diff --git a/drug-target/global.R b/drug-target/global.R index 7f6a06f..1f5b5fb 100644 --- a/drug-target/global.R +++ b/drug-target/global.R @@ -305,771 +305,771 @@ consurf_colours = c( ) # if (true()){ -if (interactive()){ - options(shiny.launch.browser = FALSE) # i am a big girl and can tie my own laces - options(shiny.port = 8000) # don't change the port every time - options(shiny.host = '0.0.0.0') # This means "listen to all addresses on all interfaces" - options(width=120) - options(DT.options = list(scrollX = TRUE)) - #### UI #### - ui <- dashboardPage(skin="purple", - dashboardHeader(title = "Drug/Target Explorer"), - - dashboardSidebar( - sidebarMenu( id = "sidebar", - selectInput( - "switch_target", - label="Switch to New Target", - choices = c( - "alr", - "embb", - "gid", - "katg", - "pnca", - "rpob" - ), - selected="embb"), - menuItem("LogoP SNP", tabName="LogoP SNP"), - #menuItem("Lineage Sample Count", tabName="Lineage Sample Count"), - menuItem("Site SNP count", tabName="Site SNP count"), - menuItem("Stability SNP by site", tabName="Stability SNP by site"), - menuItem("DM OM Plots", tabName="DM OM Plots"), - menuItem("Correlation", tabName="Correlation"), - #menuItem("Lineage Distribution", tabName="Lineage Distribution"), - menuItem("Consurf", tabName="Consurf"), - menuItem("LogoP OR", tabName="LogoP OR"), - menuItem("Lineage", tabName="Lineage"), - #menuItem('Stability count', tabName='Stability count'), - - # These conditionalPanel()s make extra settings appear in the sidebar when needed - conditionalPanel( - condition="input.sidebar == 'LogoP SNP'", - textInput( - "omit_snp_count", - "Omit SNPs", - value = c(0), - placeholder = "1,3,6" - ) - ), - # NOTE: - # I *think* we can cheat here slightly and use the min/max from - # merged_df3[['position']] for everything because the various - # dataframes for a given gene/drug combination have the - # same range of positions. May need fixing, especially - # if we get/shrink the imported data files to something - # more reasonable. - conditionalPanel( - condition=" - input.sidebar == 'LogoP SNP'|| - input.sidebar == 'Stability SNP by site' || - input.sidebar == 'Consurf' || - input.sidebar == 'LogoP OR'", - sliderInput( - "display_position_range" - , "Display Positions" - , min=1, max=150, value=c(1,150) # 150 is just a little less than the smallest pos_count - ) - ), - - 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" - ) - ), - conditionalPanel( - condition="input.sidebar == 'Correlation'", - selectInput( - "corr_method", - label="Correlation Method", - choices = list("spearman", - "pearson", - "kendall"), - selected="spearman" - ) - ), - conditionalPanel( - condition="input.sidebar == 'Correlation'", - numericInput( - "corr_lig_dist" - , "Ligand Distance Cutoff (Å)", value=1 - ) - ), - conditionalPanel( - condition="input.sidebar == 'Site SNP count'", - numericInput( - "snp_ligand_dist" - , "Ligand Distance Cutoff (Å)", value=10 - ) - ), - conditionalPanel( - condition="input.sidebar == 'Site SNP count'", - numericInput( - "snp_interface_dist" - , "Interface Distance Cutoff (Å)", value=10 - ) - ), - conditionalPanel( - condition="input.sidebar == 'Site SNP count'", - numericInput( - "snp_nca_dist" - , "NCA Distance Cutoff (Å)", value=10 - ) - ), - - conditionalPanel( - condition="input.sidebar == 'Correlation'", - checkboxGroupInput( - "corr_selected", - "Parameters", - choiceNames = c( - "DeepDDG", - "Dynamut2", - "FoldX", - "ConSurf"#, - ), - choiceValues = c( - "DeepDDG", - "Dynamut2", - "FoldX", - "ConSurf"#, - ), - selected = c( - "DeepDDG", - "Dynamut2", - "FoldX", - "ConSurf"#, - ) - ) - ), - - # conditionalPanel( - # condition="input.sidebar == 'DM OM Plots'", - # selectInput( - # "dm_om_param", - # label="Stability Parameter", - # choices = keys(dm_om_map), - # selected="SNAP2") - # ), - # colour_categ - conditionalPanel( - condition="input.sidebar == 'Stability SNP by site'", - selectInput( - "stability_snp_param", - label="Stability Parameter", - choices = stability_boxes_df$stability_type, - selected="Average") - ), - conditionalPanel( - condition="input.sidebar == 'Stability SNP by site'", - checkboxInput("reorder_custom_h", - label="Reorder by SNP count", - FALSE) - ), - conditionalPanel( - condition="input.sidebar.match(/^Lineage.*/)", - checkboxInput("all_lineages", - label="All Lineages", - FALSE) - ), - # an example of how you can match multiple things in frontend JS - conditionalPanel( - condition="input.sidebar == 'LogoP SNP' || - input.sidebar =='Stability SNP by site' || - input.sidebar =='Consurf' || - input.sidebar =='LogoP OR'", - actionButton("clear_ngl", - "Clear Structure") - ), - conditionalPanel( - condition="input.sidebar == 'LogoP SNP' || - input.sidebar =='Stability SNP by site' || - input.sidebar =='Consurf' || - input.sidebar =='LogoP OR'", - actionButton("test_ngl", - "Test NGLViewR") - )#, - - # downloadButton("save", - # "Download Plot" - # ) - # actionButton( - # "reload_target", - # label="Reload Target\nData (slow!)" - # ) - - ) - ), - #### body #### - body <- dashboardBody( - - tabItems( - tabItem(tabName = "dashboard", - h2("Dashboard tab content") - ), - - tabItem(tabName = "widgets", - h2("Widgets tab content") - ) - ), - # creates a 'Conditional Panel' containing a plot object from each of our - # ggplot plot functions (and its associated data frame) - fluidRow(column(width=12, - lapply(plot_functions_df$tab_name, - function(x){ - - plot_function=plot_functions_df[ - plot_functions_df$tab_name==x, - "plot_function"] - - plot_df=plot_functions_df[ - plot_functions_df$tab_name==x, - "plot_df"] - cat(paste0('\nCreating output: ', x)) - generate_conditionalPanel(x, plot_function, plot_df) - - } - ) - ) - ), - # Explicit fluidRow() for Lineage plots together - fluidRow( - column(conditionalPanel( - condition="input.sidebar.match(/^Lineage.*/)", box( - title="Lineage Distribution" - , status = "info" - , width=NULL - , plotOutput("lineage_distP", height="700px") %>% withSpinner(color="#0dc5c1"), - height=800 - ) - ), width=6 - ), - column(conditionalPanel( - condition="input.sidebar.match(/^Lineage.*/)", box( - title="Lineage SNP Diversity" - , status = "info" - , width=NULL - , plotOutput("lin_sc", height="700px") %>% withSpinner(color="#0dc5c1"), - height=800 - ) - ), width=6 - ) - - ), - # Explicit fluidRow() for Site SNP Count - fluidRow( - column(conditionalPanel( - condition="input.sidebar == 'Site SNP count'", - box( - title="Site SNP count" - , status = "info" - , width=NULL - , plotOutput("site_snp_count_bp") %>% withSpinner(color="#0dc5c1") - ) - ), width=6 - ), - column(conditionalPanel( - condition="input.sidebar == 'Site SNP count'", - box( - title="Ligand Distance" - , status = "info" - , width=NULL - , plotOutput("site_snp_count_bp_ligand") %>% withSpinner(color="#0dc5c1") - ) - ), width=6 - ), - column(conditionalPanel( - condition="input.sidebar == 'Site SNP count'", - box( - title="Interface Distance" - , status = "info" - , width=NULL - , plotOutput("site_snp_count_interface") %>% withSpinner(color="#0dc5c1") - ) - ), width=6 - ), - column(conditionalPanel( - condition="input.sidebar == 'Site SNP count'", - box( - title="RNA Distance" - , status = "info" - , width=NULL - , plotOutput("site_snp_count_nca") %>% withSpinner(color="#0dc5c1") - ) - ), width=6 - ) - ), - - # # Explicit fluidRow() for Stability Count - # fluidRow( - # column( - # conditionalPanel( - # condition="input.sidebar.match(/^Lineage.*/)", - # lapply( - # # FIXME: using a hardcoded target DF for this IS WRONG AND WILL BREAK - # stability_boxes_df[stability_boxes_df$outcome_colname %in% colnames(embb_merged_df3),"outcome_colname"], - # function(x){ - # print(paste0("outcome_colname: ",x)) - # box(plotOutput(x), width=4) - # } - # ), - # width=12 - # ) - # ) - # ), - - #### fluidRow()s for "Stability Count" in the sidebar #### - fluidRow( - conditionalPanel( - condition=" - input.sidebar == 'LogoP SNP' || - input.sidebar =='Stability SNP by site' || - input.sidebar =='Consurf' || - input.sidebar =='LogoP OR'", - column(NGLVieweROutput("structure"), - width=3 - ) - ), - conditionalPanel( - condition=" - input.sidebar == 'LogoP SNP' || - input.sidebar == 'Stability SNP by site' || - input.sidebar == 'Site SNP count' || - input.sidebar == 'Consurf' || - input.sidebar == 'LogoP OR'", - column( - DT::dataTableOutput('table'), - width=9 - ) - ) - ), - ) - ) - server <- function(input, output, session) { - - #output$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$nca_distance)) - - - # different data ranges required for SNP distances - snp_ligand_dist_df3 = merged_df3[merged_df3[['ligand_distance']]=plot_min & mutable_df3$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) -} +# if (interactive()){ +# options(shiny.launch.browser = FALSE) # i am a big girl and can tie my own laces +# options(shiny.port = 8000) # don't change the port every time +# options(shiny.host = '0.0.0.0') # This means "listen to all addresses on all interfaces" +# options(width=120) +# options(DT.options = list(scrollX = TRUE)) +# #### UI #### +# ui <- dashboardPage(skin="purple", +# dashboardHeader(title = "Drug/Target Explorer"), +# +# dashboardSidebar( +# sidebarMenu( id = "sidebar", +# selectInput( +# "switch_target", +# label="Switch to New Target", +# choices = c( +# "alr", +# "embb", +# "gid", +# "katg", +# "pnca", +# "rpob" +# ), +# selected="embb"), +# menuItem("LogoP SNP", tabName="LogoP SNP"), +# #menuItem("Lineage Sample Count", tabName="Lineage Sample Count"), +# menuItem("Site SNP count", tabName="Site SNP count"), +# menuItem("Stability SNP by site", tabName="Stability SNP by site"), +# menuItem("DM OM Plots", tabName="DM OM Plots"), +# menuItem("Correlation", tabName="Correlation"), +# #menuItem("Lineage Distribution", tabName="Lineage Distribution"), +# menuItem("Consurf", tabName="Consurf"), +# menuItem("LogoP OR", tabName="LogoP OR"), +# menuItem("Lineage", tabName="Lineage"), +# #menuItem('Stability count', tabName='Stability count'), +# +# # These conditionalPanel()s make extra settings appear in the sidebar when needed +# conditionalPanel( +# condition="input.sidebar == 'LogoP SNP'", +# textInput( +# "omit_snp_count", +# "Omit SNPs", +# value = c(0), +# placeholder = "1,3,6" +# ) +# ), +# # NOTE: +# # I *think* we can cheat here slightly and use the min/max from +# # merged_df3[['position']] for everything because the various +# # dataframes for a given gene/drug combination have the +# # same range of positions. May need fixing, especially +# # if we get/shrink the imported data files to something +# # more reasonable. +# conditionalPanel( +# condition=" +# input.sidebar == 'LogoP SNP'|| +# input.sidebar == 'Stability SNP by site' || +# input.sidebar == 'Consurf' || +# input.sidebar == 'LogoP OR'", +# sliderInput( +# "display_position_range" +# , "Display Positions" +# , min=1, max=150, value=c(1,150) # 150 is just a little less than the smallest pos_count +# ) +# ), +# +# 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" +# ) +# ), +# conditionalPanel( +# condition="input.sidebar == 'Correlation'", +# selectInput( +# "corr_method", +# label="Correlation Method", +# choices = list("spearman", +# "pearson", +# "kendall"), +# selected="spearman" +# ) +# ), +# conditionalPanel( +# condition="input.sidebar == 'Correlation'", +# numericInput( +# "corr_lig_dist" +# , "Ligand Distance Cutoff (Å)", value=1 +# ) +# ), +# conditionalPanel( +# condition="input.sidebar == 'Site SNP count'", +# numericInput( +# "snp_ligand_dist" +# , "Ligand Distance Cutoff (Å)", value=10 +# ) +# ), +# conditionalPanel( +# condition="input.sidebar == 'Site SNP count'", +# numericInput( +# "snp_interface_dist" +# , "Interface Distance Cutoff (Å)", value=10 +# ) +# ), +# conditionalPanel( +# condition="input.sidebar == 'Site SNP count'", +# numericInput( +# "snp_nca_dist" +# , "NCA Distance Cutoff (Å)", value=10 +# ) +# ), +# +# conditionalPanel( +# condition="input.sidebar == 'Correlation'", +# checkboxGroupInput( +# "corr_selected", +# "Parameters", +# choiceNames = c( +# "DeepDDG", +# "Dynamut2", +# "FoldX", +# "ConSurf"#, +# ), +# choiceValues = c( +# "DeepDDG", +# "Dynamut2", +# "FoldX", +# "ConSurf"#, +# ), +# selected = c( +# "DeepDDG", +# "Dynamut2", +# "FoldX", +# "ConSurf"#, +# ) +# ) +# ), +# +# # conditionalPanel( +# # condition="input.sidebar == 'DM OM Plots'", +# # selectInput( +# # "dm_om_param", +# # label="Stability Parameter", +# # choices = keys(dm_om_map), +# # selected="SNAP2") +# # ), +# # colour_categ +# conditionalPanel( +# condition="input.sidebar == 'Stability SNP by site'", +# selectInput( +# "stability_snp_param", +# label="Stability Parameter", +# choices = stability_boxes_df$stability_type, +# selected="Average") +# ), +# conditionalPanel( +# condition="input.sidebar == 'Stability SNP by site'", +# checkboxInput("reorder_custom_h", +# label="Reorder by SNP count", +# FALSE) +# ), +# conditionalPanel( +# condition="input.sidebar.match(/^Lineage.*/)", +# checkboxInput("all_lineages", +# label="All Lineages", +# FALSE) +# ), +# # an example of how you can match multiple things in frontend JS +# conditionalPanel( +# condition="input.sidebar == 'LogoP SNP' || +# input.sidebar =='Stability SNP by site' || +# input.sidebar =='Consurf' || +# input.sidebar =='LogoP OR'", +# actionButton("clear_ngl", +# "Clear Structure") +# ), +# conditionalPanel( +# condition="input.sidebar == 'LogoP SNP' || +# input.sidebar =='Stability SNP by site' || +# input.sidebar =='Consurf' || +# input.sidebar =='LogoP OR'", +# actionButton("test_ngl", +# "Test NGLViewR") +# )#, +# +# # downloadButton("save", +# # "Download Plot" +# # ) +# # actionButton( +# # "reload_target", +# # label="Reload Target\nData (slow!)" +# # ) +# +# ) +# ), +# #### body #### +# body <- dashboardBody( +# +# tabItems( +# tabItem(tabName = "dashboard", +# h2("Dashboard tab content") +# ), +# +# tabItem(tabName = "widgets", +# h2("Widgets tab content") +# ) +# ), +# # creates a 'Conditional Panel' containing a plot object from each of our +# # ggplot plot functions (and its associated data frame) +# fluidRow(column(width=12, +# lapply(plot_functions_df$tab_name, +# function(x){ +# +# plot_function=plot_functions_df[ +# plot_functions_df$tab_name==x, +# "plot_function"] +# +# plot_df=plot_functions_df[ +# plot_functions_df$tab_name==x, +# "plot_df"] +# cat(paste0('\nCreating output: ', x)) +# generate_conditionalPanel(x, plot_function, plot_df) +# +# } +# ) +# ) +# ), +# # Explicit fluidRow() for Lineage plots together +# fluidRow( +# column(conditionalPanel( +# condition="input.sidebar.match(/^Lineage.*/)", box( +# title="Lineage Distribution" +# , status = "info" +# , width=NULL +# , plotOutput("lineage_distP", height="700px") %>% withSpinner(color="#0dc5c1"), +# height=800 +# ) +# ), width=6 +# ), +# column(conditionalPanel( +# condition="input.sidebar.match(/^Lineage.*/)", box( +# title="Lineage SNP Diversity" +# , status = "info" +# , width=NULL +# , plotOutput("lin_sc", height="700px") %>% withSpinner(color="#0dc5c1"), +# height=800 +# ) +# ), width=6 +# ) +# +# ), +# # Explicit fluidRow() for Site SNP Count +# fluidRow( +# column(conditionalPanel( +# condition="input.sidebar == 'Site SNP count'", +# box( +# title="Site SNP count" +# , status = "info" +# , width=NULL +# , plotOutput("site_snp_count_bp") %>% withSpinner(color="#0dc5c1") +# ) +# ), width=6 +# ), +# column(conditionalPanel( +# condition="input.sidebar == 'Site SNP count'", +# box( +# title="Ligand Distance" +# , status = "info" +# , width=NULL +# , plotOutput("site_snp_count_bp_ligand") %>% withSpinner(color="#0dc5c1") +# ) +# ), width=6 +# ), +# column(conditionalPanel( +# condition="input.sidebar == 'Site SNP count'", +# box( +# title="Interface Distance" +# , status = "info" +# , width=NULL +# , plotOutput("site_snp_count_interface") %>% withSpinner(color="#0dc5c1") +# ) +# ), width=6 +# ), +# column(conditionalPanel( +# condition="input.sidebar == 'Site SNP count'", +# box( +# title="RNA Distance" +# , status = "info" +# , width=NULL +# , plotOutput("site_snp_count_nca") %>% withSpinner(color="#0dc5c1") +# ) +# ), width=6 +# ) +# ), +# +# # # Explicit fluidRow() for Stability Count +# # fluidRow( +# # column( +# # conditionalPanel( +# # condition="input.sidebar.match(/^Lineage.*/)", +# # lapply( +# # # FIXME: using a hardcoded target DF for this IS WRONG AND WILL BREAK +# # stability_boxes_df[stability_boxes_df$outcome_colname %in% colnames(embb_merged_df3),"outcome_colname"], +# # function(x){ +# # print(paste0("outcome_colname: ",x)) +# # box(plotOutput(x), width=4) +# # } +# # ), +# # width=12 +# # ) +# # ) +# # ), +# +# #### fluidRow()s for "Stability Count" in the sidebar #### +# fluidRow( +# conditionalPanel( +# condition=" +# input.sidebar == 'LogoP SNP' || +# input.sidebar =='Stability SNP by site' || +# input.sidebar =='Consurf' || +# input.sidebar =='LogoP OR'", +# column(NGLVieweROutput("structure"), +# width=3 +# ) +# ), +# conditionalPanel( +# condition=" +# input.sidebar == 'LogoP SNP' || +# input.sidebar == 'Stability SNP by site' || +# input.sidebar == 'Site SNP count' || +# input.sidebar == 'Consurf' || +# input.sidebar == 'LogoP OR'", +# column( +# DT::dataTableOutput('table'), +# width=9 +# ) +# ) +# ), +# ) +# ) +# server <- function(input, output, session) { +# +# #output$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$nca_distance)) +# +# +# # different data ranges required for SNP distances +# snp_ligand_dist_df3 = merged_df3[merged_df3[['ligand_distance']]=plot_min & mutable_df3$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) +# }