diff --git a/app.R b/app.R
index 487c360..93d9167 100644
--- a/app.R
+++ b/app.R
@@ -34,8 +34,8 @@ options(DT.options = list(scrollX = TRUE))
 # Gitea access token
 access_token = read_lines("~/secret-token")
 
-gene_url = "https://git.tunstall.in/api/v1/repos/tanu/fellowship_dcdf/raw/tb_data_fc/dashboard/list_unique_missense_genes.csv"
-missense_gene_url = "https://git.tunstall.in/api/v1/repos/tanu/fellowship_dcdf/raw/tb_data_fc/dashboard/missense_genes_params.csv"
+gene_url = "https://git.tunstall.in/api/v1/repos/tanu/fellowship_dcdf/raw/tb_data_fc/data_dashboard/list_unique_missense_genes.csv"
+missense_gene_url = "https://git.tunstall.in/api/v1/repos/tanu/fellowship_dcdf/raw/tb_data_fc/data_dashboard/missense_genes_params.csv"
 alphafold_url = "https://alphafold.ebi.ac.uk/files/"
 
 genes=read_csv(paste0(gene_url,"?token=",access_token))
@@ -229,7 +229,10 @@ server <- function(input, output) {
                   #"<strong>PROVEAN: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"provean_score"]), "<br/>",
                   "<strong>PROVEAN Outcome: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"provean_outcome"]), "<br/>",
                   "<strong>RSA: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"rsa"]), "<br/>",
-                  "<strong>Residue Depth: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"rd_values"]), "<br/>"
+                  "<strong>Residue Depth: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"rd_values"]), "<br/>",
+                  "<strong>Total Samples: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"total_sample_count"]), "<br/>",
+                  "<strong>Distinct Lineages: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"distinct_lineage_count"]), "<br/>"
+                  
       )
       )
       
@@ -286,7 +289,7 @@ server <- function(input, output) {
                                   opacity = 0.2
                      )
         ) %>%
-        addSelection(type="spacefill",
+        addSelection(type="ball+stick", #spacefill
                      param = list(name = "all_mutations",
                                   color="orange",
                                   sele = mutations
@@ -304,7 +307,7 @@ server <- function(input, output) {
                                   opacity = 0.2
                      )
         ) %>%
-        addSelection(type="spacefill",
+        addSelection(type="ball+stick", #spacefill
                      param = list(name = "all_mutations",
                                   color="orange",
                                   sele = mutations
@@ -318,3 +321,4 @@ server <- function(input, output) {
 # Run the application 
 shinyApp(ui = ui, server = server)
 
+
diff --git a/server.R b/server.R
new file mode 100644
index 0000000..1a4a43a
--- /dev/null
+++ b/server.R
@@ -0,0 +1,238 @@
+library(shiny)
+library(shinyjs)
+library(shinydashboard)
+#library("wesanderson") # ayyyy lmao hipster af
+library(dplyr)
+library(DT)
+library(ggplot2)
+library(grid) # for the info box
+library(plotly)
+library(shinycssloaders)
+library(NGLVieweR)
+library(httr)
+library(readr)
+library(RCurl)
+
+shinyServer(function(input, output) {
+  
+  output$distPlot <- renderPlot({
+    # generate bins based on input$bins from ui.R
+    x    <- faithful[, 2]
+    bins <- seq(min(x), max(x), length.out = input$bins + 1)
+    
+    # draw the histogram with the specified number of bins
+    hist(x, breaks = bins, col = 'darkgray', border = 'white',
+         xlab = 'Waiting time to next eruption (in mins)',
+         main = 'Histogram of waiting times')
+  })
+  ### NGLViewer ####
+  # Structure Viewer WebGL/NGLViewR window
+  output$structure <- renderNGLVieweR({
+    selected_gene=input$gene
+    ngl_gene=as.character(genes[genes$Gene==selected_gene,"PDB"])
+    NGLVieweR(ngl_gene) %>%
+      addRepresentation("cartoon",
+                        param = list(name = "cartoon",
+                                     color="tan",
+                                     #colorScheme = "bfactor",
+                                     opacity = 1
+                        )
+      ) %>%
+      stageParameters(backgroundColor = "white") %>%
+      setQuality("high") %>%
+      setFocus(0) %>%
+      setSpin(FALSE)
+  })
+  output$af_structure <- renderNGLVieweR({
+    selected_af_gene=input$gene
+    ngl_af_gene=as.character(genes[genes$Gene==selected_af_gene,"AF_PDB"])
+    
+    #af_pdb=cat(content(GET(paste0(alphafold_url,"AF-",ngl_af_gene,"-F1-model_v4.pdb")), as="text"), "\n")
+    af_pdb=content(GET(paste0(alphafold_url,"AF-",ngl_af_gene,"-F1-model_v4.pdb")), as="text")
+    #print(af_pdb)
+    #ngl_pdb_file=paste0(load_dir, "Data/", ngl_drug, '/output/depth/', ngl_gene, '_complex.pdb')
+    NGLVieweR(af_pdb, format="pdb") %>%
+      addRepresentation("cartoon",
+                        param = list(name = "cartoon",
+                                     #color="tan"
+                                     colorScheme = "bfactor",
+                                     opacity = 1
+                        )
+      ) %>%
+      stageParameters(backgroundColor = "white") %>%
+      setQuality("high") %>%
+      setFocus(0) %>%
+      setSpin(FALSE)
+  })
+  
+  # output$table <- DT::renderDataTable({
+  #   selected_gene=input$gene
+  #   gene=as.character(genes[genes$Gene==selected_gene,"Gene"])
+  #   #unique_missense_genes[unique_missense_genes$gene_name==gene,]
+  #   unique_missense_genes
+  # },
+  # selection = "single",
+  # search = list(search="alr"))
+  output$table <- DT::renderDataTable(
+    unique_missense_genes,
+    selection = "single",
+    options=list(
+      search = list(search=as.character(genes[genes$Gene==input$gene,"Gene"]))
+    )
+  )
+  
+  observeEvent(input$table_rows_selected,{
+    #req(length(input$table_row_selected) > 0)
+    mutation = as.character(unique_missense_genes[input$table_rows_selected,"hgvd_p"])
+    chain = as.character(unique_missense_genes[input$table_rows_selected,"chain"])
+    # what the absolute FUCK is this mess? I JUST WANT THE MATCH ASDLASJASDASHFKLJASDFK
+    # coming down from the trees was a mistake, and abandoning Perl doubly so.
+    clicked_position = regmatches(mutation, regexpr("[0-9]+", mutation, perl=TRUE))
+    
+    # Now update the 3D structure to highlight the clicked thing and then zoom in.
+    
+    NGLVieweR_proxy("structure") %>%
+      #addSelection('ball+stick'
+      addSelection('spacefill'
+                   , param = list(
+                     name = "Pos"
+                     , sele = trimws(paste0(clicked_position,':', chain))
+                     , color = "red"
+                     #, colorValue="00ff00"
+                     #, colorScheme="element"
+                   )
+      )
+    NGLVieweR_proxy("af_structure") %>%
+      #addSelection('ball+stick'
+      addSelection('spacefill'
+                   , param = list(
+                     name = "Pos"
+                     , sele = clicked_position
+                     , color = "red"
+                     #, colorValue="00ff00"
+                     #, colorScheme="element"
+                   )
+      )
+    
+    NGLVieweR_proxy("af_structure") %>% updateZoomMove(
+      center = clicked_position,
+      zoom = clicked_position,
+      duration = 1000, # animation time in ms
+      z_offSet = -1
+    )
+    NGLVieweR_proxy("structure") %>% updateZoomMove(
+      center = trimws(paste0(clicked_position,':', chain)),
+      zoom = trimws(paste0(clicked_position,':', chain)),
+      duration = 1000, # animation time in ms
+      z_offSet = -1
+    )
+    output$information <- renderUI({
+      selected_gene=input$gene
+      HTML(paste0("<strong>Mutation: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"mutationinformation"]),"<br/>",
+                  "<strong>PDB ID: </strong>", as.character(genes[genes$Gene==selected_gene,"PDB"]),"<br/>",
+                  "<strong>AlphaFold ID: </strong>", as.character(genes[genes$Gene==selected_gene,"AF_PDB"]), "<br/>",
+                  "<strong>Ligand Distance: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"ligand_distance"]), "<br/>",
+                  "<strong>mCSM Lig: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"mcsm_lig"]), "<br/>",
+                  "<strong>mmCSM Lig: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"mmcsm_lig"]), "<br/>",
+                  "<strong>mCSM DUET: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"ddg_duet"]), "<br/>",
+                  "<strong>FoldX: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"ddg_foldx"]), "<br/>",
+                  "<strong>DeepDDG: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"ddg_deepddg"]), "<br/>",
+                  "<strong>Dynamut2: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"ddg_dynamut2"]), "<br/>",
+                  "<strong>mCSM PPI2: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"mcsm_ppi2_affinity"]), "<br/>",
+                  "<strong>Interface Distance: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"interface_dist"]), "<br/>",
+                  "<strong>mCSM NA: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"mcsm_na_affinity"]), "<br/>",
+                  "<strong>Consurf: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"consurf_score"]), "<br/>",
+                  #"<strong>SNAP2: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"snap2_score"]), "<br/>",
+                  "<strong>SNAP2 Outcome: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"snap2_outcome"]), "<br/>",
+                  #"<strong>PROVEAN: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"provean_score"]), "<br/>",
+                  "<strong>PROVEAN Outcome: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"provean_outcome"]), "<br/>",
+                  "<strong>RSA: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"rsa"]), "<br/>",
+                  "<strong>Residue Depth: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"rd_values"]), "<br/>",
+                  "<strong>Total Samples: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"total_sample_count"]), "<br/>",
+                  "<strong>Distinct Lineages: </strong>", as.character(unique_missense_genes[input$table_rows_selected,"distinct_lineage_count"]), "<br/>"
+                  
+      )
+      )
+      
+    })
+    
+    # output$debug <- renderPrint({
+    #   print(c(mutation, clicked_position))
+    # })
+  })
+  observeEvent(
+    {
+      input$clear_ngl
+    }, {
+      NGLVieweR_proxy("structure") %>%
+        removeSelection("Pos") %>%
+        removeSelection("all_mutations_surface") %>%
+        updateVisibility("cartoon", TRUE) %>%
+        removeSelection("all_mutations")
+      NGLVieweR_proxy("af_structure") %>%
+        removeSelection("Pos") %>%
+        removeSelection("all_mutations_surface") %>%
+        updateVisibility("cartoon", TRUE) %>%
+        removeSelection("all_mutations")
+    })
+  # add a surface representation and highlight all mutations on it
+  observeEvent(
+    {
+      input$all_mutations
+    }, {
+      gene = input$gene
+      mutations = paste0(":",
+                         as.matrix(unique_missense_genes[unique_missense_genes$gene_name == gene,c("chain")])[1],
+                         " and (",
+                         paste0(
+                           apply(
+                             unique_missense_genes[unique_missense_genes$gene_name == gene,c("position","chain")],
+                             1,
+                             function(x){
+                               paste0(trimws(x[1])
+                               )}
+                           ),
+                           collapse=", "
+                         ), ")"
+      )
+      #print(mutations)
+      
+      
+      NGLVieweR_proxy("structure") %>%
+        updateVisibility("cartoon", FALSE) %>%
+        addSelection(type="cartoon",
+                     param = list(name = "all_mutations_surface",
+                                  sele = "all",
+                                  color="tan",
+                                  opacity = 0.2
+                     )
+        ) %>%
+        addSelection(type="ball+stick", #spacefill
+                     param = list(name = "all_mutations",
+                                  color="orange",
+                                  sele = mutations
+                                  #colorScheme = "bfactor",
+                                  #opacity = 1
+                     )
+        )
+      NGLVieweR_proxy("af_structure") %>%
+        updateVisibility("cartoon", FALSE) %>%
+        addSelection(type="cartoon",
+                     param = list(name = "all_mutations_surface",
+                                  sele = "all",
+                                  #color="tan",
+                                  colorScheme = "bfactor",
+                                  opacity = 0.2
+                     )
+        ) %>%
+        addSelection(type="ball+stick", #spacefill
+                     param = list(name = "all_mutations",
+                                  color="orange",
+                                  sele = mutations
+                                  #colorScheme = "bfactor",
+                                  #opacity = 1
+                     )
+        )
+    })
+}
+)
diff --git a/ui.R b/ui.R
new file mode 100644
index 0000000..5c50730
--- /dev/null
+++ b/ui.R
@@ -0,0 +1,66 @@
+library(shiny)
+library(shinyjs)
+library(shinydashboard)
+#library("wesanderson") # ayyyy lmao hipster af
+library(dplyr)
+library(DT)
+library(ggplot2)
+library(grid) # for the info box
+library(plotly)
+library(shinycssloaders)
+library(NGLVieweR)
+library(httr)
+library(readr)
+library(RCurl)
+
+dashboardPage(skin="purple",
+                 dashboardHeader(title="Tuberculosis Host"),
+                 dashboardSidebar(
+                   radioButtons("gene",
+                                label="Gene",
+                                choices = genes$Gene,
+                                selected="alr" # "alr" is a value
+                   ),
+                   actionButton("clear_ngl",
+                                "Reset Structures"),
+                   actionButton("all_mutations",
+                                "All Mutations")
+                 ),
+                 dashboardBody(
+                   useShinyjs(),
+                   fluidRow(
+                     box(
+                       title="Crystallised Structure",
+                       width=5,
+                       column(
+                         NGLVieweROutput("structure"),
+                         width=12
+                       ) 
+                     ),
+                     box(
+                       title="AlphaFold Structure",
+                       width=5,
+                       column(
+                         NGLVieweROutput("af_structure"),
+                         width=12
+                       )
+                     ),
+                     box(
+                       title="Mutation Information",
+                       width=2,
+                       column(
+                         htmlOutput("information"),
+                         width=12
+                       )
+                     )
+                   ),
+                   fluidRow(
+                     column(
+                       DT::dataTableOutput('table'),
+                       width=12
+                     )
+                   ),
+                   verbatimTextOutput("debug")
+                 )
+)
+