diff --git a/msa/.global.R.swp b/msa/.global.R.swp
deleted file mode 100644
index ae9e887..0000000
Binary files a/msa/.global.R.swp and /dev/null differ
diff --git a/msa/global.R b/msa/global.R
index 92e2cc4..9873d8b 100644
--- a/msa/global.R
+++ b/msa/global.R
@@ -1,17 +1,47 @@
+# ***************************
+# **   I M P O R T A N T   **
+# ***************************
+
+# DO NOT USE OR MODIFY THIS.
+# USE THE ONE IN THE 'Dashboards'
+# REPO
+
+
+
+
+
 library(shinycssloaders)
 library(DT)
 library(NGLVieweR)
 library(hash)
 
+# FIXME This is slow and should happen *once only*
+#source("~/git/LSHTM_analysis/scripts/Header_TT.R")
+
+# FIXME: these are needed but slow to load every time
+#  source("~/git/LSHTM_analysis/config/alr.R")
+#  source("~/git/LSHTM_analysis/config/gid.R")
+
+#  source("~/git/LSHTM_analysis/config/pnca.R")
+#  source("~/git/LSHTM_analysis/config/rpob.R")
+#  source("~/git/LSHTM_analysis/config/katg.R")
+
+# TODO: this is TEMPORARY and will shortly get replaced with a target picker
+# that'll reload everything when changing targets. the lapply() is *much* quicker
+# than previous approaches
+
+# system.time({
+source("~/git/LSHTM_analysis/scripts/Header_TT.R")
+
 load_target_globals=function(target){
   cat(paste0("Reloading Target: ", target))
-  source(paste0("/srv/shiny-server/git/LSHTM_analysis/config/", target, ".R")) # load per-target config file
-  
-  invisible(assign(paste0(target, "_merged_df3"), read.csv(paste0("/srv/shiny-server/git/Misc/shiny_dashboard/data/",target,"-merged_df3.csv")), envir = .GlobalEnv))
-  invisible(assign(paste0(target, "_merged_df2"), read.csv(paste0("/srv/shiny-server/git/Misc/shiny_dashboard/data/",target,"-merged_df2.csv")), envir = .GlobalEnv))
-  invisible(assign(paste0(target, "_corr_df_m3_f"), read.csv(paste0("/srv/shiny-server/git/Misc/shiny_dashboard/data/",target,"-corr_df_m3_f.csv")), envir = .GlobalEnv))
-  invisible(assign(paste0(target, "_lin_lf"), read.csv(paste0("/srv/shiny-server/git/Misc/shiny_dashboard/data/",target,"-lin_lf.csv")), envir = .GlobalEnv))
-  invisible(assign(paste0(target, "_lin_wf"), read.csv(paste0("/srv/shiny-server/git/Misc/shiny_dashboard/data/",target,"-lin_wf.csv")), envir = .GlobalEnv))
+  source(paste0("~/git/LSHTM_analysis/config/", target, ".R")) # load per-target config file
+
+  invisible(assign(paste0(target, "_merged_df3"), read.csv(paste0("~/git/Misc/shiny_dashboard/data/",target,"-merged_df3.csv")), envir = .GlobalEnv))
+  invisible(assign(paste0(target, "_merged_df2"), read.csv(paste0("~/git/Misc/shiny_dashboard/data/",target,"-merged_df2.csv")), envir = .GlobalEnv))
+  invisible(assign(paste0(target, "_corr_df_m3_f"), read.csv(paste0("~/git/Misc/shiny_dashboard/data/",target,"-corr_df_m3_f.csv")), envir = .GlobalEnv))
+  invisible(assign(paste0(target, "_lin_lf"), read.csv(paste0("~/git/Misc/shiny_dashboard/data/",target,"-lin_lf.csv")), envir = .GlobalEnv))
+  invisible(assign(paste0(target, "_lin_wf"), read.csv(paste0("~/git/Misc/shiny_dashboard/data/",target,"-lin_wf.csv")), envir = .GlobalEnv))
   lapply(
     c(
       "duet",
@@ -26,12 +56,12 @@ load_target_globals=function(target){
       "mcsm_ppi2"#,
       #"mcsm_na"
     ), function(x){
-      wf_filename=paste0("/srv/shiny-server/git/Misc/shiny_dashboard/data/", tolower(gene), "-wf_", x ,".csv")
+      wf_filename=paste0("~/git/Misc/shiny_dashboard/data/", tolower(gene), "-wf_", x ,".csv")
       wf_var=paste0("wf_",x)
       if (file.exists(wf_filename)){
         invisible(assign(wf_var,read.csv(wf_filename), envir = .GlobalEnv)) # FILTH
       }
-      lf_filename=paste0("/srv/shiny-server/git/Misc/shiny_dashboard/data/", tolower(gene), "-lf_", x ,".csv")
+      lf_filename=paste0("~/git/Misc/shiny_dashboard/data/", tolower(gene), "-lf_", x ,".csv")
       lf_var=paste0(target, "_lf_",x)
       if (file.exists(lf_filename)){
         invisible(assign(lf_var,read.csv(lf_filename), envir = .GlobalEnv)) # FILTH
@@ -42,37 +72,24 @@ load_target_globals=function(target){
 # populate target-specific *_unified_msa vars
 load_msa_global=function(gene){
   drug=target_map[[gene]]
-  in_filename_msa = paste0(tolower(gene), "_msa.csv") 
-  infile_msa = paste0("/srv/shiny-server/git/Data/", drug, "/output/", in_filename_msa)
+  in_filename_msa = paste0(tolower(gene), "_msa.csv")
+  infile_msa = paste0("~/git/Data/", drug, "/output/", in_filename_msa)
   print(infile_msa)
   msa1 = read.csv(infile_msa, header = F)
   msa_seq = msa1$V1
-  
-  infile_fasta = paste0("/srv/shiny-server/git/Data/", drug, "/input/", tolower(gene), "2_f2.fasta")
+
+  infile_fasta = paste0("~/git/Data/", drug, "/input/", tolower(gene), "2_f2.fasta")
   print(infile_fasta)
   msa2 = read.csv(infile_fasta, header = F)
   wt_seq = msa2$V1
-  
+
   target_name=paste0(gene, '_unified_msa')
   #print(target_name)
   invisible(assign(target_name, list(msa_seq = msa_seq, wt_seq = wt_seq), envir = .GlobalEnv))
 }
 
 #### Local Functions ####
-# Generate a conditionalPanel() for a given graph function and sidebar name combination
-generate_conditionalPanel = function(tab_name, plot_function, plot_df){
-  # e.g.: list("lin_count_bp_diversity", "Lineage diversity count")
-  cond=paste0("input.sidebar == '", tab_name, "'")
-  conditionalPanel(condition=cond, box(
-    title=tab_name
-    , status = "info"
-    , width=NULL
-    , plotOutput(plot_function
-                 , click = "plot_click") %>% withSpinner(color="#0dc5c1")
-    # , plotOutput(plot_function, click = "plot_click")
-  )
-  )
-}
+
 
 # FIXME: passing in the per-plot params is broken
 lin_sc=function(x, all_lineages = F, ...){
@@ -180,7 +197,7 @@ table_columns = c(
   "snap2_outcome",
   "consurf_outcome",
   "provean_outcome",
-  "rsa", 
+  "rsa",
   "kd_values" ,
   "rd_values"
 )
@@ -197,26 +214,6 @@ dm_om_methods = c("DUET ΔΔG"
                   , "Ligand affinity (log fold change)"
                   , "mCSM-NA affinity ΔΔG"
                   , "SNAP2")
-dm_om_map = hash(c(
-  "DUET ΔΔG"
-  , "Consurf"      
-  , "Deepddg ΔΔG"  
-  , "Dynamut2 ΔΔG" 
-  , "FoldX ΔΔG"    
-  , "Ligand affinity (log fold change)"
-  , "mCSM-NA affinity ΔΔG"
-  , "SNAP2"
-), c(
-  "lf_duet"
-  ,"lf_consurf"
-  ,"lf_deepddg"
-  ,"lf_dynamut2"
-  ,"lf_foldx"
-  ,"lf_mcsm_lig"
-  ,"lf_mcsm_na"
-  ,"lf_snap2"
-)
-)
 #### target_map: handy gene/drug mapping hash ####
 target_map = hash(
   c(
@@ -235,7 +232,7 @@ target_map = hash(
     "isoniazid")
 )
 
-# load E V E R Y T H I N G
+#load E V E R Y T H I N G
 lapply(c(
   "alr",
   "embb",
@@ -245,57 +242,188 @@ lapply(c(
   "rpob"
 ),function(x){
   invisible(load_target_globals(x))
-  invisible(load_msa_global(x)) # turn off to speed up start time at the expense of "LogoP ED"
+  invisible(load_msa_global(x))
 }
 )
 
-consurf_palette1 = c("0" = "yellow2"
-                     , "1" = "cyan1"
-                     , "2" = "steelblue2"
-                     , "3" = "cadetblue2"
-                     , "4" = "paleturquoise2"
-                     , "5" = "thistle3"
-                     , "6" = "thistle2"
-                     , "7" = "plum2"
-                     , "8" = "maroon"
-                     , "9" = "violetred2")
-
-consurf_palette2 =  c("0" = "yellow2"
-                      , "1" = "forestgreen"
-                      , "2" = "seagreen3"
-                      , "3" = "palegreen1"
-                      , "4" = "darkseagreen2"
-                      , "5" = "thistle3"
-                      , "6" = "lightpink1"
-                      , "7" = "orchid3"
-                      , "8" = "orchid4"
-                      , "9" = "darkorchid4")
-
-# decreasing levels mess legend
-# consurf_colours_LEVEL = c(
-#    "0" = rgb(1.00,1.00,0.59)
-#   , "9" = rgb(0.63,0.16,0.37)
-#   , "8" = rgb(0.94,0.49,0.67)
-#   , "7" = rgb(0.98,0.78,0.86)
-#   , "6" = rgb(0.98,0.92,0.96)
-#   , "5" = rgb(1.00,1.00,1.00)
-#   , "4" = rgb(0.84,0.94,0.94)
-#   , "3" = rgb(0.65,0.86,0.90)
-#   , "2" = rgb(0.29,0.69,0.75)
-#   , "1" = rgb(0.04,0.49,0.51)
-#   )
-
-consurf_colours = c(
-  "0" = rgb(1.00,1.00,0.59)
-  , "1" = rgb(0.04,0.49,0.51)
-  , "2" = rgb(0.29,0.69,0.75)
-  , "3" = rgb(0.65,0.86,0.90)
-  , "4" = rgb(0.84,0.94,0.94)
-  , "5" = rgb(1.00,1.00,1.00)
-  , "6" = rgb(0.98,0.92,0.96)
-  , "7" = rgb(0.98,0.78,0.86)
-  , "8" = rgb(0.94,0.49,0.67)
-  , "9" = rgb(0.63,0.16,0.37)
+#### Shiny UI #####
+if(interactive()){
+ui <- dashboardPage(
+  #dashboardHeader(title = paste0(gene, "/", drug)),
+  dashboardHeader(title = "Sequence Alignment"),
+  
+  dashboardSidebar(
+    sidebarMenu( id = "sidebar",
+                 selectInput(
+                   "switch_target",
+                   label="Target",
+                   choices = c(
+                     "alr",
+                     "embb",
+                     "gid",
+                     "katg",
+                     "pnca",
+                     "rpob"
+                   ),
+                   selected="embb"),
+                 menuItem("LogoP ED", tabName="LogoP ED"),
+                 
+                 sliderInput(
+                   "display_position_full_range"
+                   , "Display Positions"
+                   , min=1, max=150, value=c(1,150)
+                 ),
+                 
+                 conditionalPanel(
+                   condition="
+                                  input.sidebar == 'LogoP SNP' ||
+                                  input.sidebar == 'LogoP OR' ||
+                                  input.sidebar == 'LogoP ED'", 
+                   selectInput(
+                     "logoplot_colour_scheme", 
+                     label="Logo Plot Colour Scheme", 
+                     choices = logoPlotSchemes, 
+                     selected="chemistry"
+                   )
+                 )
+    )
+  ),
+  body <- dashboardBody(
+    
+    tabItems(
+      tabItem(tabName = "dashboard",
+              h2("Dashboard tab content")
+      ),
+      
+      tabItem(tabName = "widgets",
+              h2("Widgets tab content")
+      )
+    ),
+    # creates a 'Conditional Panel' containing a plot object from each of our 
+    # ggplot plot functions (and its associated data frame)
+    fluidRow(
+      column(
+        width=12,
+        plotOutput("LogoPlotMSA",
+                   click = "plot_click") %>% withSpinner(color="#0dc5c1")
+      )
+    )
+  )
 )
+#### Shiny Backend Server #####
+server <- function(input, output, session) {
+  observeEvent(
+    {
+      input$display_position_full_range #special-purpose for MSA
+      input$logoplot_colour_scheme
+      input$switch_target
+    },
+    {
+      # C O M P A T I B I L I T Y
+      #gene=input$switch_target
+      #drug=target_map[[gene]]
+      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)
+      unified_msa = get(paste0(input$switch_target, '_unified_msa'))
+      # 
+      # # re-sort the dataframe according to position count
+      sorted_df = cbind(merged_df3)
+      sorted_df = sorted_df %>% arrange(pos_count)
+      
+      # 
+      outdir = paste0("~/git/Data/", drug, '/output/')
+      indir  = paste0("~/git/Data/", drug , "/input/")
+      # 
+      # source("~/git/LSHTM_analysis/scripts/plotting/logo_data_msa.R") # probably unnecessary...
+      
+      #  source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
+      
+      #### nasty special-purpose merged_df3 variants ####
+      # FIXME: SLOW
+      # corr_plotdf = corr_data_extract(
+      #   merged_df3
+      #   , gene = gene
+      #   , drug = drug
+      #   , extract_scaled_cols = F
+      # )
+      
+      #input$stability_snp_param
+      
+      updateSliderInput(
+        session, 
+        "display_position_range",
+        min = position_min,
+        max = position_max
+        #, value = c(position_min, position_min+150)
+      )
+      updateSliderInput(
+        session,
+        "display_position_full_range",
+        min = 1, 
+        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)
+      
+      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$display_position_range
+      plot_min=display_position_range[1]
+      plot_max=display_position_range[2]
+      
+      display_position_full_range = input$display_position_full_range
+      full_range_min=display_position_full_range[1]
+      full_range_max=display_position_full_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),]
+      
+      
+      
+      #### LogoPlotMSA/Logo Plot ED ####
+      output$LogoPlotMSA = renderPlot(
+        LogoPlotMSA(target=input$switch_target,
+                    plot_positions=full_range_min:full_range_max,
+                    my_logo_col = logoplot_colour_scheme,
+                    aa_pos_drug = aa_pos_drug,
+                    active_aa_pos = active_aa_pos,
+                    aa_pos_lig1 = aa_pos_lig1,
+                    aa_pos_lig2 = aa_pos_lig2,
+                    aa_pos_lig3 = aa_pos_lig3
+        )
+      )
+    }
+  )
+  
+  #### EOF Shiny Server ####
+  
+  
+  
+}
+################ Running Server ##############
+app <- shinyApp(ui, server)
 
 
+runApp(app)
+}
\ No newline at end of file
diff --git a/msa/server.R b/msa/server.R
index e69de29..542fe34 100644
--- a/msa/server.R
+++ b/msa/server.R
@@ -0,0 +1,105 @@
+function(input, output, session) {
+  observeEvent(
+    {
+      input$display_position_full_range #special-purpose for MSA
+      input$logoplot_colour_scheme
+      input$switch_target
+    },
+    {
+      # C O M P A T I B I L I T Y
+      #gene=input$switch_target
+      #drug=target_map[[gene]]
+      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)
+      unified_msa = get(paste0(input$switch_target, '_unified_msa'))
+      # 
+      # # re-sort the dataframe according to position count
+      sorted_df = cbind(merged_df3)
+      sorted_df = sorted_df %>% arrange(pos_count)
+      
+      # 
+      outdir = paste0("~/git/Data/", drug, '/output/')
+      indir  = paste0("~/git/Data/", drug , "/input/")
+      # 
+      # source("~/git/LSHTM_analysis/scripts/plotting/logo_data_msa.R") # probably unnecessary...
+      
+      #  source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
+      
+      #### nasty special-purpose merged_df3 variants ####
+      # FIXME: SLOW
+      # corr_plotdf = corr_data_extract(
+      #   merged_df3
+      #   , gene = gene
+      #   , drug = drug
+      #   , extract_scaled_cols = F
+      # )
+      
+      #input$stability_snp_param
+      
+      updateSliderInput(
+        session, 
+        "display_position_range",
+        min = position_min,
+        max = position_max
+        #, value = c(position_min, position_min+150)
+      )
+      updateSliderInput(
+        session,
+        "display_position_full_range",
+        min = 1, 
+        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)
+      
+      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$display_position_range
+      plot_min=display_position_range[1]
+      plot_max=display_position_range[2]
+      
+      display_position_full_range = input$display_position_full_range
+      full_range_min=display_position_full_range[1]
+      full_range_max=display_position_full_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),]
+      
+      
+      
+      #### LogoPlotMSA/Logo Plot ED ####
+      output$LogoPlotMSA = renderPlot(
+        LogoPlotMSA(target=input$switch_target,
+                    plot_positions=full_range_min:full_range_max,
+                    my_logo_col = logoplot_colour_scheme,
+                    aa_pos_drug = aa_pos_drug,
+                    active_aa_pos = active_aa_pos,
+                    aa_pos_lig1 = aa_pos_lig1,
+                    aa_pos_lig2 = aa_pos_lig2,
+                    aa_pos_lig3 = aa_pos_lig3
+        )
+      )
+    }
+  )
+}
\ No newline at end of file
diff --git a/msa/ui.R b/msa/ui.R
index e69de29..2fe5bc6 100644
--- a/msa/ui.R
+++ b/msa/ui.R
@@ -0,0 +1,62 @@
+dashboardPage(
+  #dashboardHeader(title = paste0(gene, "/", drug)),
+  dashboardHeader(title = "Sequence Alignment"),
+  
+  dashboardSidebar(
+    sidebarMenu( id = "sidebar",
+                 selectInput(
+                   "switch_target",
+                   label="Target",
+                   choices = c(
+                     "alr",
+                     "embb",
+                     "gid",
+                     "katg",
+                     "pnca",
+                     "rpob"
+                   ),
+                   selected="embb"),
+                 menuItem("LogoP ED", tabName="LogoP ED"),
+                 
+                 sliderInput(
+                   "display_position_full_range"
+                   , "Display Positions"
+                   , min=1, max=150, value=c(1,150)
+                 ),
+                 
+                 conditionalPanel(
+                   condition="
+                                  input.sidebar == 'LogoP SNP' ||
+                                  input.sidebar == 'LogoP OR' ||
+                                  input.sidebar == 'LogoP ED'", 
+                   selectInput(
+                     "logoplot_colour_scheme", 
+                     label="Logo Plot Colour Scheme", 
+                     choices = logoPlotSchemes, 
+                     selected="chemistry"
+                   )
+                 )
+    )
+  ),
+  body <- dashboardBody(
+    
+    tabItems(
+      tabItem(tabName = "dashboard",
+              h2("Dashboard tab content")
+      ),
+      
+      tabItem(tabName = "widgets",
+              h2("Widgets tab content")
+      )
+    ),
+    # creates a 'Conditional Panel' containing a plot object from each of our 
+    # ggplot plot functions (and its associated data frame)
+    fluidRow(
+      column(
+        width=12,
+        plotOutput("LogoPlotMSA",
+                   click = "plot_click") %>% withSpinner(color="#0dc5c1")
+      )
+    )
+  )
+)
\ No newline at end of file