Optimize some details

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

@@ -229,7 +229,8 @@ server.modules_pancan_comp_m2o = function(input, output, session) {
 				data = dplyr::inner_join(y_data, group_data) %>%
 					dplyr::select(Sample, value, group, everything()) %>% na.omit()
 				# 检查数据是否合理
-				if(nrow(data)==0 | sd(data$value)==0 | length(unique(data$group))==1) return(c(NaN, NaN, NaN))
+				if(nrow(data)==0 | sd(data$value)==0) return(c(NaN, NaN, NaN))
+				if(length(unique(data$group))==1 | min(table(data$group))<3) return(c(NaN, NaN, NaN))
 
 				if(input$comp_method == "t.test"){
 					comp_obj = t.test(value ~ group, data)

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

@@ -265,7 +265,7 @@ server.modules_pancan_comp_o2m = function(input, output, session) {
 		    merge_data_line() %>%
 		      dplyr::group_by(cancer, group) %>%
 		      dplyr::summarise(n1=n()) %>%
-		      dplyr::filter(n1>=2) %>% # 每小组的样本数大于等于2
+		      dplyr::filter(n1>=3) %>% # 每小组的样本数大于等于3
 		      dplyr::distinct(cancer, group) %>%
 		      dplyr::count(cancer,name = "n2") %>%
 		      dplyr::filter(n2==2) %>% dplyr::pull("cancer") # 每个肿瘤有两组

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

@@ -268,10 +268,10 @@ server.modules_pancan_comp_o2o = function(input, output, session) {
 		shiny::validate(
 			need(try(nrow(merge_data_box())>0), 
 				"Please inspect whether to set groups or download variable data in S2 or S3 step."),
-		)
-		shiny::validate(
 			need(try(length(unique(merge_data_box()$group))==2), 
-				"No enough samples for comparing, please check your input."),
+				"No two groups for comparing, please check your input."),
+			need(try(min(table(merge_data_box()$group))>2),   
+				"No enough samples (n≤3) for one group for comparing, please check your input."),	
 		)
 		merge_data_box = merge_data_box()
 

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

@@ -213,7 +213,7 @@ server.modules_pancan_cor_m2o = function(input, output, session) {
 				xy_data = x_datas %>%
 					dplyr::filter(x_id == L3_x) %>%
 					dplyr::inner_join(y_data) %>% as.data.frame()
-				if(nrow(na.omit(xy_data))==0){return(c(NaN, NaN))}
+				if(nrow(na.omit(xy_data))<3){return(c(NaN, NaN))}
 			    cor_obj = cor.test(xy_data[,"x_value"],xy_data[,"y_value"],
 			                       method = input$cor_method)
 			    incProgress(1 / length(L3s_x()), detail = paste0("(Finished ",i,"/",length(L3s_x()),")"))

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

@@ -253,9 +253,16 @@ server.modules_pancan_cor_o2m = function(input, output, session) {
 		colnames(x_axis_data)[c(1:3,5)] = paste0("x_",colnames(x_axis_data)[c(1:3,5)])
 		y_axis_data = y_axis_data()
 		colnames(y_axis_data)[c(1:3,5)] = paste0("y_",colnames(y_axis_data)[c(1:3,5)])
-
 		data = dplyr::inner_join(x_axis_data, y_axis_data) %>%
 			dplyr::select(cancer, Sample, everything())
+
+		data <- data %>%
+			dplyr::filter(cancer %in% (
+				data %>%
+					dplyr::count(cancer) %>%
+					dplyr::filter(n > 2) %>%
+					dplyr::pull(cancer)
+			))
 		# print(head(data))
 		data
 	})

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

@@ -269,6 +269,8 @@ server.modules_pancan_cor_o2o = function(input, output, session) {
 		shiny::validate(
 			need(try(nrow(merge_data_sct())>0), 
 				"Please inspect whether to get valid data in Step2."),
+			need(try(nrow(merge_data_sct())>2), 
+				"Please adjust to ensure that enough samples (n≥3) are included for analysis.")
 		)
 		p = plot_cor_o2o(
 			data = merge_data_sct(), cor_method = input$cor_method,

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

@@ -264,51 +264,50 @@ 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
 	})
 
 	w <- waiter::Waiter$new(id = ns("x_axis_data_table"), html = waiter::spin_hexdots(), color = "black")
 
-	observeEvent(input$query_data,{
-
-		w$show()
-		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."),
-					)
-					if(check_numeric){
+	# observeEvent(input$query_data,{
+	observe({
+		if (input$query_data>0) {
+			w$show()
+			output$x_axis_data_table = renderUI({
+				if(table.ui){
+					output$x_tmp_table = renderDataTable({
+						# shinyjs::enable("query_data")
 						shiny::validate(
-							need(try(class(download_data()$value)!="character"), 
-								"Please select a numeric variable."),
-						)	
-					}
-					x_axis_data_ = download_data()[,c("Sample","value","cancer")]
-
-					if(class(x_axis_data_[,"value"])=="numeric"){
-						x_axis_data_[,"value"] = round(x_axis_data_[,"value"], digits = 3)
-					}
-					datatable(x_axis_data_, 
-						options = list(pageLength = 3,
-							columnDefs = list(list(className = 'dt-center', targets="_all")))
-					)
-				}) 
-				dataTableOutput(ns("x_tmp_table"))
-			} else {
-				output$x_tmp_table = renderPrint({
-					# ids_num = nrow()
-					cat(paste0("Tip: identifier values of ", nrow(download_data()), " samples are prepared."))
-				})
-				verbatimTextOutput(ns("x_tmp_table"))
-			}
+							need(try(nrow(download_data())>0), 
+								"No sample data  available. Please inspect operations in Preset step."),
+						)
+						if(check_numeric){
+							shiny::validate(
+								need(try(class(download_data()$value)!="character"), 
+									"Please select a numeric variable."),
+							)	
+						}
+						x_axis_data_ = download_data()[,c("Sample","value","cancer")]
 
-		})
-
+						if(class(x_axis_data_[,"value"])=="numeric"){
+							x_axis_data_[,"value"] = round(x_axis_data_[,"value"], digits = 3)
+						}
+						datatable(x_axis_data_, 
+							options = list(pageLength = 3,
+								columnDefs = list(list(className = 'dt-center', targets="_all")))
+						)
+					}) 
+					dataTableOutput(ns("x_tmp_table"))
+				} else {
+					output$x_tmp_table = renderPrint({
+						# ids_num = nrow()
+						cat(paste0("Tip: identifier values of ", nrow(download_data()), " samples are prepared."))
+					})
+					verbatimTextOutput(ns("x_tmp_table"))
+				}
+			})
+		}		
 	})
 
 	# observeEvent(input$query_data,{

inst/shinyapp/utils_appdata.R

@@ -92,7 +92,7 @@ tcga_id_option = list(
     ),
     "TIMER" = list(
       "all" = tcga_id.list[["TIMER"]],
-      "default" = "Monocyte"
+      "default" = "Macrophage"
     ),
     "XCELL" = list(
       "all" = tcga_id.list[["XCELL"]],

inst/shinyapp/utils_plot.R

@@ -97,7 +97,12 @@ plot_comb_o2m = function(data1, data2, x_name, title_name,
 
     p1 = ggplot(data1_sub) +
         stat_summary(aes(x=cancer, y=value, color=group),
-                    position=position_dodge(width=0.5)) +   
+                    # colour = "gray",
+                    position=position_dodge(width=0.5)) + 
+        geom_jitter(aes(x=cancer, y=value, color=group),
+                    position=position_dodge(width=0.5), size = 1, 
+                    # colour = "gray", 
+                    alpha = 0.4) +
         xlab("") + ylab(x_name) + ggtitle(label = title_name) + #转置
 		scale_color_manual(values = c(group_1_color_2, group_2_color_2)) +
         coord_flip() + custom_theme