Análisis-Randomización. Evitar la desaparición de ratones sin grupo (excluidos).

invivos/app.R

@@ -48,6 +48,7 @@ ui <- fluidPage(
                          checkboxInput("filter_stats","Filtrar Estadística"),
                          checkboxInput("increase_volume","Usar Incremento de Volumen"),
                          checkboxInput("operated","Cortar al operar", value = TRUE),
+                         checkboxInput("dead","Eliminar ratones muertos", value = FALSE),
                          downloadButton("downloadVolume", "Descargar Volúmenes")
                        ),
                        mainPanel(
@@ -120,12 +121,22 @@ server <- function(input, output) {
       }
       table$Date<-format(table$Date, format="%d/%m/%Y")
       if ("sex" %in% colnames(table)){table<-select(table, -sex)}
-      for (i in 1:nrow(table)){
+      if ("Abs" %in% colnames(table)){
-        long<-as.numeric(gsub(",",".",strsplit(as.character(table[i,"Long"]),"+", fixed = T)[[1]]))
+        table<-rename(table, "Volume"="Abs")
-        wide<-as.numeric(gsub(",",".",strsplit(as.character(table[i,"Wide"]),"+", fixed = T)[[1]]))
+      }else{
-        table[i,"Volume"]<-sum(sapply(1:length(long), function(x) (long[x]*wide[x]*wide[x])*(pi/6)))
+        for (i in 1:nrow(table)){
+          long<-as.numeric(gsub(",",".",strsplit(as.character(table[i,"Long"]),"+", fixed = T)[[1]]))
+          wide<-as.numeric(gsub(",",".",strsplit(as.character(table[i,"Wide"]),"+", fixed = T)[[1]]))
+          table[i,"Volume"]<-sum(sapply(1:length(long), function(x) (long[x]*wide[x]*wide[x])*(pi/6)))
+        }
+        table$Volume<-as.numeric(table$Volume)
       }
-      table$Volume<-as.numeric(table$Volume)
+
+      if ("Cage" %in% colnames(table)){
+        table$Animal<-paste0(table$Cage, table$Animal)
+        table<-table[,-which(colnames(table) == "Cage")]
+      }
+      
       dades$taula<-table
       dades$groups<-read.xlsx(input$file_sizes$datapath, sheet = "Groups", colNames=F)[,1]
       if (readxl::excel_sheets(input$file_sizes$datapath) %>% length > 2){
@@ -187,8 +198,8 @@ server <- function(input, output) {
   
   grafic<-eventReactive(input$goButton,{
     df<-dades$taula %>% filter(DayPostInoc == input$day_vol)
-    print(df)
     df<-df[!is.na(df$Volume),]
+    print(df)
     up_cuttof<-input$upcut
     low_cuttof<-input$lowcut
 
@@ -217,7 +228,6 @@ server <- function(input, output) {
         while(interr == T){
           ind<-sample(rep(dades$groups, each=ceiling(length(unique(df_sex$Animal))/ngroup)), length(unique(df_sex$Animal)))
           df_sex<-merge(df_sex[,c("Animal", "Side","Volume")], data.frame("Animal"=unique(df_sex$Animal), "group"=as.factor(ind),check.names=F))
-          print(df_sex)
           if ((nrow(df_sex)/ngroup) %% 2 == 0){
             interr<-any(table(df_sex$group) < floor(nrow(df_sex)/ngroup) | table(df_sex$group) > ceiling(nrow(df_sex)/ngroup))  
           }else{
@@ -238,20 +248,21 @@ server <- function(input, output) {
         }
       }
       index<-which(unlist(lvn.list) == min(unlist(lvn.list)[which(unlist(pval.list) %in% sort(unlist(pval.list), decreasing = T)[1:20])]))[1]
-      # print(df_sex)
       df_def[[sex.var]]<-merge(df_sex %>% select(-group), ind.list[[index]])
     }
     df_def<-do.call(rbind, c(df_def, make.row.names=F))
-    # lapply(df_def, function(x) x %>% as_tibble %>% print(n=Inf))
+
-    # df_def<-rbind(df_def[[1]], df_def[[2]], make.row.names=F)
     if ("Group" %in% colnames(df_def)){
       df_def<-df_def %>% select(-"Group") 
     }
+
     df_def<-merge(
-      if(!is.null(dades$sex)){merge(dades$taula %>% filter(DayPostInoc == input$day_vol), dades$sex)}else{
+      if(!is.null(dades$sex)){merge(dades$taula %>% filter(DayPostInoc == input$day_vol), dades$sex)%>% select(-Group)}else{
         dades$taula %>% filter(DayPostInoc == input$day_vol) %>% add_column(sex="undefined")} %>% select(-Group), 
-      df_def[,c("Animal", "group")] %>% unique, all=T, by="Animal") %>% rename(Group=group)
+      df_def[,c("Animal", "group")] %>% unique, all=T, by="Animal")
-    df_def<-select(df_def, Cage, Animal, Date, DayPostInoc, Group, Side, Weight, Long, Wide, Volume, Observations)
+    df_def<-df_def %>% rename(Group=group)
+    
+    df_def<-select(df_def, Animal, sex, Date, DayPostInoc, Group, Side, Weight, Long, Wide, Volume, Observations)
     # if("DPV" %in% colnames(df_def)){df_def<-select(df_def, c(`ID animal`, `sex`,`ID tumor`, Volume, Cage, Major, Minor, group))}
     # if("TS-Deep" %in% colnames(df_def)){df_def<-select(df_def, c(`ID animal`, `sex`,`ID tumor`, Volume, Cage, `TS-Deep`,`TS-Length`,`TS-Width`, group))}
     
@@ -321,12 +332,15 @@ server <- function(input, output) {
       # timepoint<-c(7,10,13,16,19,22,25)
       
       if (!is.null(input$file_sizes)){
-        template<-dades$db %>% filter(!is.na(Group)) %>% 
+        template<-dades$db %>%
           select(Animal, Group) %>% unique()
         dtemplate<-merge(dades$taula %>% select(-Group), template) %>% 
           arrange(DayPostInoc, Animal, Side) %>% 
-          select(Cage, Animal, Date, DayPostInoc, Group, Side, 
+          select(Animal, Date, DayPostInoc, Group, Side, 
                  Weight, Long, Wide, Volume, Observations)
+        if ("Abs" %in% colnames(read.xlsx(input$file_sizes$datapath, sheet = 1, check.names = F, sep.names = " ", detectDates = T,cols=1:11))){
+          dtemplate<-rename(dtemplate, "Abs"="Volume")
+        }
       }else{
         
         template<-data.frame(
@@ -342,6 +356,7 @@ server <- function(input, output) {
           Volume="",
           Observations=""
         )
+        template<-template %>% mutate(Animal=paste0(Cage,Animal)) %>% select(-Cage)
         dtemplate<-template
       }
       write.xlsx(list("Measures"=dtemplate, "Groups"=NULL,"Sex"=NULL), file)
@@ -378,6 +393,10 @@ server <- function(input, output) {
         table[i,"Volume"]<-sum(sapply(1:length(long), function(x) (long[x]*wide[x]*wide[x])*(pi/6)))
       }
       table$Volume<-as.numeric(table$Volume)
+      if ("Cage" %in% colnames(table)){
+        table$Animal<-paste0(table$Cage, table$Animal)
+        table<-table[,-which(colnames(table) == "Cage")]
+      }
       
       ## Autocompletado de grupo
       table_group<-merge(
@@ -389,16 +408,28 @@ server <- function(input, output) {
         table %>% select(-Group),
         table_group
       ) %>% relocate(Group, .after = DayPostInoc) %>% 
-        relocate(Cage, .before = Animal) %>% 
         arrange(DayPostInoc, Animal, Side)
       
       if("Groups" %in% readxl::excel_sheets(input$file_analy$datapath)){
         levels<-read.xlsx(input$file_analy$datapath, sheet = "Groups", colNames=F)[,1]
-        print(levels)
         table$Group<-factor(table$Group, levels=levels)
         table<-filter(table, !is.na(Group))
       }else(table$Group<-factor(table$Group))
-      print(str(table))
+      
+      
+      if (input$increase_volume){
+        cols<-colnames(table)
+        timepoints<-unique(table$DayPostInoc)
+        table_old<-select(table, -Volume)
+        table_vols<-table %>% 
+          select(-Weight, -Date, -Long, -Wide,-Observations) %>% 
+          spread(DayPostInoc, Volume) %>% 
+          mutate(across(all_of(as.character(timepoints)), function(x){(x*100/`0`)-100})) %>%
+          gather(DayPostInoc, Volume, all_of(as.character(timepoints))) %>% 
+          mutate(Volume=case_when(Volume < 0 ~ 0, T~Volume))
+        table<-merge(table_old, table_vols)[,cols]
+      }
+      
       analysis$taula<-table
     }
   })
@@ -406,7 +437,6 @@ server <- function(input, output) {
     if (!is.null(analysis$taula)){
       observeEvent(analysis$taula, {})
       max_val<-max(analysis$taula$Volume, na.rm = T)
-      # print(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)
     }
   })
@@ -418,17 +448,10 @@ server <- function(input, output) {
 
       table<-analysis$taula
       table<-table %>% filter(!is.na(Group))
-      if (input$increase_volume){
-        timepoints<-unique(table$Timepoint)
-        table<-table %>% select(-Major, -Minor) %>% 
-          spread(Timepoint, Volume) %>% 
-          mutate(across(all_of(timepoints), function(x){(x*100/`0`)-100})) %>%
-          gather(Timepoint, Volume, -Cage, -`ID animal`, -`ID tumor`, -Group) %>% 
-          mutate(Volume=case_when(Volume < 0 ~ 0, T~Volume))
-      }
       table %>% group_by(Group, DayPostInoc, Side) %>% count() %>% spread(DayPostInoc, n)
     }
   })
+  
   output$cin_group<-renderPlot({
     if (!is.null(input$file_analy) & !is.null(analysis$taula)){
       observeEvent(analysis$taula, {})
@@ -438,7 +461,6 @@ server <- function(input, output) {
       sides<-unique(table$Side)
       groups<-table %>% select(Animal, Group) %>% unique() %>% pull(Group)
       basal<-data.frame(
-        Cage="",
         Animal=rep(animals, each=length(sides)),
         Date="",
         DayPostInoc=0,
@@ -450,17 +472,25 @@ server <- function(input, output) {
         Volume=0,
         Observations=""
       )
-      table<-rbind(table, basal)
+      if (!(0 %in% table$DayPostInoc) | sum(table[table$DayPostInoc == 0,"Volume"],na.rm = T) == 0){
+        table<-rbind(table, basal)  
+      }
       
       if (input$vacc == "Sí"){
         firstoper<- filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "*") %>% 
           select(DayPostInoc, Side) %>% unique() %>% 
           group_by(Side) %>% summarise(FirstOper=min(DayPostInoc))
+        deadmice<-filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "+") %>% 
+          pull(Animal)
 
-        if (input$operated == TRUE){
+        if (input$operated == TRUE & nrow(firstoper) > 0){
           for (i in 1:nrow(firstoper)){
             table<-table %>% filter(DayPostInoc < firstoper$FirstOper[i] | Side != firstoper$Side[i])
           } 
+        }else{
+          if(input$dead == TRUE){
+            table<-table %>% filter(!Animal %in% deadmice)
+          }
         }
 
         ggplot(table, aes(DayPostInoc, Volume, color=Group, group=Group))+
@@ -476,10 +506,16 @@ server <- function(input, output) {
 
         firstoper<- filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "*") %>% 
           pull(DayPostInoc) %>% min(na.rm = T)
-        print(firstoper)
+        if (firstoper == Inf){firstoper<-c()}
         
-        if (input$operated == TRUE){
+        if (input$operated == TRUE & length(firstoper) > 0){
           table<-table %>% filter(DayPostInoc < firstoper)
+        }else{
+          deadmice<-filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "+") %>% 
+            pull(Animal)
+          if(input$dead == TRUE){
+            table<-table %>% filter(!Animal %in% deadmice)
+          }
         }
 
         ggplot(table, aes(DayPostInoc, Volume, color=Group, group=Group))+
@@ -503,7 +539,6 @@ server <- function(input, output) {
       sides<-unique(table$Side)
       groups<-table %>% select(Animal, Group) %>% unique() %>% pull(Group)
       basal<-data.frame(
-        Cage="",
         Animal=rep(animals, each=length(sides)),
         Date="",
         DayPostInoc=0,
@@ -515,9 +550,25 @@ server <- function(input, output) {
         Volume=0,
         Observations=""
       )
-      table<-rbind(table, basal)
+      if (!(0 %in% table$DayPostInoc) | sum(table[table$DayPostInoc == 0,"Volume"],na.rm = T) == 0){
+        table<-rbind(table, basal)  
+      }
       
       if (input$vacc == "Sí"){
+        firstoper<- filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "*") %>% 
+          select(DayPostInoc, Side) %>% unique() %>% 
+          group_by(Side) %>% summarise(FirstOper=min(DayPostInoc))
+        if (input$operated == TRUE & nrow(firstoper) > 0){
+          for (i in 1:nrow(firstoper)){
+            table<-table %>% filter(DayPostInoc < firstoper$FirstOper[i] | Side != firstoper$Side[i])
+          } 
+        }else{
+          if(input$dead == TRUE){
+            deadmice<-filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "+") %>% 
+              pull(Animal)
+            table<-table %>% filter(!Animal %in% deadmice)
+          }
+        }
         ggplot(table, aes(DayPostInoc, Volume, color=Group, group=Animal))+
           # geom_errorbar(stat="summary", width=0.05)+
           geom_line()+
@@ -528,6 +579,19 @@ server <- function(input, output) {
           labs(x="Days after tumor inoculation")+
           theme_bw()  
       }else{
+        firstoper<- filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "*") %>% 
+          pull(DayPostInoc) %>% min(na.rm = T)
+        if (firstoper == Inf){firstoper<-c()}
+        
+        if (input$operated == TRUE & length(firstoper) > 0){
+          table<-table %>% filter(DayPostInoc < firstoper)
+        }else{
+          deadmice<-filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "+") %>% 
+            pull(Animal)
+          if(input$dead == TRUE){
+            table<-table %>% filter(!Animal %in% deadmice)
+          }
+        }
         ggplot(table, aes(DayPostInoc, Volume, color=Group, group=paste0(Animal, Side)))+
           # geom_errorbar(stat="summary", width=0.05)+
           geom_line()+
@@ -547,14 +611,29 @@ server <- function(input, output) {
       observeEvent(analysis$taula, {})
       table<-analysis$taula
       if (input$vacc == "Sí"){
+        firstoper<- filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "*") %>% 
+          select(DayPostInoc, Side) %>% unique() %>% 
+        if (firstoper == Inf){firstoper<-c()}
+        
+        if (input$operated == TRUE & length(firstoper) > 0){
+          for (i in 1:nrow(firstoper)){
+            table<-table %>% filter(DayPostInoc < firstoper$FirstOper[i] | Side != firstoper$Side[i])
+          } 
+        }else{
+          if(input$dead == TRUE){
+            deadmice<-filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "+") %>% 
+              pull(Animal)
+            table<-table %>% filter(!Animal %in% deadmice)
+          }
+        }
         g<-list()
         for (side in c("L","R")){
           tableR<-filter(table, Side == side) %>% filter(!is.na(Volume))
-          endtime<-dcast(tableR %>% filter(Volume < input$cutoff), Cage+Animal+Side+Group~., value.var = "DayPostInoc", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
+          endtime<-dcast(tableR %>% filter(Volume < input$cutoff), Animal+Side+Group~., value.var = "DayPostInoc", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
-          endtime["Dead"]<-dcast(tableR, Cage+Animal+Side+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") > input$cutoff
+          endtime["Dead"]<-dcast(tableR, Animal+Side+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") > input$cutoff
           table_tumor<<-endtime
           
-          g[side]<-ggsurvplot(survfit(Surv(table_tumor$end, table_tumor$Dead) ~ table_tumor$Group, data=table_tumor),
+          g[side]<-ggsurvplot(survfit(Surv(end, Dead) ~ Group, data=table_tumor),
                               pval = T, pval.method = T,
                               title = side,
                               # legend.labs = paste(c("< median", ">= median"), "MICA"),
@@ -573,13 +652,27 @@ server <- function(input, output) {
         do.call(grid.arrange, g)
         
       }else{
+        firstoper<- filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "*") %>% 
+          pull(DayPostInoc) %>% min(na.rm = T)
+        if (firstoper == Inf){firstoper<-c()}
+        
+        if (input$operated == TRUE & length(firstoper) > 0){
+          table<-table %>% filter(DayPostInoc < firstoper)
+        }else{
+          deadmice<-filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "+") %>% 
+            pull(Animal)
+          if(input$dead == TRUE){
+            table<-table %>% filter(!Animal %in% deadmice)
+          }
+        }
+        
         tableR<-table %>% filter(!is.na(Volume))
         endtime<-dcast(if(length(unique(tableR$DayPostInoc)) > 1){tableR %>% filter(Volume < input$cutoff)}else{tableR}, Animal+Side+Group~., 
                        value.var = "DayPostInoc", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
         endtime["Dead"]<-dcast(tableR, Animal+Side+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$Group, data=table_tumor),
+        g<-ggsurvplot(survfit(Surv(end, Dead) ~ Group, data=table_tumor),
                             pval = T, pval.method = T,
                             # legend.labs = paste(c("< median", ">= median"), "MICA"),
                             ggtheme=theme_classic(base_size=15)
@@ -603,9 +696,6 @@ server <- function(input, output) {
         for (side in c("L","R")){
           tableR<-filter(table, Side == side) %>% filter(!is.na(Volume))
           if (length(unique(tableR$Volume)) > 1 & length(unique(tableR$DayPostInoc)) > 1){
-            print(paste0("Side: ",side))
-            # print(summary(aov(Volume~Group+DayPostInoc+Error(paste0(Animal,Cage)), data=tableR)))
-            print(summary(aov(Volume~Group+DayPostInoc+Error(Animal), data=tableR)))
           }
         }
       }
@@ -665,7 +755,6 @@ server <- function(input, output) {
     },
     content = function(file){
       dtemplate<-analysis$taula
-      # print(str(dtemplate))
       write.xlsx(dtemplate,file, )
     }
   )
@@ -689,7 +778,6 @@ server <- function(input, output) {
       sides<-unique(table$Side)
       groups<-table %>% select(Animal, Group) %>% unique() %>% pull(Group)
       basal<-data.frame(
-        Cage="",
         Animal=rep(animals, each=length(sides)),
         Date="",
         DayPostInoc=0,
@@ -701,7 +789,9 @@ server <- function(input, output) {
         Volume=0,
         Observations=""
       )
-      table<-rbind(table, basal)
+      if (!(0 %in% table$DayPostInoc) | sum(table[table$DayPostInoc == 0,"Volume"],na.rm = T) == 0){
+        table<-rbind(table, basal)  
+      }
       if (input$fig_id %in% c("Cinética Grupo", "Cinética Individual")){
         if (input$fig_id == "Cinética Grupo"){
           if (input$vacc == "Sí"){
@@ -713,6 +803,12 @@ server <- function(input, output) {
               for (i in 1:nrow(firstoper)){
                 table<-table %>% filter(DayPostInoc < firstoper$FirstOper[i] | Side != firstoper$Side[i])
               } 
+            }else{
+              if(input$dead == TRUE){
+                deadmice<-filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "+") %>% 
+                  pull(Animal)
+                table<-table %>% filter(!Animal %in% deadmice)
+              }
             }
             std<-function(x, na.rm=T){sd(x, na.rm=na.rm)/sqrt(length(x))}
             errbar<-table %>% group_by(Group,Side,DayPostInoc) %>% 
@@ -735,11 +831,17 @@ server <- function(input, output) {
           }else{
             firstoper<- filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "*") %>% 
               pull(DayPostInoc) %>% min(na.rm = T)
-            print(firstoper)
             
             if (input$operated == TRUE){
               table<-table %>% filter(DayPostInoc < firstoper)
+            }else{
+              deadmice<-filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "+") %>% 
+                pull(Animal)
+              if(input$dead == TRUE){
+                table<-table %>% filter(!Animal %in% deadmice)
+              }
             }
+            
             std<-function(x, na.rm=T){sd(x, na.rm=na.rm)/sqrt(length(x))}
             errbar<-table %>% group_by(Group, DayPostInoc) %>% 
               summarise(mean=mean(Volume, na.rm=T), std=std(Volume)) %>% 
@@ -761,6 +863,22 @@ server <- function(input, output) {
         }
         if (input$fig_id == "Cinética Individual"){
           if (input$vacc == "Sí"){
+            firstoper<- filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "*") %>% 
+              select(DayPostInoc, Side) %>% unique() %>% 
+              group_by(Side) %>% summarise(FirstOper=min(DayPostInoc))
+            
+            if (input$operated == TRUE){
+              for (i in 1:nrow(firstoper)){
+                table<-table %>% filter(DayPostInoc < firstoper$FirstOper[i] | Side != firstoper$Side[i])
+              } 
+            }else{
+              if(input$dead == TRUE){
+                deadmice<-filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "+") %>% 
+                  pull(Animal)
+                table<-table %>% filter(!Animal %in% deadmice)
+              }
+            }
+            
             g<-ggplot(table, aes(as.numeric(as.character(DayPostInoc)), Volume, color=Group, group=Animal))+
               scale_x_continuous(expand = expansion(mult = c(0,0.0)),
                                  breaks=sort(unique(as.numeric(as.character(table$DayPostInoc)))),
@@ -768,7 +886,20 @@ server <- function(input, output) {
               facet_grid(factor(Side, labels = c("Vaccination", "Rechallenge"))~Group, scale="free_y")+
               theme_bw()
           }else{
-            g<-ggplot(table, aes(as.numeric(as.character(DayPostInoc)), Volume, color=Group, group=Animal))+
+            firstoper<- filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "*") %>% 
+              pull(DayPostInoc) %>% min(na.rm = T)
+            
+            if (input$operated == TRUE){
+              table<-table %>% filter(DayPostInoc < firstoper)
+            }else{
+              deadmice<-filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "+") %>% 
+                pull(Animal)
+              if(input$dead == TRUE){
+                table<-table %>% filter(!Animal %in% deadmice)
+              }
+            }
+
+            g<-ggplot(table, aes(as.numeric(as.character(DayPostInoc)), Volume, color=Group, group=paste0(Animal,Side)))+
               scale_x_continuous(expand = expansion(mult = c(0,0.0)),
                                  breaks=sort(unique(as.numeric(as.character(table$DayPostInoc)))),
                                  limits = c(0,max(as.numeric(as.character(table$DayPostInoc)))*1.1))+
@@ -818,12 +949,26 @@ server <- function(input, output) {
         }
 
         if (input$vacc == "Sí"){
+          firstoper<- filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "*") %>% 
+            select(DayPostInoc, Side) %>% unique() %>% 
+            group_by(Side) %>% summarise(FirstOper=min(DayPostInoc))
+          if (input$operated == TRUE){
+            for (i in 1:nrow(firstoper)){
+              table<-table %>% filter(DayPostInoc < firstoper$FirstOper[i] | Side != firstoper$Side[i])
+            } 
+          }else{
+            if(input$dead == TRUE){
+              deadmice<-filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "+") %>% 
+                pull(Animal)
+              table<-table %>% filter(!Animal %in% deadmice)
+            }
+          }
           g<-list()
           count<-1
           for (side in c("L","R")){
             tableR<-filter(table, Side == side) %>% filter(!is.na(Volume))
-            endtime<-dcast(tableR %>% filter(Volume < (input$cutoff*as.numeric(input$unit_fact))), Cage+Animal+Side+Group~., value.var = "DayPostInoc", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
+            endtime<-dcast(tableR %>% filter(Volume < (input$cutoff*as.numeric(input$unit_fact))), Animal+Side+Group~., value.var = "DayPostInoc", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
-            endtime["Dead"]<-dcast(tableR, Cage+Animal+Side+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") > (input$cutoff*as.numeric(input$unit_fact))
+            endtime["Dead"]<-dcast(tableR, Animal+Side+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") > (input$cutoff*as.numeric(input$unit_fact))
             table_tumor<-endtime
             if (input$colors != ""){
               col<-strsplit(input$colors, ",")[[1]]
@@ -831,7 +976,7 @@ server <- function(input, output) {
               col<-gg_color_hue(length(unique(endtime$Group)))
             }
             table_tumor$Group<-factor(table_tumor$Group, levels = levels(analysis$taula$Group))
-            g[[count]]<-ggsurvplot(survfit(Surv(table_tumor$end, table_tumor$Dead) ~ Group, data=table_tumor),
+            g[[count]]<-ggsurvplot(survfit(Surv(end, Dead) ~ Group, data=table_tumor),
                                 pval = T, pval.method = T,
                                 title = side,
                                 ggtheme=theme_classic(base_size=input$`font-size`),
@@ -842,6 +987,18 @@ server <- function(input, output) {
           g_surv_vacc<-g
           
         }else{
+          firstoper<- filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "*") %>% 
+            pull(DayPostInoc) %>% min(na.rm = T)
+          
+          if (input$operated == TRUE){
+            table<-table %>% filter(DayPostInoc < firstoper)
+          }else{
+            deadmice<-filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "+") %>% 
+              pull(Animal)
+            if(input$dead == TRUE){
+              table<-table %>% filter(!Animal %in% deadmice)
+            }
+          }
           tableR<-table %>% filter(!is.na(Volume))
           endtime<-dcast(tableR %>% filter(Volume < (input$cutoff*as.numeric(input$unit_fact))), Animal+Group~., value.var = "DayPostInoc", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
           endtime["Dead"]<-dcast(tableR, Animal+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") > (input$cutoff*as.numeric(input$unit_fact))
@@ -852,7 +1009,7 @@ server <- function(input, output) {
             col<-gg_color_hue(length(unique(table_tumor$Group)))
           }
           table_tumor$Group<-factor(table_tumor$Group, levels = levels(analysis$taula$Group))
-          g<-ggsurvplot(survfit(Surv(table_tumor$end, table_tumor$Dead) ~ Group, data=table_tumor),
+          g<-ggsurvplot(survfit(Surv(end, Dead) ~ Group, data=table_tumor),
                         pval = T, pval.method = T,
                         # ggtheme=theme_classic(base_size=input$`font-size`),
                         palette = col