Update PFCdevApp.qmd

PFCdevApp.qmd

@@ -55,7 +55,11 @@ Spatial data
 </p>
 
 <p style="font-size: 20px; text-align: justify;">
-We collected the whole brain stereo-seq datasets of P1 and Adult mice from [(Han et al., Neuron, 2025)](https://doi.org/10.1016/j.neuron.2025.02.015, extracted and analyzed the PFC brain region. Users can browse the following content through the spatial page:
+We collected the whole brain stereo-seq datasets of P1 and Adult mice from [(Han et al., Neuron, 2025)](https://doi.org/10.1016/j.neuron.2025.02.015
+        
+        
+        
+        , extracted and analyzed the PFC brain region. Users can browse the following content through the spatial page:
 </p>
 
 - Spatial Clustering: Select different cell subtypes to view their spatial distribution
@@ -224,10 +228,21 @@ output$gene_plot <- renderPlot({
 
 
 output$vln_plot <- renderPlot({
-  VlnPlot(seu(), features = input$gene, group.by = input$celltype,
-          col = col_cluster[[input$celltype]]) +
-    NoLegend() +
-    labs(x="")
+  FeaturePlot(
+    seu(),
+    features = input$gene,
+    reduction = 'umap',
+    split.by = "orig.ident",
+    ncol=4,
+    order = T,
+    pt.size = 0.5
+  ) &
+    theme_bw(base_size = 15) &
+    theme(panel.grid = element_blank(), plot.title = element_text(hjust = 0.5),
+          strip.text = element_text(size = 20, face = "bold"),
+          legend.position = c(0.1,0.25)) &
+    coord_fixed() &
+    scale_color_gradientn(colours = c("lightblue3", "lightblue", "white", "red", "red4"), limits=c(0,2), breaks=c(0,2), na.value = "red4")
 })
 ```