Merge pull request #344 from lishensuo/master

Modify some UI details

NEWS.md

@@ -37,8 +37,8 @@ See the [UCSCXenaShiny v2 Book](https://lishensuo.github.io/UCSCXenaShiny_Book/i
 - `.opt_pancan` : Default setting for alternative TPC datasets.
 - `mol_quick_analysis()`: Quick molecule analysis and report generation based on TCGA dataset.
 - `query_tcga_group()`: Group TPC samples by build-in or custom phenotype and support filtering or merging operations.
-- `vis_dim_dist()`: Visualize the distribution difference of TCGA samples after dimension reduction analysis.
-- `vis_identifier_dim_dist()`: Visualize the distribution difference of samples after Molecule Identifier dimension reduction analysis.
+- `vis_dim_dist()`: Visualize the distribution difference of TCGA samples after dimensionality reduction analysis.
+- `vis_identifier_dim_dist()`: Visualize the distribution difference of samples after Molecule Identifier dimensionality reduction analysis.
 - `vis_toil_Mut()`: Visualize molecular profile difference between mutation and wild status of queried gene.
 - `vis_toil_Mut_cancer()`: Visualize molecular profile difference between mutation and wild status of queried gene in Single Cancer Type
 
@@ -50,13 +50,13 @@ See the [UCSCXenaShiny v2 Book](https://lishensuo.github.io/UCSCXenaShiny_Book/i
 
 - General Dataset  Analysis
 
-  - Added one general dimension reduction analysis module.
+  - Added one general dimensionality reduction analysis module.
 
 - Quick TPC Analysis
 
   - Added one module for association analysis between molecule and pathway;
   - Added one module for association analysis between molecule and mutation;
-  - Added one module for dimension reduction analysis.
+  - Added one module for dimensionality reduction analysis.
 
 - Personalized Analysis
 

R/query_general.R

@@ -425,7 +425,11 @@ mol_quick_analysis <- function(molecule, data_type, out_dir = ".", out_report =
   print("##### Step1: Query the moleluce value... #####")
   mol_data <- query_pancan_value(molecule, data_type = data_type, database = "toil")
   if (is.list(mol_data)) mol_data <- mol_data[[1]]
-
+
+  if (all(is.na(mol_data))) {
+    message("All NAs returned, return NULL instead.")
+    return(NULL)
+  }
 
   print(paste0("=== ", "Clinical phenotype"))
   mol_data_df <- suppressMessages(data.frame(

R/vis_dim_dist.R

@@ -1,9 +1,9 @@
-#' Visualize the distribution difference of samples after dimension reduction analysis
+#' Visualize the distribution difference of samples after dimensionality reduction analysis
 #'
 #' @param ids molecular identifiers (>=3)
 #' @param data_type molecular types, refer to query_pancan_value() function
 #' @param group_info two-column grouping information with names 'Sample','Group'
-#' @param DR_method the dimension reduction method
+#' @param DR_method the dimensionality reduction method
 #' @param palette the color setting of RColorBrewer
 #' @param add_margin the marginal plot (NULL, "density", "boxplot")
 #' @param opt_pancan specify one dataset for some molercular profiles

R/vis_identifier_dim_dist.R

@@ -1,4 +1,4 @@
-#' Visualize the distribution difference of samples after Molecule Identifier dimension reduction analysis
+#' Visualize the distribution difference of samples after Molecule Identifier dimensionality reduction analysis
 #'
 #' NOTE: the dataset must be dense matrix in UCSC Xena data hubs.
 #'
@@ -10,7 +10,7 @@
 #' - The second column refers to groups indicated in axis X.
 #' @param samples default is `NULL`, can be common sample names for two datasets.
 #' @param return.data whether to reture the raw meta/matrix data (list) instead of plot
-#' @param DR_method the dimension reduction method
+#' @param DR_method the dimensionality reduction method
 #' @param add_margin the marginal plot (NULL, "density", "boxplot")
 #' @param palette the color setting of RColorBrewer
 #'

inst/shinyapp/helper/cross_pw.md

@@ -33,7 +33,7 @@
 
 
 
-<img src="https://ucscxenashiny-1301043367.cos.ap-shanghai.myqcloud.com/Shiny-figures//helper_cross_pw.png" alt="helper_cross_pw"  width="700"/>
+<img src="https://ucscxenashiny-1301043367.cos.ap-shanghai.myqcloud.com/Shiny-figures/helper_cross_pw.png" alt="helper_cross_pw"  width="700"/>
 
 
 

inst/shinyapp/modules/01_general/modules-ga-dim-distribution.R

@@ -216,7 +216,7 @@ server.modules_ga_dim_distribution <- function(
     show_table <- selected_database_add_url_and_phenotype()
     selectInput(
       inputId = ns("ga_data2_id"),
-      label = "Select dataset for DR(Dimension Reduction):",
+      label = "Select dataset for DR(Dimensionality reduction):",
       choices = c("NONE", unique(show_table$XenaDatasets)),
       selected = "NONE",
       multiple = FALSE

inst/shinyapp/modules/02_quick/modules-1-tcga-11-Dim.R

@@ -182,7 +182,7 @@ ui.modules_1_tcga_11 = function(id){
         box(main_ui,
             width = 5,
             solidHeader = TRUE,
-            title = "Quick TCGA Analysis: Dimension reduction analysis", 
+            title = "Quick TCGA Analysis: Dimensionality reduction analysis", 
             status = "warning",
             background = "gray",
             collapsible = FALSE,

inst/shinyapp/modules/06_tpc_func/modules-z-download-feat.R

@@ -264,7 +264,7 @@ download_feat_Server = function(input, output, session, database = "toil",#id_op
 		x_data$cancer = clinical_phe[,2,drop=T][match(x_data$Sample, clinical_phe$Sample)]
 		x_data = x_data[,c("id","level1","level2","Sample","value","cancer")] %>%
 			dplyr::arrange(cancer,Sample)
-		shinyjs::enable("query_data")
+		# shinyjs::enable("query_data")
 		x_data
 	})
 
@@ -276,6 +276,8 @@ download_feat_Server = function(input, output, session, database = "toil",#id_op
 		output$x_axis_data_table = renderUI({
 			if(table.ui){
 				output$x_tmp_table = renderDataTable({
+					shinyjs::enable("query_data")
+
 					shiny::validate(
 						need(try(nrow(download_data())>0), 
 							"No sample data  available. Please inspect operations in Preset step."),

inst/shinyapp/modules/08_other_page/home-pancan-search.R

@@ -134,7 +134,10 @@ server.home_search_box <- function(input, output, session) {
           Show.P.value = input$pdist_show_p_value,
           Show.P.label = input$pdist_show_p_label
         )
-
+        shiny::validate(
+          need(try(inherits(p,'gg')), 
+            "Error: Please select a valid molecule.")
+        )
         p + cowplot::theme_cowplot() + ggpubr::rotate_x_text(45)
       })
     }
@@ -233,23 +236,31 @@ server.home_search_box <- function(input, output, session) {
   observeEvent(input$report_1, {
     w$show()
     output$tip1 = renderText({
-      paste0("Tip: You now can run step2 or step3. (",
-        format(Sys.time(), "%H:%M:%S"), ")")
+      if(report_1_OK()) {
+        paste0("Tip: You now can run step2 or step3. (",
+          format(Sys.time(), "%H:%M:%S"), ")")
+      } else {
+        "Error: Please exit and select a valid molecule."
+      }
     })
   })
 
-
+  report_1_OK <- reactiveVal(TRUE)
   observeEvent(input$report_1, {    
     time_stamp = format(Sys.time(), "%Y-%m-%d_%H-%M-%S")
     res_dat = mol_quick_analysis(molecule = input$Pancan_search, 
                        data_type = input$Pancan_search_type, 
                        out_dir = tempdir(), out_report = FALSE)
 
+    if(is.null(res_dat)) {
+      report_1_OK(FALSE)
+    } 
+    shiny::validate(
+      need(try(!is.null(res_dat)), 
+        "Error: Please exit and select a valid molecule.")
+    )
 
-
-
-    output$report_2 = downloadHandler(
-
+    output$report_2 = downloadHandler(   
       filename = paste0(time_stamp,"_report.html"),
       content = function(file) {
         tempReport <- file.path(tempdir(), paste0(time_stamp,"_report.Rmd"))

inst/shinyapp/server/modules.R

@@ -22,7 +22,7 @@ observeEvent(req(input$navbar=="TCGA: Survival analysis"),{
   callModule(server.modules_1_tcga_10, "modules_1_tcga_10")
 }, once = TRUE)  
 
-observeEvent(req(input$navbar=="TCGA: Dimension reduction"),{
+observeEvent(req(input$navbar=="TCGA: Dimensionality reduction"),{
   callModule(server.modules_1_tcga_11, "modules_1_tcga_11")
 }, once = TRUE)  
 

inst/shinyapp/shiny-doc/intro_personal_pips.md

@@ -1,5 +1,5 @@
 <center>
-<h1>Personalized TPC pipelines</h1>
+<h1>TPC pipelines</h1>
 </center>
 
 
@@ -30,4 +30,4 @@
 
 
 
-> <font size="5">Tips: The menu of `Custom TPC modules` enable specific and quick  TPC molecular analysis, such as tumor and tomor comparison, molecule and molecule correlation.</font>
+> <font size="5">Tips: The menu of `TPC modules` enable specific and quick  TPC molecular analysis, such as tumor and tomor comparison, molecule and molecule correlation.</font>

inst/shinyapp/shiny-doc/intro_quick_mods.md

@@ -1,5 +1,5 @@
 <center>
-<h1>Custom TPC modules</h1>
+<h1>TPC modules</h1>
 </center>
 
 
@@ -60,5 +60,5 @@
 
 
 
-> <font size="5">Tips: The menu of `Personalized TPC Pipelins` supports more general and personalized TPC molecular analysis, including alternative datasets, precise data preparation and versatile modes.</font>
+> <font size="5">Tips: The menu of `TPC Pipelins` supports more general and personalized TPC molecular analysis, including alternative datasets, precise data preparation and versatile modes.</font>
 

inst/shinyapp/ui/link2advanced.R

@@ -3,10 +3,10 @@ ui.link2advanced <- function() {
     title = "Advanced analysis",
     icon = icon("question-circle"),
 
-    tabPanel(a("Custom T·P·C Modules", 
+    tabPanel(a("T·P·C Modules", 
                href="http://localhost:1498/",
                target="_blank")),
-    # tabPanel(a("Personalized T·P·C Pipelines", 
+    # tabPanel(a("T·P·C Pipelines", 
     #            href="https://lishensuo.github.io/UCSCXenaShiny_Book/",
     #            target="_blank")),
     # tabPanel(a("PharmacoGenomics", 

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

@@ -65,10 +65,10 @@ ui.page_pancan_quick <- function() {
       )
     ),
 
-    tabPanel("TCGA: Dimension reduction",
+    tabPanel("TCGA: Dimensionality reduction",
       tabsetPanel(
         tabPanel(
-          "Dimension reduction",
+          "Dimensionality reduction",
           ui.modules_1_tcga_11("modules_1_tcga_11")
         )
       )