Solucionando algunos problemas del análisis. Cutoff, ausencia de ID tumor...

invivos/app.R

@@ -345,7 +345,7 @@ server <- function(input, output) {
       observeEvent(analysis$taula_def, {})
       max_val<-max(analysis$taula_def$Volume, na.rm = T)
       # print(max_val)
-      sliderInput("cutoff", "Cutoff para Survival", min=0, max=round(max_val), step=round(max_val)/200, value=max_val)
+      sliderInput("cutoff", "Cutoff para Survival", min=0, max=round(max_val, digits=2), step=round(max_val, digits=2)/200, value=max_val)
     }
   })
   output$ntable<-renderTable({
@@ -360,7 +360,7 @@ server <- function(input, output) {
       if ("ID.tumor" %in% colnames(table)){table<-rename(table, "ID tumor"=`ID.tumor`)}
       # table[table$ID.tumor == "R","0"]<-NA
       col_nodays<-c("ID","Code", "Cage","Group", "ID.animal","ID animal", "ID.tumor", "ID tumor", "TS","DPV", "Absorbance")
-      if (length(grep(0, colnames(table)[!colnames(table) %in% col_nodays])) == 0){
+      if (length(grep(0, colnames(table)[!colnames(table) %in% col_nodays])) == 0 & input$vacc == "Sí"){
         table["0"]<-0
       }
       table<-melt(table, id=colnames(table)[colnames(table) %in% col_nodays], variable.name = "Timepoint")
@@ -474,8 +474,8 @@ server <- function(input, output) {
         
       }else{
         tableR<-table %>% filter(!is.na(Volume))
-        endtime<-dcast(tableR %>% filter(Volume < input$cutoff), `ID animal`+Group~., value.var = "Timepoint", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
-        endtime["Dead"]<-dcast(tableR, `ID animal`+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") > input$cutoff
+        endtime<-dcast(tableR, `ID animal`+`ID tumor`+Group~., value.var = "Timepoint", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
+        endtime["Dead"]<-dcast(tableR, `ID animal`+`ID tumor`+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") >= input$cutoff
         table_tumor<<-endtime
         
         g<-ggsurvplot(survfit(Surv(table_tumor$end, table_tumor$Dead) ~ table_tumor$Group, data=table_tumor),
@@ -497,7 +497,7 @@ server <- function(input, output) {
       table<-analysis$taula_def
       if (input$vacc == "No"){
         table<-filter(table, !is.na(Volume))
-        summary(aov(Volume~Group+Timepoint+Error(`ID animal`), data=table))
+        summary(aov(Volume~Group+Timepoint+Error(`ID animal`+`ID tumor`), data=table))
       }else{
         for (side in c("L","R")){
           tableR<-filter(table, `ID tumor` == side) %>% filter(!is.na(Volume))