Add mutation type to TCGA modules of Cox analysis

openbiox · Sep 10, 2024 · 464005f · 464005f
1 parent 29d0b16
commit 464005f
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Showing 3 changed files with 9 additions and 5 deletions.
diff --git a/R/vis_pancan_value.R b/R/vis_pancan_value.R
@@ -258,10 +258,14 @@ vis_unicox_tree <- function(Gene = "TP53", measure = "OS", data_type = "mRNA", u
     dplyr::inner_join(tcga_surv, by = "sample") %>%
     dplyr::inner_join(tcga_gtex[, c("tissue", "sample")], by = "sample")
   sss <- split(ss, ss$tissue)
+  # discard cancer types with constant values (e.g. all TP53-wild samples)
+  sss = sss[sapply(sss, function(x){stats::sd(x$values)!=0})]
   tissues <- names(sss)
   .f <- function(cancer) {
     sss_can <- sss[[cancer]]
-
+    # By default, cox analysis based on continuous molecule values. HR>0: Higher values, More risky. 
+    # Set use_optimal_cutoff as TRUE: Divide into 2 groups (Low/High) according the optimal cutoff. Then, 
+    ## cox analysis based on discrete molecule groups. HR>0: 'High' Group are more risky.
     if (use_optimal_cutoff) {
       sss_can <- sss_can %>%
         survminer::surv_cutpoint(

diff --git a/inst/shinyapp/modules/02_quick/modules-1-tcga-10-Cox.R b/inst/shinyapp/modules/02_quick/modules-1-tcga-10-Cox.R
@@ -3,7 +3,7 @@ ui.modules_1_tcga_10 = function(id){
 
     main_ui = tagList(
         mol_quick_select_UI(ns("id"), "tcga", 
-            c("mRNA","transcript","methylation","miRNA","protein", "cnv")),
+            c("mRNA","transcript","methylation","miRNA","protein", "cnv", "mutation")),
 
         h4("3. Select TCGA endpoint type"),
         selectInput(ns("measure"), NULL,c("OS", "DSS", "DFI", "PFI")),

diff --git a/inst/shinyapp/modules/03_tcga/modules-pancan-cross-gene-o2m.R b/inst/shinyapp/modules/03_tcga/modules-pancan-cross-gene-o2m.R
@@ -257,11 +257,11 @@ server.modules_pancan_cross_gene_o2m = function(input, output, session) {
 		Sys.sleep(0.5)
 
 		output$step2_2_text = renderPrint({
-			cat(paste0("Tip: (1) mRNA is ", 
+			cat(paste0("Tips: \n(1) mRNA is ", 
 					   ifelse(check_omics$mRNA,"OK; ","missing; "),
-					   "(2) Mutation is ",
+					   "\n(2) Mutation is ",
 					   ifelse(check_omics$mutation,"OK; ","missing; "),
-					   "(2) CNV is ",
+					   "\n(3) CNV is ",
 					   ifelse(check_omics$cnv,"OK.","missing.")
 			))
 		})