diff --git a/drug-target/global.R b/drug-target/global.R
index 54175cb..fd5ace4 100644
--- a/drug-target/global.R
+++ b/drug-target/global.R
@@ -651,425 +651,425 @@ if (interactive()){
                         ),
                       )
   )
-  server <- function(input, output, session) {
-
-    #output$LogoPlotSnps = renderPlot(LogoPlotSnps(mutable_df3))
-    output$lin_sc = renderPlot(
-      lin_sc(
-        input$switch_target,
-        all_lineages = input$all_lineages,
-        my_xats = 12, # x axis text size
-        my_yats = 12, # y axis text size
-        my_xals = 12, # x axis label size
-        my_yals = 12, # y axis label size
-        my_lls   = 12, # legend label size
-        d_lab_size = 4
-      )
-    )
-    #### lineage_distP ####
-    output$lineage_distP = renderPlot(
-      lineage_distP(
-        get(paste0(input$switch_target, '_merged_df2')),
-        all_lineages = input$all_lineages,
-        x_lab = "Average Stability",
-        x_axis = "avg_stability_scaled",
-        fill_categ_cols = c("red", "blue")
-      )
-    )
-
-
-    #### observeEvent() Fun(tm) ####
-    observeEvent(input$clear_ngl, {
-      NGLVieweR_proxy("structure") %>%
-        removeSelection("Pos")
-    })
-    # Button to test adding a position
-    observeEvent(input$test_ngl, {
-      NGLVieweR_proxy("structure") %>%
-        addSelection('ball+stick'
-                     , param = list(
-                       name = "Pos"
-                       , sele = "35"
-                       , color = "green")
-        )
-    })
-
-    observeEvent(
-      {
-        input$display_position_range
-        input$stability_snp_param
-        input$logoplot_colour_scheme
-        input$omit_snp_count
-        input$switch_target
-        input$snp_ligand_dist
-        input$snp_nca_dist
-        input$snp_interface_dist
-      },
-      {
-        print("entering main observeEvent()")
-        # C O M P A T I B I L I T Y
-        #gene=input$switch_target
-        #drug=target_map[[gene]]
-        target_gene = input$switch_target
-        merged_df3 = cbind(get(paste0(input$switch_target, '_merged_df3')))
-
-        position_max=max(merged_df3[['position']])
-        position_min=min(merged_df3[['position']])
-        min_ligand_distance=min(merged_df3$ligand_distance)
-        max_ligand_distance=max(merged_df3$ligand_distance)
-        # FIXME: these are IMPORTANT
-        # # add "pos_count" position count column
-        # merged_df3=merged_df3 %>% dplyr::add_count(position)
-        # merged_df3$pos_count=merged_df3$n
-        # merged_df3$n=NULL
-        #
-        mutable_df3 = cbind(merged_df3)
-        #
-        # # re-sort the dataframe according to position count
-        sorted_df = cbind(merged_df3)
-        sorted_df = sorted_df %>% arrange(pos_count)
-
-        #
-        outdir = paste0(load_dir, "Data/", drug, '/output/')
-        indir  = paste0(load_dir, "Data/", drug , "/input/")
-
-
-        #### nasty special-purpose merged_df3 variants ####
-        # FIXME: SLOW
-        # corr_plotdf = corr_data_extract(
-        #   merged_df3
-        #   , gene = gene
-        #   , drug = drug
-        #   , extract_scaled_cols = F
-        # )
-
-        #input$stability_snp_param
-
-        updateCheckboxGroupInput(
-          session,
-          "corr_selected",
-          choiceNames = colnames(get(paste0(input$switch_target,"_corr_df_m3_f"))),
-          choiceValues = colnames(get(paste0(input$switch_target,"_corr_df_m3_f"))),
-          selected = c("FoldX", "DeepDDG", "mCSM.DUET")
-        )
-
-        updateSliderInput(
-          session,
-          "display_position_range",
-          min = position_min,
-          max = position_max
-          #, value = c(position_min, position_min+150)
-        )
-
-        updateNumericInput(session, "selected_logop_snp_position", min = position_min, max = position_max, value = position_min)
-        updateNumericInput(session, "selected_logop_ed_position", min = position_min, max = position_max, value = position_min)
-        updateNumericInput(session, "corr_lig_dist", min = min_ligand_distance, max = max_ligand_distance, value = min_ligand_distance)
-
-        updateNumericInput(session, "snp_ligand_dist", min = min(merged_df3$ligand_distance), max = max(merged_df3$ligand_distance))
-        updateNumericInput(session, "snp_interface_dist", min = min(merged_df3$interface_dist), max = max(merged_df3$interface_dist))
-        updateNumericInput(session, "snp_nca_dist", min = min(merged_df3$nca_distance), max = max(merged_df3$nca_distance))
-
-
-        # different data ranges required for SNP distances
-        snp_ligand_dist_df3    = merged_df3[merged_df3[['ligand_distance']]<input$snp_ligand_dist,]
-        if ("interface_dist" %in% colnames(merged_df3)){
-          snp_interface_dist_df3 = merged_df3[merged_df3[['interface_dist']]<input$snp_interface_dist,]
-        } else {
-          snp_interface_dist_df3 = NULL
-        }
-
-        if ("nca_distance" %in% colnames(merged_df3)){
-          snp_nca_dist_df3       = merged_df3[merged_df3[['nca_distance']]<input$snp_nca_dist,]
-        } else {
-          snp_nca_dist_df3 = NULL
-        }
-
-        stability_colname      = stability_boxes_df[stability_boxes_df$stability_type==input$stability_snp_param,"stability_colname"]
-        outcome_colname        = stability_boxes_df[stability_boxes_df$stability_type==input$stability_snp_param,"outcome_colname"]
-
-        display_position_range = input$display_position_range
-        plot_min=display_position_range[1]
-        plot_max=display_position_range[2]
-
-        logoplot_colour_scheme = input$logoplot_colour_scheme
-        omit_snp_count = input$omit_snp_count
-
-        print(paste0('Plotting positions between: ', plot_min, ' and ', plot_max))
-
-        subset_mutable_df3=mutable_df3[(mutable_df3$position>=plot_min & mutable_df3$position <=plot_max),]
-
-        subset_mutable_df3=mutable_df3[(mutable_df3$position>=plot_min & mutable_df3$position <=plot_max),]
-        subset_sorted_df=sorted_df[(sorted_df$position>=plot_min & sorted_df$position <=plot_max),]
-
-        #### LogoPlotSnps ####
-        output$LogoPlotSnps = renderPlot(
-          LogoPlotSnps(subset_mutable_df3,
-                       aa_pos_drug = get(paste0(target_gene,"_aa_pos_drug")),
-                       active_aa_pos = get(paste0(target_gene,"_active_aa_pos")),
-                       aa_pos_lig1 = get(paste0(target_gene,"_aa_pos_lig1")),
-                       aa_pos_lig2 = get(paste0(target_gene,"_aa_pos_lig2")),
-                       aa_pos_lig3 = get(paste0(target_gene,"_aa_pos_lig3")),
-                       my_logo_col = logoplot_colour_scheme,
-                       omit_snp_count = omit_snp_count
-
-          )
-        )
-
-        ### NGLViewer ####
-        # Structure Viewer WebGL/NGLViewR window
-        output$structure <- renderNGLVieweR({
-          #ngl_gene=isolate(input$switch_target)
-          ngl_gene=input$switch_target
-          ngl_drug=target_map[[ngl_gene]]
-          ngl_pdb_file=paste0(load_dir, "Data/", ngl_drug, '/output/depth/', ngl_gene, '_complex.pdb')
-          print(ngl_pdb_file)
-          NGLVieweR(ngl_pdb_file) %>%
-            addRepresentation("cartoon",
-                              param = list(name = "cartoon",
-                                           color="tan"
-                                           #, colorScheme = "chainid"
-                              )
-            ) %>%
-            stageParameters(backgroundColor = "lightgrey") %>%
-            setQuality("high") %>%
-            setFocus(0) %>%
-            setSpin(FALSE)
-        })
-
-
-        #### Shared dataTable() ####
-        output$table = DT::renderDataTable(
-          datatable(subset_sorted_df[,table_columns],
-                    filter="top",
-                    selection = "single"
-          )
-        )
-
-        #### bp_stability_hmap ####
-        # red/blue tiles wala "Stability SNP by Site"
-        output$bp_stability_hmap = renderPlot(
-          bp_stability_hmap(
-            subset_sorted_df,
-            reorder_position = input$reorder_custom_h,
-            p_title = NULL,
-            yvar_colname = stability_colname,
-            stability_colname = stability_colname,
-            stability_outcome_colname = outcome_colname,
-            my_ylab = NULL,
-            y_max_override = max(sorted_df$pos_count),
-            aa_pos_drug = get(paste0("embb","_aa_pos_drug")),
-            active_aa_pos = get(paste0("embb","_active_aa_pos")),
-            aa_pos_lig1 = get(paste0("embb","_aa_pos_lig1")),
-            aa_pos_lig2 = get(paste0("embb","_aa_pos_lig2")),
-            aa_pos_lig3 = get(paste0("embb","_aa_pos_lig3"))
-          )
-        )
-        #### LogoPlotCustomH ####
-        output$LogoPlotCustomH = renderPlot(
-          LogoPlotCustomH(
-            subset_sorted_df,
-            my_logo_col = logoplot_colour_scheme,
-            aa_pos_drug = get(paste0(target_gene,"_aa_pos_drug")),
-            active_aa_pos = get(paste0(target_gene,"_active_aa_pos")),
-            aa_pos_lig1 = get(paste0(target_gene,"_aa_pos_lig1")),
-            aa_pos_lig2 = get(paste0(target_gene,"_aa_pos_lig2")),
-            aa_pos_lig3 = get(paste0(target_gene,"_aa_pos_lig3"))
-          )
-        )
-
-        #### wideP_consurf3 ####
-        output$wideP_consurf3 = renderPlot(
-          wideP_consurf3(
-            subset_sorted_df,
-            point_colours = consurf_colours,
-            aa_pos_drug = get(paste0(target_gene,"_aa_pos_drug")),
-            active_aa_pos = get(paste0(target_gene,"_active_aa_pos")),
-            aa_pos_lig1 = get(paste0(target_gene,"_aa_pos_lig1")),
-            aa_pos_lig2 = get(paste0(target_gene,"_aa_pos_lig2")),
-            aa_pos_lig3 = get(paste0(target_gene,"_aa_pos_lig3"))
-          )
-        )
-
-        #### site_snp_count_bp ####
-        #mutable_df3[(mutable_df3$position>=plot_min & mutable_df3$position <=plot_max),]
-        # ligand_distance
-        # interface_dist
-        # nca_distance
-        # change to: multiple plots, all use site_snp_count_bp
-        # 4 x plots side by side, one normal (no dist. filter), 2/3 filtered by distance columns above
-        # use "subtitle text" from pos_count_bp_i.R
-
-        output$site_snp_count_bp = renderPlot(
-          site_snp_count_bp(
-            mutable_df3,
-            title_colour = 'black',
-            subtitle_colour = "black",
-            leg_text_size = 12,
-            axis_label_size = 12,
-            geom_ls = 4
-          )
-        )
-        output$site_snp_count_bp_ligand = renderPlot(
-          site_snp_count_bp(
-            snp_ligand_dist_df3,
-            title_colour = 'black',
-            subtitle_colour = "black",
-            leg_text_size = 12,
-            axis_label_size = 12,
-            geom_ls = 4
-          )
-        )
-
-        # if ("interface_dist" %in% colnames(input$switch_target)) {
-        output$site_snp_count_interface = renderPlot(
-          site_snp_count_bp(
-            snp_interface_dist_df3,
-            title_colour = 'black',
-            subtitle_colour = "black",
-            leg_text_size = 12,
-            axis_label_size = 12,
-            geom_ls = 4
-          )
-        )
-        # } #else {
-        #   output$site_snp_count_interface = renderPlot(
-        #     ggplot() + annotate(x=1,y=1,"text", label="No interface data for this target")+theme_void()
-        #   )
-        # }
-
-        output$site_snp_count_nca = renderPlot( #{
-          #if ("nca_distance" %in% colnames(input$switch_target)) {
-          site_snp_count_bp(
-            snp_nca_dist_df3,
-            title_colour = 'black',
-            subtitle_colour = "black",
-            leg_text_size = 12,
-            axis_label_size = 12,
-            geom_ls = 4
-          )
-          #   }  else {
-          #     ggplot() + annotate(x=1,y=1,"text", label="No RNA data for this target")+theme_void()
-          #   }
-          # }
-        )
-
-
-
-        #### DM OM Plots ####
-        #dm_om_param
-        # order needs to be:
-        # embb_lf_duet, embb_lf_foldx, embb_lf_deepddg, embb_lf_dynamut2, embb_lf_dist_gen,
-        # embb_lf_consurf, embb_lf_provean, embb_lf_snap2, embb_lf_mcsm_lig, embb_lf_mmcsm_lig,
-        # embb_lf_mcsm_ppi2, SOMETHING NA
-
-        # embb_lf_mmcsm_lig SOMETHING NA,
-        #dm_om_selection=input$dm_om_param
-        #dm_om_df = dm_om_map[[dm_om_selection]]
-        #output$lf_bp2 = renderPlot(lf_bp2(get(paste0(input$switch_target, '_', dm_om_df))))
-
-        output$lf_bp2 = renderPlot(
-          cowplot::plot_grid(
-            plotlist = lapply(
-              ls(name=.GlobalEnv,
-                 pattern=paste0(
-                   target_gene,
-                   '_lf_'
-                 )
-              ),
-              function(x){
-                lf_bp2(get(x))
-              }
-            )#, nrow=3
-          ), height=800
-        )
-      }
-    )
-
-
-    # FIXME: Doesn't add selected table rows correctly
-    observeEvent(
-      {
-        input$table_rows_selected
-      },
-      {
-        # having to duplicate this is a bit annoying :-(
-        ngl_merged_df3=cbind(get(paste0(input$switch_target, '_merged_df3')))
-        ngl_sorted_df = cbind(ngl_merged_df3)
-        ngl_sorted_df = ngl_sorted_df %>% arrange(pos_count)
-
-        position_max=max(ngl_merged_df3[['position']])
-        position_min=min(ngl_merged_df3[['position']])
-        display_position_range = input$display_position_range
-        plot_min=display_position_range[1]
-        plot_max=display_position_range[2]
-        #ngl_subset_df=ngl_merged_df3[(ngl_merged_df3$position>=plot_min & ngl_merged_df3$position <=plot_max),]
-        ngl_subset_df=ngl_sorted_df[(ngl_sorted_df$position>=plot_min & ngl_sorted_df$position <=plot_max),]
-
-
-        #table_rows_selected = isolate(input$table_rows_selected)
-        table_rows_selected = input$table_rows_selected
-        class(table_rows_selected)
-        #cat(paste0("Target: ", as.character(input$switch_target), "\nTable Rows for NGLViewR: ", as.character(table_rows_selected)))
-
-        struct_pos=(as.character(ngl_subset_df[table_rows_selected,"position"]))
-        cat(paste0('Table Index: ', table_rows_selected, "position: ", struct_pos))
-
-        NGLVieweR_proxy("structure") %>%
-          #addSelection('ball+stick'
-          addSelection('hyperball'
-                       , param = list(
-                         name = "Pos"
-                         , sele = struct_pos
-                         #, color = "#00ff00"
-                         , colorValue="00ff00"
-                         , colorScheme="element"
-                       )
-          )
-        #cat(paste0('Done NGLViewR addSelection for: ', positions_to_add))
-      }
-    )
-    #### Correlation observeEvent ####
-    # Yet another special-case observeEvent to handle the correlation pair plot
-
-    observeEvent(
-      {
-        input$corr_selected
-        input$corr_method
-        input$corr_lig_dist
-      },
-      {
-        dist_cutoff_user = input$corr_lig_dist
-        target_gene=input$switch_target
-        plot_title=paste0(target_map[[target_gene]],"/",target_gene)
-
-        corr_plot_df = get(
-          paste0(
-            input$switch_target,"_corr_df_m3_f"
-          )
-        )[,c(input$corr_selected, "dst_mode")]
-
-        #if ( dist_cutoff_user >= 2) {
-        #corr_plotdf_subset = corr_plot_df[corr_plot_df[['Lig.Dist']] < dist_cutoff_user,]
-        #}
-        # else {
-        #   corr_plotdf_subset = corr_plot_df
-        # }
-
-        #### Correlation using ggpairs() ####
-        output$my_corr_pairs = renderPlot(
-          dashboard_ggpairs(
-            corr_plot_df,
-            plot_title = plot_title,
-            method = input$corr_method,
-            tt_args_size = 7,
-            gp_args_size = 7
-          ), height = 900
-        )
-      }
-    )
-  }
-
-
-  app <- shinyApp(ui, server)
-  runApp(app)
+  # server <- function(input, output, session) {
+  # 
+  #   #output$LogoPlotSnps = renderPlot(LogoPlotSnps(mutable_df3))
+  #   output$lin_sc = renderPlot(
+  #     lin_sc(
+  #       input$switch_target,
+  #       all_lineages = input$all_lineages,
+  #       my_xats = 12, # x axis text size
+  #       my_yats = 12, # y axis text size
+  #       my_xals = 12, # x axis label size
+  #       my_yals = 12, # y axis label size
+  #       my_lls   = 12, # legend label size
+  #       d_lab_size = 4
+  #     )
+  #   )
+  #   #### lineage_distP ####
+  #   output$lineage_distP = renderPlot(
+  #     lineage_distP(
+  #       get(paste0(input$switch_target, '_merged_df2')),
+  #       all_lineages = input$all_lineages,
+  #       x_lab = "Average Stability",
+  #       x_axis = "avg_stability_scaled",
+  #       fill_categ_cols = c("red", "blue")
+  #     )
+  #   )
+  # 
+  # 
+  #   #### observeEvent() Fun(tm) ####
+  #   observeEvent(input$clear_ngl, {
+  #     NGLVieweR_proxy("structure") %>%
+  #       removeSelection("Pos")
+  #   })
+  #   # Button to test adding a position
+  #   observeEvent(input$test_ngl, {
+  #     NGLVieweR_proxy("structure") %>%
+  #       addSelection('ball+stick'
+  #                    , param = list(
+  #                      name = "Pos"
+  #                      , sele = "35"
+  #                      , color = "green")
+  #       )
+  #   })
+  # 
+  #   observeEvent(
+  #     {
+  #       input$display_position_range
+  #       input$stability_snp_param
+  #       input$logoplot_colour_scheme
+  #       input$omit_snp_count
+  #       input$switch_target
+  #       input$snp_ligand_dist
+  #       input$snp_nca_dist
+  #       input$snp_interface_dist
+  #     },
+  #     {
+  #       print("entering main observeEvent()")
+  #       # C O M P A T I B I L I T Y
+  #       #gene=input$switch_target
+  #       #drug=target_map[[gene]]
+  #       target_gene = input$switch_target
+  #       merged_df3 = cbind(get(paste0(input$switch_target, '_merged_df3')))
+  # 
+  #       position_max=max(merged_df3[['position']])
+  #       position_min=min(merged_df3[['position']])
+  #       min_ligand_distance=min(merged_df3$ligand_distance)
+  #       max_ligand_distance=max(merged_df3$ligand_distance)
+  #       # FIXME: these are IMPORTANT
+  #       # # add "pos_count" position count column
+  #       # merged_df3=merged_df3 %>% dplyr::add_count(position)
+  #       # merged_df3$pos_count=merged_df3$n
+  #       # merged_df3$n=NULL
+  #       #
+  #       mutable_df3 = cbind(merged_df3)
+  #       #
+  #       # # re-sort the dataframe according to position count
+  #       sorted_df = cbind(merged_df3)
+  #       sorted_df = sorted_df %>% arrange(pos_count)
+  # 
+  #       #
+  #       outdir = paste0(load_dir, "Data/", drug, '/output/')
+  #       indir  = paste0(load_dir, "Data/", drug , "/input/")
+  # 
+  # 
+  #       #### nasty special-purpose merged_df3 variants ####
+  #       # FIXME: SLOW
+  #       # corr_plotdf = corr_data_extract(
+  #       #   merged_df3
+  #       #   , gene = gene
+  #       #   , drug = drug
+  #       #   , extract_scaled_cols = F
+  #       # )
+  # 
+  #       #input$stability_snp_param
+  # 
+  #       updateCheckboxGroupInput(
+  #         session,
+  #         "corr_selected",
+  #         choiceNames = colnames(get(paste0(input$switch_target,"_corr_df_m3_f"))),
+  #         choiceValues = colnames(get(paste0(input$switch_target,"_corr_df_m3_f"))),
+  #         selected = c("FoldX", "DeepDDG", "mCSM.DUET")
+  #       )
+  # 
+  #       updateSliderInput(
+  #         session,
+  #         "display_position_range",
+  #         min = position_min,
+  #         max = position_max
+  #         #, value = c(position_min, position_min+150)
+  #       )
+  # 
+  #       updateNumericInput(session, "selected_logop_snp_position", min = position_min, max = position_max, value = position_min)
+  #       updateNumericInput(session, "selected_logop_ed_position", min = position_min, max = position_max, value = position_min)
+  #       updateNumericInput(session, "corr_lig_dist", min = min_ligand_distance, max = max_ligand_distance, value = min_ligand_distance)
+  # 
+  #       updateNumericInput(session, "snp_ligand_dist", min = min(merged_df3$ligand_distance), max = max(merged_df3$ligand_distance))
+  #       updateNumericInput(session, "snp_interface_dist", min = min(merged_df3$interface_dist), max = max(merged_df3$interface_dist))
+  #       updateNumericInput(session, "snp_nca_dist", min = min(merged_df3$nca_distance), max = max(merged_df3$nca_distance))
+  # 
+  # 
+  #       # different data ranges required for SNP distances
+  #       snp_ligand_dist_df3    = merged_df3[merged_df3[['ligand_distance']]<input$snp_ligand_dist,]
+  #       if ("interface_dist" %in% colnames(merged_df3)){
+  #         snp_interface_dist_df3 = merged_df3[merged_df3[['interface_dist']]<input$snp_interface_dist,]
+  #       } else {
+  #         snp_interface_dist_df3 = NULL
+  #       }
+  # 
+  #       if ("nca_distance" %in% colnames(merged_df3)){
+  #         snp_nca_dist_df3       = merged_df3[merged_df3[['nca_distance']]<input$snp_nca_dist,]
+  #       } else {
+  #         snp_nca_dist_df3 = NULL
+  #       }
+  # 
+  #       stability_colname      = stability_boxes_df[stability_boxes_df$stability_type==input$stability_snp_param,"stability_colname"]
+  #       outcome_colname        = stability_boxes_df[stability_boxes_df$stability_type==input$stability_snp_param,"outcome_colname"]
+  # 
+  #       display_position_range = input$display_position_range
+  #       plot_min=display_position_range[1]
+  #       plot_max=display_position_range[2]
+  # 
+  #       logoplot_colour_scheme = input$logoplot_colour_scheme
+  #       omit_snp_count = input$omit_snp_count
+  # 
+  #       print(paste0('Plotting positions between: ', plot_min, ' and ', plot_max))
+  # 
+  #       subset_mutable_df3=mutable_df3[(mutable_df3$position>=plot_min & mutable_df3$position <=plot_max),]
+  # 
+  #       subset_mutable_df3=mutable_df3[(mutable_df3$position>=plot_min & mutable_df3$position <=plot_max),]
+  #       subset_sorted_df=sorted_df[(sorted_df$position>=plot_min & sorted_df$position <=plot_max),]
+  # 
+  #       #### LogoPlotSnps ####
+  #       output$LogoPlotSnps = renderPlot(
+  #         LogoPlotSnps(subset_mutable_df3,
+  #                      aa_pos_drug = get(paste0(target_gene,"_aa_pos_drug")),
+  #                      active_aa_pos = get(paste0(target_gene,"_active_aa_pos")),
+  #                      aa_pos_lig1 = get(paste0(target_gene,"_aa_pos_lig1")),
+  #                      aa_pos_lig2 = get(paste0(target_gene,"_aa_pos_lig2")),
+  #                      aa_pos_lig3 = get(paste0(target_gene,"_aa_pos_lig3")),
+  #                      my_logo_col = logoplot_colour_scheme,
+  #                      omit_snp_count = omit_snp_count
+  # 
+  #         )
+  #       )
+  # 
+  #       ### NGLViewer ####
+  #       # Structure Viewer WebGL/NGLViewR window
+  #       output$structure <- renderNGLVieweR({
+  #         #ngl_gene=isolate(input$switch_target)
+  #         ngl_gene=input$switch_target
+  #         ngl_drug=target_map[[ngl_gene]]
+  #         ngl_pdb_file=paste0(load_dir, "Data/", ngl_drug, '/output/depth/', ngl_gene, '_complex.pdb')
+  #         print(ngl_pdb_file)
+  #         NGLVieweR(ngl_pdb_file) %>%
+  #           addRepresentation("cartoon",
+  #                             param = list(name = "cartoon",
+  #                                          color="tan"
+  #                                          #, colorScheme = "chainid"
+  #                             )
+  #           ) %>%
+  #           stageParameters(backgroundColor = "lightgrey") %>%
+  #           setQuality("high") %>%
+  #           setFocus(0) %>%
+  #           setSpin(FALSE)
+  #       })
+  # 
+  # 
+  #       #### Shared dataTable() ####
+  #       output$table = DT::renderDataTable(
+  #         datatable(subset_sorted_df[,table_columns],
+  #                   filter="top",
+  #                   selection = "single"
+  #         )
+  #       )
+  # 
+  #       #### bp_stability_hmap ####
+  #       # red/blue tiles wala "Stability SNP by Site"
+  #       output$bp_stability_hmap = renderPlot(
+  #         bp_stability_hmap(
+  #           subset_sorted_df,
+  #           reorder_position = input$reorder_custom_h,
+  #           p_title = NULL,
+  #           yvar_colname = stability_colname,
+  #           stability_colname = stability_colname,
+  #           stability_outcome_colname = outcome_colname,
+  #           my_ylab = NULL,
+  #           y_max_override = max(sorted_df$pos_count),
+  #           aa_pos_drug = get(paste0("embb","_aa_pos_drug")),
+  #           active_aa_pos = get(paste0("embb","_active_aa_pos")),
+  #           aa_pos_lig1 = get(paste0("embb","_aa_pos_lig1")),
+  #           aa_pos_lig2 = get(paste0("embb","_aa_pos_lig2")),
+  #           aa_pos_lig3 = get(paste0("embb","_aa_pos_lig3"))
+  #         )
+  #       )
+  #       #### LogoPlotCustomH ####
+  #       output$LogoPlotCustomH = renderPlot(
+  #         LogoPlotCustomH(
+  #           subset_sorted_df,
+  #           my_logo_col = logoplot_colour_scheme,
+  #           aa_pos_drug = get(paste0(target_gene,"_aa_pos_drug")),
+  #           active_aa_pos = get(paste0(target_gene,"_active_aa_pos")),
+  #           aa_pos_lig1 = get(paste0(target_gene,"_aa_pos_lig1")),
+  #           aa_pos_lig2 = get(paste0(target_gene,"_aa_pos_lig2")),
+  #           aa_pos_lig3 = get(paste0(target_gene,"_aa_pos_lig3"))
+  #         )
+  #       )
+  # 
+  #       #### wideP_consurf3 ####
+  #       output$wideP_consurf3 = renderPlot(
+  #         wideP_consurf3(
+  #           subset_sorted_df,
+  #           point_colours = consurf_colours,
+  #           aa_pos_drug = get(paste0(target_gene,"_aa_pos_drug")),
+  #           active_aa_pos = get(paste0(target_gene,"_active_aa_pos")),
+  #           aa_pos_lig1 = get(paste0(target_gene,"_aa_pos_lig1")),
+  #           aa_pos_lig2 = get(paste0(target_gene,"_aa_pos_lig2")),
+  #           aa_pos_lig3 = get(paste0(target_gene,"_aa_pos_lig3"))
+  #         )
+  #       )
+  # 
+  #       #### site_snp_count_bp ####
+  #       #mutable_df3[(mutable_df3$position>=plot_min & mutable_df3$position <=plot_max),]
+  #       # ligand_distance
+  #       # interface_dist
+  #       # nca_distance
+  #       # change to: multiple plots, all use site_snp_count_bp
+  #       # 4 x plots side by side, one normal (no dist. filter), 2/3 filtered by distance columns above
+  #       # use "subtitle text" from pos_count_bp_i.R
+  # 
+  #       output$site_snp_count_bp = renderPlot(
+  #         site_snp_count_bp(
+  #           mutable_df3,
+  #           title_colour = 'black',
+  #           subtitle_colour = "black",
+  #           leg_text_size = 12,
+  #           axis_label_size = 12,
+  #           geom_ls = 4
+  #         )
+  #       )
+  #       output$site_snp_count_bp_ligand = renderPlot(
+  #         site_snp_count_bp(
+  #           snp_ligand_dist_df3,
+  #           title_colour = 'black',
+  #           subtitle_colour = "black",
+  #           leg_text_size = 12,
+  #           axis_label_size = 12,
+  #           geom_ls = 4
+  #         )
+  #       )
+  # 
+  #       # if ("interface_dist" %in% colnames(input$switch_target)) {
+  #       output$site_snp_count_interface = renderPlot(
+  #         site_snp_count_bp(
+  #           snp_interface_dist_df3,
+  #           title_colour = 'black',
+  #           subtitle_colour = "black",
+  #           leg_text_size = 12,
+  #           axis_label_size = 12,
+  #           geom_ls = 4
+  #         )
+  #       )
+  #       # } #else {
+  #       #   output$site_snp_count_interface = renderPlot(
+  #       #     ggplot() + annotate(x=1,y=1,"text", label="No interface data for this target")+theme_void()
+  #       #   )
+  #       # }
+  # 
+  #       output$site_snp_count_nca = renderPlot( #{
+  #         #if ("nca_distance" %in% colnames(input$switch_target)) {
+  #         site_snp_count_bp(
+  #           snp_nca_dist_df3,
+  #           title_colour = 'black',
+  #           subtitle_colour = "black",
+  #           leg_text_size = 12,
+  #           axis_label_size = 12,
+  #           geom_ls = 4
+  #         )
+  #         #   }  else {
+  #         #     ggplot() + annotate(x=1,y=1,"text", label="No RNA data for this target")+theme_void()
+  #         #   }
+  #         # }
+  #       )
+  # 
+  # 
+  # 
+  #       #### DM OM Plots ####
+  #       #dm_om_param
+  #       # order needs to be:
+  #       # embb_lf_duet, embb_lf_foldx, embb_lf_deepddg, embb_lf_dynamut2, embb_lf_dist_gen,
+  #       # embb_lf_consurf, embb_lf_provean, embb_lf_snap2, embb_lf_mcsm_lig, embb_lf_mmcsm_lig,
+  #       # embb_lf_mcsm_ppi2, SOMETHING NA
+  # 
+  #       # embb_lf_mmcsm_lig SOMETHING NA,
+  #       #dm_om_selection=input$dm_om_param
+  #       #dm_om_df = dm_om_map[[dm_om_selection]]
+  #       #output$lf_bp2 = renderPlot(lf_bp2(get(paste0(input$switch_target, '_', dm_om_df))))
+  # 
+  #       output$lf_bp2 = renderPlot(
+  #         cowplot::plot_grid(
+  #           plotlist = lapply(
+  #             ls(name=.GlobalEnv,
+  #                pattern=paste0(
+  #                  target_gene,
+  #                  '_lf_'
+  #                )
+  #             ),
+  #             function(x){
+  #               lf_bp2(get(x))
+  #             }
+  #           )#, nrow=3
+  #         ), height=800
+  #       )
+  #     }
+  #   )
+  # 
+  # 
+  #   # FIXME: Doesn't add selected table rows correctly
+  #   observeEvent(
+  #     {
+  #       input$table_rows_selected
+  #     },
+  #     {
+  #       # having to duplicate this is a bit annoying :-(
+  #       ngl_merged_df3=cbind(get(paste0(input$switch_target, '_merged_df3')))
+  #       ngl_sorted_df = cbind(ngl_merged_df3)
+  #       ngl_sorted_df = ngl_sorted_df %>% arrange(pos_count)
+  # 
+  #       position_max=max(ngl_merged_df3[['position']])
+  #       position_min=min(ngl_merged_df3[['position']])
+  #       display_position_range = input$display_position_range
+  #       plot_min=display_position_range[1]
+  #       plot_max=display_position_range[2]
+  #       #ngl_subset_df=ngl_merged_df3[(ngl_merged_df3$position>=plot_min & ngl_merged_df3$position <=plot_max),]
+  #       ngl_subset_df=ngl_sorted_df[(ngl_sorted_df$position>=plot_min & ngl_sorted_df$position <=plot_max),]
+  # 
+  # 
+  #       #table_rows_selected = isolate(input$table_rows_selected)
+  #       table_rows_selected = input$table_rows_selected
+  #       class(table_rows_selected)
+  #       #cat(paste0("Target: ", as.character(input$switch_target), "\nTable Rows for NGLViewR: ", as.character(table_rows_selected)))
+  # 
+  #       struct_pos=(as.character(ngl_subset_df[table_rows_selected,"position"]))
+  #       cat(paste0('Table Index: ', table_rows_selected, "position: ", struct_pos))
+  # 
+  #       NGLVieweR_proxy("structure") %>%
+  #         #addSelection('ball+stick'
+  #         addSelection('hyperball'
+  #                      , param = list(
+  #                        name = "Pos"
+  #                        , sele = struct_pos
+  #                        #, color = "#00ff00"
+  #                        , colorValue="00ff00"
+  #                        , colorScheme="element"
+  #                      )
+  #         )
+  #       #cat(paste0('Done NGLViewR addSelection for: ', positions_to_add))
+  #     }
+  #   )
+  #   #### Correlation observeEvent ####
+  #   # Yet another special-case observeEvent to handle the correlation pair plot
+  # 
+  #   observeEvent(
+  #     {
+  #       input$corr_selected
+  #       input$corr_method
+  #       input$corr_lig_dist
+  #     },
+  #     {
+  #       dist_cutoff_user = input$corr_lig_dist
+  #       target_gene=input$switch_target
+  #       plot_title=paste0(target_map[[target_gene]],"/",target_gene)
+  # 
+  #       corr_plot_df = get(
+  #         paste0(
+  #           input$switch_target,"_corr_df_m3_f"
+  #         )
+  #       )[,c(input$corr_selected, "dst_mode")]
+  # 
+  #       #if ( dist_cutoff_user >= 2) {
+  #       #corr_plotdf_subset = corr_plot_df[corr_plot_df[['Lig.Dist']] < dist_cutoff_user,]
+  #       #}
+  #       # else {
+  #       #   corr_plotdf_subset = corr_plot_df
+  #       # }
+  # 
+  #       #### Correlation using ggpairs() ####
+  #       output$my_corr_pairs = renderPlot(
+  #         dashboard_ggpairs(
+  #           corr_plot_df,
+  #           plot_title = plot_title,
+  #           method = input$corr_method,
+  #           tt_args_size = 7,
+  #           gp_args_size = 7
+  #         ), height = 900
+  #       )
+  #     }
+  #   )
+  # }
+  # 
+  # 
+  # app <- shinyApp(ui, server)
+  # runApp(app)
 }