Update PFCdevApp.qmd

PFCdevApp.qmd

@@ -286,9 +286,35 @@ plotOutput('p1_subtype_plot')
 #### Column
 
 ```{r}
-plotOutput('p1_gene_plot')
+plotOutput('p1_geneplot')
 ```
 
+```{r}
+#| context: server
+
+output$p1_geneplot <- renderPlot({
+  gene_i <- input$sp_gene
+  data <- data.frame(
+    x = sp_p1$x_rotated, y = sp_p1$y_rotated,
+    gene = scale(sp_p1@assays$RNA$counts[gene_i,])
+    )
+  data$gene[data$gene<0] <- 0
+  data$gene[data$gene>3] <- 3
+  color <- col_cluster[["gene"]]
+  ggplot(data, aes(x=x, y=y, color=gene)) +
+    geom_point(size=2) +
+    scale_color_gradientn(colours = color, na.value = "lightgray",
+                          limits = c(0,3), 
+                          breaks = c(0,3)) +
+    coord_fixed() +
+    theme_void()+
+    theme(legend.position = c(0.9,0.2), legend.title = element_blank(),
+          plot.title = element_text(hjust = 0.5)) +
+    labs(title=paste("P1", gene_i))
+})
+```
+
+
 #### Column
 
 ```{r}
@@ -298,9 +324,33 @@ plotOutput('p77_subtype_plot')
 #### Column
 
 ```{r}
-plotOutput('p77_gene_plot')
+plotOutput('p77_geneplot')
 ```
 
+```{r}
+#| context: server
+
+output$p77_geneplot <- renderPlot({
+  gene_i <- input$sp_gene
+  data <- data.frame(
+    x = sp_p77$x_rotated, y = sp_p77$y_rotated,
+    gene = scale(sp_p77@assays$RNA$counts[gene_i,])
+    )
+  data$gene[data$gene<0] <- 0
+  data$gene[data$gene>3] <- 3
+  color <- col_cluster[["gene"]]
+  ggplot(data, aes(x=x, y=y, color=gene)) +
+    geom_point(size=0.8) +
+    scale_color_gradientn(colours = color, na.value = "lightgray",
+                          limits = c(0,3), 
+                          breaks = c(0,3)) +
+    coord_fixed() +
+    theme_void() +
+    theme(legend.position = c(0.9,0.2), legend.title = element_blank(),
+          plot.title = element_text(hjust = 0.5)) +
+    labs(title=paste("P77", gene_i))
+})
+```
 
 
 
@@ -365,29 +415,6 @@ output$p1_subtype_plot <- renderPlot({
 })
 
 
-output$p1_gene_plot <- renderPlot({
-  data <- data.frame(
-    x = sp_p1$x_rotated, y = sp_p1$y_rotated,
-    gene = scale(sp_p1@assays@RNA@counts[input$sp_gene,])
-    )
-  data$gene[data$gene<0] <- 0
-  data$gene[data$gene>3] <- 3
-  color <- col_cluster[["gene"]]
-  ggplot(data, aes(x=x, y=y, color=gene)) +
-    geom_point(size=2) +
-    scale_color_gradientn(colours = color, na.value = "lightgray",
-                          limits = c(0,3), 
-                          breaks = c(0,3)) +
-    coord_fixed() +
-    #ggdark::dark_theme_void() +
-    theme_void()+
-    theme(legend.position = c(0.9,0.2), legend.title = element_blank(),
-          plot.title = element_text(hjust = 0.5)) +
-    labs(title=paste("P1", input$sp_gene))
-})
-
-
-
 output$p77_subtype_plot <- renderPlot({
   data <- P77_cell2loc
   data$`L5 IT`[data$`L5 IT`<0.25] <- 0
@@ -413,28 +440,6 @@ output$p77_subtype_plot <- renderPlot({
           plot.title = element_text(hjust = 0.5)) +
     labs(title=paste("P77",subtype_i))
 })
-
-
-output$p77_gene_plot <- renderPlot({
-  data <- data.frame(
-    x = sp_p77$x_rotated, y = sp_p77$y_rotated,
-    gene = scale(sp_p77@assays$RNA$counts[input$sp_gene,])
-    )
-  data$gene[data$gene<0] <- 0
-  data$gene[data$gene>3] <- 3
-  color <- col_cluster[["gene"]]
-  ggplot(data, aes(x=x, y=y, color=gene)) +
-    geom_point(size=0.8) +
-    scale_color_gradientn(colours = color, na.value = "lightgray",
-                          limits = c(0,3), 
-                          breaks = c(0,3)) +
-    coord_fixed() +
-    #ggdark::dark_theme_void() +
-    theme_void() +
-    theme(legend.position = c(0.9,0.2), legend.title = element_blank(),
-          plot.title = element_text(hjust = 0.5)) +
-    labs(title=paste("P77", input$sp_gene))
-})
 ```