 
+
+        plotting_violin <- function(data) {
+
+            plot_rows <- if (length(selected_samples()) > 1) { floor(length( selected_samples() )/2) } else { as.numeric(1) }
+
+            lapply(append(selected_samples(), "legend"), function(x){
+                data %>%
+                filter(str_detect(cluster_name, x)) %>%
+                ggplot(aes(as.factor(cluster_num), score, fill = as.factor(cluster_num))) +
+                geom_violin() +
+                theme(legend.position="none") +
+                xlab("") +
+                ggtitle(paste(x))
+            }) %>% grid.arrange(grobs = ., nrow = plot_rows)
+        }
+
+        output$violin <- renderPlot({ plotting_violin(outHeatmapData()) },
+            height = function(){400* if (length(selected_samples()) > 1) { floor(length( selected_samples() )/2) } else { as.numeric(1.5) }})
+
+
+
         plotting_tsne <- function(data, vis_mode){
 
             plot_rows <- if (length(selected_samples()) > 1) { floor(length( selected_samples() )/2) } else { as.numeric(1) }
@@ -319,7 +341,8 @@ app <- shinyApp(
                             geom_point(size = 0.2) +
                             guides(colour = guide_legend(override.aes = list(size=5), title="cluster")) +
                             coord_fixed() +
-                            ggtitle(x)
+                            ggtitle(x) #+
+                            #geom_encircle(aes(x = tSNE_1, y = tSNE_2), subset_data, expand = 0.01)
 
                 }else if (vis_mode == "expression"){
                 data[ which(data$cluster_name == x),] %>%
@@ -335,9 +358,9 @@ app <- shinyApp(
         }
 
         output$tsne <- renderPlot({
-            ph <-
-            plot_to_draw <- plotting_tsne(outHeatmapData(), input$vis_method)
-            plot_to_draw
+            plotting_tsne(outHeatmapData(), input$vis_method)
+            # plot_to_draw <- plotting_tsne(outHeatmapData(), input$vis_method)
+            # plot_to_draw
 
         }, height = function(){400* if (length(selected_samples()) > 1) { floor(length( selected_samples() )/2) } else { as.numeric(1.5) }})