improve ui of TPC analysis and navigation bar (openbiox#338)

R/query_general.R

@@ -180,11 +180,11 @@ query_general_id = function(){
   # pcawg_id_referrence = load_data("pcawg_identifier")
   pcawg_id_referrence = load_data("v2_pcawg_id")
   pcawg_id_option$`Molecular profile` = list(
-       `mRNA Expression` = list(all = sort(v2_pcawg_id$L3[v2_pcawg_id$L2=="Gene"]), default = "TP53"),
-       `Promoter Activity` = list(all = sort(v2_pcawg_id$L3[v2_pcawg_id$L2=="Promoter"]), default = "prmtr.1"),
-       `Gene Fusion` = list(all = sort(v2_pcawg_id$L3[v2_pcawg_id$L2=="Fusion"]), default = "SAMD11"),
-       `miRNA Expression` = list(all = sort(v2_pcawg_id$L3[v2_pcawg_id$L2=="miRNA"]), default = "hsa-let-7a-2-3p"),
-       `APOBEC Mutagenesis` = list(all = sort(v2_pcawg_id$L3[v2_pcawg_id$L2=="Muta"]), default = "A3A_or_A3B")
+       `mRNA Expression` = list(all = sort(pcawg_id_referrence$L3[pcawg_id_referrence$L2=="Gene"]), default = "TP53"),
+       `Promoter Activity` = list(all = sort(pcawg_id_referrence$L3[pcawg_id_referrence$L2=="Promoter"]), default = "prmtr.1"),
+       `Gene Fusion` = list(all = sort(pcawg_id_referrence$L3[pcawg_id_referrence$L2=="Fusion"]), default = "SAMD11"),
+       `miRNA Expression` = list(all = sort(pcawg_id_referrence$L3[pcawg_id_referrence$L2=="miRNA"]), default = "hsa-let-7a-2-3p"),
+       `APOBEC Mutagenesis` = list(all = sort(pcawg_id_referrence$L3[pcawg_id_referrence$L2=="Muta"]), default = "A3A_or_A3B")
     )
   pcawg_id_option$`Tumor index` = list(
        `Tumor Purity` = list(all = c("purity", "ploidy", "purity_conf_mad", "wgd_status", "wgd_uncertain"), 
@@ -201,10 +201,10 @@ query_general_id = function(){
   # ccle_id_referrence = load_data("ccle_identifier")
   ccle_id_referrence = load_data("v2_ccle_id")
   ccle_id_option$`Molecular profile` = list(
-       `mRNA Expression` = list(all = sort(v2_pcawg_id$L3[v2_pcawg_id$L2=="Gene"]), default = "TP53"),
-       `Protein Expression` = list(all = sort(v2_ccle_id$L3[v2_ccle_id$L2=="Protein"]), default = "14-3-3_beta"),
-       `Copy Number Variation` = list(all = sort(v2_pcawg_id$L3[v2_pcawg_id$L2=="Gene"]), default = "TP53"),
-       `Mutation status` = list(all = sort(v2_pcawg_id$L3[v2_pcawg_id$L2=="Gene"]), default = "TP53")
+       `mRNA Expression` = list(all = sort(ccle_id_referrence$L3[ccle_id_referrence$L2=="Gene"]), default = "TP53"),
+       `Protein Expression` = list(all = sort(ccle_id_referrence$L3[ccle_id_referrence$L2=="Protein"]), default = "14-3-3_beta"),
+       `Copy Number Variation` = list(all = sort(ccle_id_referrence$L3[ccle_id_referrence$L2=="Gene"]), default = "TP53"),
+       `Mutation status` = list(all = sort(ccle_id_referrence$L3[ccle_id_referrence$L2=="Gene"]), default = "TP53")
     )
   ccle_id_option$`Tumor index` = list(
        `Tumor Purity` = list(all = c("Purity", "Ploidy", "Genome Doublings", "Lineage"), 

R/vis_pancan_value.R

@@ -1166,13 +1166,13 @@ vis_gene_cor_cancer <- function(Gene1 = "CSF1R",
     dplyr::distinct(.data$sample, .keep_all = TRUE)
 
   t1 <- query_pancan_value(Gene1, data_type = data_type1, opt_pancan = opt_pancan)
-  if (is.null(t1[[1]])) {
+  if (length(na.omit(t1[[1]]))==0) {
     warning("No data available", immediate. = TRUE)
     return(NULL)
   }
   if (is.list(t1)) t1 <- t1[[1]]
   t3 <- query_pancan_value(Gene2, data_type = data_type2, opt_pancan = opt_pancan)
-  if (is.null(t3[[1]])) {
+  if (length(na.omit(t1[[3]]))==0) {
     warning("No data available", immediate. = TRUE)
     return(NULL)
   }

inst/shinyapp/App.R

@@ -32,11 +32,11 @@ ui <- tagList(
     # inst/shinyapp/ui
     ui.page_home(),
     ui.page_repository(),
-    ui.page_general_analysis(),
     ui.page_pancan_quick(),
     ui.page_pancan_tcga(),
-    ui.page_PharmacoGenomics(),
+    ui.page_general_analysis(),
     ui.page_download(),
+    ui.page_PharmacoGenomics(),
     ui.page_help(),
     ui.page_developers(),
     footer = ui.footer(),

inst/shinyapp/modules/02_quick/modules-1-tcga-03-Cor.R

@@ -155,6 +155,7 @@ server.modules_1_tcga_03 = function(input, output, session){
             color = input$color,
             alpha = input$alpha
         )
+        if(is.null(p)){return(NULL)}
         p <- p + themes_list[[input$theme]] +
                 theme(text = element_text(size = 20),
                     legend.position = "none")

inst/shinyapp/modules/02_quick/modules-1-tcga-09-KM.R

@@ -146,10 +146,19 @@ server.modules_1_tcga_09 = function(input, output, session){
             load_data("tcga_surv"),
             by = "sample"
         )
+
         dat1 = tcga_surv_get(
             TCGA_cohort = input$Cancer, item = mol_info$molecule(),
             profile = mol_info$profile(), TCGA_cli_data = TCGA_cli_merged
         )
+        if(is.null(dat1)){dat1 = data.frame(
+                                    sampleID=NA, value=NA, 
+                                    OS=NA, OS.time=NA, 
+                                    DSS=NA, DSS.time=NA, 
+                                    DFI=NA, DFI.time=NA, 
+                                    PFI=NA, PFI.time=NA, 
+                                    gender=NA, age=NA, stage=NA)
+        } 
         # filter
         dat2 = dat_filter(data = dat1, age = input$age,
                           gender = input$sex, stage = input$stage, 
@@ -159,6 +168,10 @@ server.modules_1_tcga_09 = function(input, output, session){
 
 
     tips = eventReactive(input$submit_bt, {
+		shiny::validate(
+			need(try(nrow(sur_dat())>0), 
+				"Error: Please select a valid molecule.")
+		)
         if(mol_info$profile() == "mutation"){
             sur_dat2 = sur_dat() %>%
                     dplyr::mutate(group = value)
@@ -197,14 +210,12 @@ server.modules_1_tcga_09 = function(input, output, session){
 
     output$msg = renderPrint({cat(tips())})
 
-
-
-
     plot_func = eventReactive(input$submit_bt, {
         req(grep("Note", tips()))
         id <- showNotification(h3("The task is running..."), duration = NULL, closeButton = FALSE, type = "message")
         on.exit(removeNotification(id), add = TRUE)  #reactive语句执行完毕时，运行remove命令
         cutoff_mode = ifelse(input$groupby=="Optimal cutoff","Auto","Custom")
+
         p <- tcga_surv_plot(sur_dat(),
                             cutoff_mode = cutoff_mode, #"Custom",
                             cutpoint = c(50, 50),
@@ -218,6 +229,7 @@ server.modules_1_tcga_09 = function(input, output, session){
     w <- waiter::Waiter$new(id = ns("surplot"), html = waiter::spin_hexdots(), color = "black")
     observeEvent(input$submit_bt,{
         shinyjs::disable("submit_bt")
+
         output$surplot <- renderUI({
             w$show()
             output$plot = renderPlot(plot_func())

inst/shinyapp/modules/02_quick/modules-1-tcga-10-Cox.R

@@ -101,13 +101,15 @@ server.modules_1_tcga_10 = function(input, output, session){
     plot_func = eventReactive(input$search_bttn, {
         id <- showNotification(h3("The task is running..."), duration = NULL, closeButton = FALSE, type = "message")
         on.exit(removeNotification(id), add = TRUE)  #reactive语句执行完毕时，运行remove命令
+
         p <- vis_unicox_tree(
             Gene = mol_info$molecule(),
             measure = input$measure,
             threshold = 0.5,
             data_type = mol_info$profile(),
             values = c(input$first_col, input$second_col, input$third_col)
         )
+        if(is.null(p)){return(NULL)}
         pdata <- p$data %>% 
             as.data.frame() %>%
             dplyr::select(cancer, measure, n_contrast, n_ref, beta, HR_log, lower_95_log, upper_95_log, Type, p.value)

inst/shinyapp/modules/03_tcga/modules-pancan-comp-m2o.R

@@ -88,7 +88,7 @@ ui.modules_pancan_comp_m2o = function(id) {
 					h4(strong("S3.1 Set analysis parameters")), 
 					# br(),br(),
 					# h4("1. Set method"),
-					selectInput(ns("comp_method"), "Correlation method:",choices = c("t.test", "wilcox.test")),
+					selectInput(ns("comp_method"), "Comparison method:",choices = c("wilcox.test", "t.test"),selected="wilcoxon"),
 					shinyWidgets::actionBttn(
 						ns("cal_batch_comp"), "Run",
 				        style = "gradient",

inst/shinyapp/modules/03_tcga/modules-pancan-comp-o2m.R

@@ -91,7 +91,7 @@ ui.modules_pancan_comp_o2m = function(id) {
 					style = "height:1100px",
 
 					h4(strong("S3.1 Set analysis parameters")),
-					selectInput(ns("comp_method"), "Comparison method:",choices = c("t-test", "wilcoxon")),
+					selectInput(ns("comp_method"), "Comparison method:",choices = c("wilcoxon","t-test"),selected="wilcoxon"),
 					shinyWidgets::actionBttn(
 						ns("step3_plot_line_1"), "Run (Calculate)",
 				        style = "gradient",

inst/shinyapp/modules/03_tcga/modules-pancan-comp-o2o.R

@@ -87,7 +87,7 @@ ui.modules_pancan_comp_o2o = function(id) {
 					                   content = "analyze_comp_1"),  
 					style = "height:1100px",
 					h4(strong("S3.1 Set analysis parameters")), 
-					selectInput(ns("comp_method"), "Comparison method:",choices = c("wilcoxon","t-test")),
+					selectInput(ns("comp_method"), "Comparison method:",choices = c("wilcoxon","t-test"),selected="wilcoxon"),
 
 					h4(strong("S3.2 Set visualization parameters")), 
 					fluidRow(

inst/shinyapp/modules/03_tcga/modules-pancan-cor-m2o.R

@@ -86,7 +86,7 @@ ui.modules_pancan_cor_m2o = function(id) {
 					                   content = "analyze_cor_3"),  
 
 					h4(strong("S3.1 Set analysis parameters")), 
-					selectInput(ns("cor_method"),"Correlation method:",choices = c("pearson", "spearman")),
+					selectInput(ns("cor_method"),"Correlation method:",choices = c("spearman","pearson"), selected="Spearman"),
 					shinyWidgets::actionBttn(
 						ns("cal_batch_cor"), "Run",
 				        style = "gradient",

inst/shinyapp/modules/03_tcga/modules-pancan-cor-o2m.R

@@ -91,7 +91,7 @@ ui.modules_pancan_cor_o2m = function(id) {
 					style = "height:1100px",
 					h4(strong("S3.1 Set analysis parameters")), 
 					# br(),
-					selectInput(ns("cor_method"), "Correlation method:",choices = c("Pearson", "Spearman")),
+					selectInput(ns("cor_method"), "Correlation method:",choices = c("Spearman","Pearson"), selected="Spearman"),
 					shinyWidgets::actionBttn(
 						ns("step3_plot_bar_1"), "Run (Calculate)",
 				        style = "gradient",

inst/shinyapp/modules/03_tcga/modules-pancan-cor-o2o.R

@@ -90,7 +90,7 @@ ui.modules_pancan_cor_o2o = function(id) {
 					                   content = "analyze_cor_1"),  
 					style = "height:1100px",
 					h4(strong("S3.1 Set analysis parameters")), 
-					selectInput(ns("cor_method"), "Correlation method:",choices = c("Spearman", "Pearson")),
+					selectInput(ns("cor_method"), "Correlation method:",choices = c("Spearman", "Pearson"),selected="Spearman"),
 					h4(strong("S3.2 Set visualization parameters")), 
 					fluidRow(
 						column(3, colourpicker::colourInput(inputId = ns("line_color"), "Line color:", "#0000FF")),

inst/shinyapp/server/general-analysis.R

@@ -143,7 +143,7 @@ output$ga_dataset_table <- DT::renderDataTable(
 
 
 # Individual analysis pages -------------------------------------------------------------
-observeEvent(req(input$navbar=="General Dataset Analysis"),{
+observeEvent(req(input$navbar=="General Analysis"),{
   callModule(
     server.modules_ga_scatter_correlation, "module_ga_scatter_correlation",
     selected_database_rm_phenotype, selected_database_add_url_and_phenotype,

inst/shinyapp/server/modules.R

@@ -63,14 +63,6 @@ observeEvent(req(input$navbar=="CCLE: Drug analysis"),{
 html_spin = tagList(spin_1(), br(),
                     h2("Loading (Only needed for the first time)"))
 # TCGA pancan
-observeEvent(req(input$navbar=="TCGA: Cross-Omics Analysis"),{
-    waiter <- waiter::Waiter$new(color = "grey", fadeout = TRUE, html = html_spin)
-    waiter$show()
-		callModule(server.modules_pancan_cross_gene_o2m, "modules_pancan_cross_gene_o2m")
-		callModule(server.modules_pancan_cross_pw_o2m, "modules_pancan_cross_pw_o2m")
-    on.exit(waiter$hide())
-}, once = TRUE)  
-
 observeEvent(req(input$navbar=="TCGA: Correlation Analysis"),{
     waiter <- waiter::Waiter$new(color = "grey", fadeout = TRUE, html = html_spin)
     waiter$show()
@@ -98,7 +90,13 @@ observeEvent(req(input$navbar=="TCGA: Survival Analysis"),{
     on.exit(waiter$hide())
 }, once = TRUE)  
 
-
+observeEvent(req(input$navbar=="TCGA: Cross-Omics Analysis"),{
+    waiter <- waiter::Waiter$new(color = "grey", fadeout = TRUE, html = html_spin)
+    waiter$show()
+		callModule(server.modules_pancan_cross_gene_o2m, "modules_pancan_cross_gene_o2m")
+		callModule(server.modules_pancan_cross_pw_o2m, "modules_pancan_cross_pw_o2m")
+    on.exit(waiter$hide())
+}, once = TRUE)  
 
 # PCAWG 
 observeEvent(req(input$navbar=="PCAWG: Correlation Analysis"),{

inst/shinyapp/server/repository.R

@@ -401,7 +401,7 @@ observeEvent(input$show_R_code, {
 
 # ref: https://stackoverflow.com/questions/38706965/is-there-any-way-for-an-actionbutton-to-navigate-to-another-tab-within-a-r-shi
 observeEvent(input$analyze_data, {
-  updateNavbarPage(session = session, inputId = "navbar", selected = "General Dataset Analysis")
+  updateNavbarPage(session = session, inputId = "navbar", selected = "General Analysis")
 })
 
 # Show alert info when select rows from table -----------------------------

inst/shinyapp/shiny-doc/intro_personal_pips.md

@@ -3,15 +3,15 @@
 </center>
 
 
-<font size="5">Here, we introduced a series of personalized TPC pipelines for comprehensive and precise TPC molecule exploration with various operations.  In general, 8 panels for common analytical scenario are available, as follows:</font>
+<font size="5">Here, we introduced a series of personalized TPC pipelines for comprehensive and precise TPC molecule exploration with various operations.  In general, 9 panels for common analytical scenario are available, as follows:</font>
 
 
 <center>
-<img src="https://raw.githubusercontent.com/lishensuo/images2/main/img01/image-20240413163342892.png" alt="image-20240413163342892"  style="zoom:50%";/>
+<img src="https://raw.githubusercontent.com/lishensuo/images2/main/img01/image-20240708162416954.png" alt="image-20240413163342892"  style="zoom:50%";/>
 </center>
 
 
-<font size="5">Each analytical pipeline comprises of three main subpanels (S1, S2, S3).</font>
+<font size="5">Generally, each analytical pipeline comprises of three main subpanels (S1, S2, S3).</font>
 
 - <font size="5">In S1 subpanel, you can prepare and select the expected data and sample ranges;</font>
 - <font size="5">In S2 subpanel, you can fetch the specific tumor data for downstream analysis;</font>

inst/shinyapp/ui/general-analysis.R

@@ -12,7 +12,7 @@ ui.page_general_analysis <- function() {
   #   #          ui.sg.pancan.analysis("sg.pancan.analysis"))
   # )
   tabPanel(
-    title = "General Dataset Analysis",
+    title = "General Analysis",
     icon = icon("angle-double-down"),
     fluidRow(
       column(

inst/shinyapp/ui/pancan-analysis-quick.R

@@ -1,6 +1,6 @@
 ui.page_pancan_quick <- function() {
   navbarMenu(
-    title = "Custom T·P·C Modules",
+    title = "T·P·C Modules",
     icon = icon("buromobelexperte"),
 
     tabPanel(

inst/shinyapp/ui/pancan-analysis-tpc.R

@@ -1,6 +1,6 @@
 ui.page_pancan_tcga <- function() {
   navbarMenu(
-    title = "Personalized T·P·C Pipelines",
+    title = "T·P·C Pipelines",
     icon = icon("buromobelexperte"),
     tabPanel(
       "Introduction",