Cambiar Supervivencia y Kluskal de formato.

invivos/app.R

@@ -362,21 +362,20 @@ server <- function(input, output) {
       table_group<-merge(
         table %>% select(Animal, Group) %>% unique() %>% group_by(Animal) %>% count(),
         table %>% select(Animal, Group) %>% unique()
-      ) %>% filter(n > 1 & (!is.na(Group) | Group != "")) %>% select(-n)
+      ) %>% filter(!is.na(Group) | Group != "") %>% select(-n)
       
       table<-merge(
         table %>% select(-Group),
         table_group
       ) %>% relocate(Group, .after = DayPostInoc) %>% arrange(DayPostInoc, Animal, Side)
       
-      
       analysis$taula<-table
     }
   })
   output$cutoffUI<-renderUI({
-    if (!is.null(analysis$taula_def)){
-      observeEvent(analysis$taula_def, {})
-      max_val<-max(analysis$taula_def$Volume, na.rm = T)
+    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)
     }
@@ -494,15 +493,15 @@ server <- function(input, output) {
   })
   
   output$survival<-renderPlot({
-    if (!is.null(input$file_analy) & !is.null(analysis$taula_def)){
-      observeEvent(analysis$taula_def, {})
-      table<-analysis$taula_def
+    if (!is.null(input$file_analy) & !is.null(analysis$taula)){
+      observeEvent(analysis$taula, {})
+      table<-analysis$taula
       if (input$vacc == "Sí"){
         g<-list()
         for (side in c("L","R")){
-          tableR<-filter(table, `ID tumor` == side) %>% filter(!is.na(Volume))
-          endtime<-dcast(tableR %>% filter(Volume < input$cutoff), Cage+`ID animal`+`ID tumor`+Group~., value.var = "Timepoint", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
-          endtime["Dead"]<-dcast(tableR, Cage+`ID animal`+`ID tumor`+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") > input$cutoff
+          tableR<-filter(table, Side == side) %>% filter(!is.na(Volume))
+          endtime<-dcast(tableR %>% filter(Volume < input$cutoff), Cage+Animal+Side+Group~., value.var = "DayPostInoc", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
+          endtime["Dead"]<-dcast(tableR, Cage+Animal+Side+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") > input$cutoff
           table_tumor<<-endtime
           
           g[side]<-ggsurvplot(survfit(Surv(table_tumor$end, table_tumor$Dead) ~ table_tumor$Group, data=table_tumor),
@@ -525,9 +524,9 @@ server <- function(input, output) {
         
       }else{
         tableR<-table %>% filter(!is.na(Volume))
-        endtime<-dcast(if(length(unique(tableR$Timepoint)) > 1){tableR %>% filter(Volume < input$cutoff)}else{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$cutoff
+        endtime<-dcast(if(length(unique(tableR$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$Group, data=table_tumor),
@@ -544,19 +543,19 @@ server <- function(input, output) {
   output$stats<-renderPrint({
     stattest<-"dunn"
     oneside<-""
-    if (!is.null(input$file_analy) & !is.null(analysis$taula_def)){
-      observeEvent(analysis$taula_def, {})
-      table<-analysis$taula_def
+    if (!is.null(input$file_analy) & !is.null(analysis$taula)){
+      observeEvent(analysis$taula, {})
+      table<-analysis$taula
       if (input$vacc == "No"){
         table<-filter(table, !is.na(Volume))
-        summary(aov(Volume~Group+Timepoint+Error(`ID animal`+`ID tumor`), data=table))
+        summary(aov(Volume~Group+DayPostInoc+Error(Animal+Side), data=table))
       }else{
         for (side in c("L","R")){
-          tableR<-filter(table, `ID tumor` == side) %>% filter(!is.na(Volume))
-          if (length(unique(tableR$Volume)) > 1 & length(unique(tableR$Timepoint)) > 1){
+          tableR<-filter(table, Side == side) %>% filter(!is.na(Volume))
+          if (length(unique(tableR$Volume)) > 1 & length(unique(tableR$DayPostInoc)) > 1){
             print(paste0("Side: ",side))
-            # print(summary(aov(Volume~Group+Timepoint+Error(paste0(ID animal,Cage)), data=tableR)))
-            print(summary(aov(Volume~Group+Timepoint+Error(`ID animal`), data=tableR)))
+            # print(summary(aov(Volume~Group+DayPostInoc+Error(paste0(Animal,Cage)), data=tableR)))
+            print(summary(aov(Volume~Group+DayPostInoc+Error(Animal), data=tableR)))
           }
         }
       }
@@ -565,42 +564,42 @@ server <- function(input, output) {
   output$tab_stats<-renderTable({
     stattest<-"dunn"
     oneside<-""
-    if (!is.null(input$file_analy) & !is.null(analysis$taula_def)){
-      table<-analysis$taula_def
+    if (!is.null(input$file_analy) & !is.null(analysis$taula)){
+      table<-analysis$taula
       table_stats<-list()
       if (input$vacc == "No"){
         table<-table%>%filter(!is.na(Volume))
         if (length(unique(table$Volume)) > 1){
-          table_stats<-multi_stats(table, "Volume", "Timepoint", "Group", stat.test=stattest)  
+          table_stats<-multi_stats(table, "Volume", "DayPostInoc", "Group", stat.test=stattest)  
         }
         table_kw<-as.data.frame(matrix(nrow=0, ncol=2))
-        for (point in unique(table$Timepoint)){
-          len_group<-length(unique(table %>% filter(Timepoint == point) %>% pull(Group)))
+        for (point in unique(table$DayPostInoc)){
+          len_group<-length(unique(table %>% filter(DayPostInoc == point) %>% pull(Group)))
           if (len_group > 1){
-            table_kw<-rbind(table_kw, data.frame(point,kruskal.test(table %>% filter(Timepoint == point) %>% pull(Volume), table %>% filter(Timepoint == point) %>% pull(Group))[3][[1]]))
+            table_kw<-rbind(table_kw, data.frame(point,kruskal.test(table %>% filter(DayPostInoc == point) %>% pull(Volume), table %>% filter(DayPostInoc == point) %>% pull(Group))[3][[1]]))
           }
         }
-        colnames(table_kw)<-c("Timepoint", "KW-p.val")
+        colnames(table_kw)<-c("DayPostInoc", "KW-p.val")
         table_stats<-merge(table_stats, table_kw)
         
       }else{
         for (side in c("L","R")){
-          tableR<-filter(table, `ID tumor` == side) %>% filter(!is.na(Volume))
+          tableR<-filter(table, Side == side) %>% filter(!is.na(Volume))
           if (length(unique(tableR$Volume)) > 1){
-            table_stats[[side]]<-multi_stats(tableR, "Volume", "Timepoint", "Group", stat.test=stattest)  
+            table_stats[[side]]<-multi_stats(tableR, "Volume", "DayPostInoc", "Group", stat.test=stattest)  
           }
           table_kw<-as.data.frame(matrix(nrow=0, ncol=2))
-          for (point in unique(tableR$Timepoint)){
-            len_group<-length(unique(tableR %>% filter(Timepoint == point) %>% pull(Group)))
+          for (point in unique(tableR$DayPostInoc)){
+            len_group<-length(unique(tableR %>% filter(DayPostInoc == point) %>% pull(Group)))
             if (len_group > 1){
-              table_kw<-rbind(table_kw, data.frame(point,kruskal.test(tableR %>% filter(Timepoint == point) %>% pull(Volume), tableR %>% filter(Timepoint == point) %>% pull(Group))[3][[1]]))
+              table_kw<-rbind(table_kw, data.frame(point,kruskal.test(tableR %>% filter(DayPostInoc == point) %>% pull(Volume), tableR %>% filter(DayPostInoc == point) %>% pull(Group))[3][[1]]))
             }
           }
-          colnames(table_kw)<-c("Timepoint", "KW-p.val")
+          colnames(table_kw)<-c("DayPostInoc", "KW-p.val")
           table_stats[[side]]<-merge(table_stats[[side]], table_kw)
         }
       }
-      table_stats_def<-bind_rows(table_stats, .id = "ID tumor")
+      table_stats_def<-bind_rows(table_stats, .id = "Side")
       if (input$filter_stats == T){
         table_stats_def %>% filter(p.adj < 0.05)
       }else{
@@ -622,48 +621,69 @@ server <- function(input, output) {
   
   ##Exportar
   output$expPlotUI<- renderUI({
-    observeEvent(analysis$taula_def, {})
-    if (!is.null(input$file_analy) & !is.null(analysis$taula_def)){
+    observeEvent(analysis$taula, {})
+    if (!is.null(input$file_analy) & !is.null(analysis$taula)){
       plotOutput("expPlot", width=paste0(input$width/10,"px"), height = paste0(input$height/10, "px"))
     }
   })
   
   output$expPlot <- renderPlot({
-    observeEvent(analysis$taula_def, {})
-    if (!is.null(input$file_analy) & !is.null(analysis$taula_def)){
-      table<-analysis$taula_def
-      
+    observeEvent(analysis$taula, {})
+    if (!is.null(input$file_analy) & !is.null(analysis$taula)){
+      table<-analysis$taula
+      animals<-unique(table$Animal)
+      sides<-unique(table$Side)
+      groups<-table %>% select(Animal, Group) %>% unique() %>% pull(Group)
+      basal<-data.frame(
+        Cage="",
+        Animal=rep(animals, each=length(sides)),
+        Date="",
+        DayPostInoc=0,
+        Group=rep(groups, each=length(sides)),
+        Side=rep(sides, length(animals)),
+        Weight="",
+        Long="",
+        Wide="",
+        Volume=0,
+        Observations=""
+      )
+      table<-rbind(table, basal)
       if (input$fig_id %in% c("Cinética Grupo", "Cinética Individual")){
         if (input$fig_id == "Cinética Grupo"){
           if (input$vacc == "Sí"){
             std<-function(x, na.rm=T){sd(x, na.rm=na.rm)/sqrt(length(x))}
-            errbar<-table %>% group_by(Group,`ID tumor`, Timepoint) %>% 
+            errbar<-table %>% group_by(Group,Side,DayPostInoc) %>% 
               summarise(mean=mean(Volume, na.rm=T), std=std(Volume)) %>% 
-              mutate(Timepoint2=as.numeric(as.character(Timepoint))) %>% 
+              mutate(Timepoint2=as.numeric(as.character(DayPostInoc))) %>% 
               mutate(x=Timepoint2-input$`errorbar-width`, xend=Timepoint2+input$`errorbar-width`)
             
-            g<-ggplot(table, aes(as.numeric(as.character(Timepoint)), Volume, color=Group, group=Group))+
-              scale_x_continuous(expand = expansion(mult = c(0,0.0)), 
-                                 breaks=sort(unique(errbar$Timepoint2)),
-                                 limits = c(0,max(as.numeric(as.character(table$Timepoint)))*1.1))+
-              facet_grid(factor(`ID tumor`, labels = c("Vaccination", "Rechallenge"))~., scale="free_y")+
+            g<-ggplot(table, aes(DayPostInoc, Volume, color=Group, group=Group))+
+              geom_errorbar(stat="summary", width=0.05)+
+              geom_line(stat="summary")+
+              geom_point(stat="summary")+
+              facet_grid(factor(Side, labels = c("Vaccination", "Rechallenge"))~., scale="free_y")+
+              labs(x="Days after tumor inoculation")+
+              scale_y_continuous(expand = expansion(mult = c(0,0.05)))+
+              scale_x_continuous(expand = expansion(mult = c(0,0.05)), limits = c(0, (round(max(table$DayPostInoc) / 5)+1)*5))+
               theme_bw()+
               geom_segment(data=errbar, aes(y=mean, yend=mean+std, x=Timepoint2,  xend=Timepoint2))+
               geom_segment(data=errbar, aes(y=mean+std, yend=mean+std,
                                             x=x,xend=xend))
           }else{
             std<-function(x, na.rm=T){sd(x, na.rm=na.rm)/sqrt(length(x))}
-            errbar<-table %>% group_by(Group, Timepoint) %>% 
+            errbar<-table %>% group_by(Group, DayPostInoc) %>% 
               summarise(mean=mean(Volume, na.rm=T), std=std(Volume)) %>% 
-              mutate(Timepoint2=as.numeric(as.character(Timepoint))) %>% 
+              mutate(Timepoint2=as.numeric(as.character(DayPostInoc))) %>% 
               mutate(x=Timepoint2-input$`errorbar-width`, xend=Timepoint2+input$`errorbar-width`)
             
-            g<-ggplot(table, aes(as.numeric(as.character(Timepoint)), Volume, color=Group, group=Group))+
-              scale_x_continuous(expand = expansion(mult = c(0,0.0)), 
-                                 breaks=sort(unique(errbar$Timepoint2)),
-                                 limits = c(0,max(as.numeric(as.character(table$Timepoint)))*1.1))+
-              # limits = c(0, (round(max(as.numeric(as.character(table$Timepoint))) / 5)+1)*5))+
+            g<-ggplot(table, aes(DayPostInoc, Volume, color=Group, group=Group))+
+              geom_errorbar(stat="summary",width=0.05)+
+              geom_line(stat="summary")+
+              geom_point(stat="summary")+
+              labs(x="Days after tumor challenge")+
+              scale_y_continuous(expand = expansion(mult = c(0,0.05)))+
               theme_bw()+
+              theme(axis.text.x=element_text(angle=45, hjust=1))+
               geom_segment(data=errbar, aes(y=mean, yend=mean+std, x=Timepoint2,  xend=Timepoint2))+
               geom_segment(data=errbar, aes(y=mean+std, yend=mean+std,
                                             x=x,xend=xend))
@@ -671,17 +691,17 @@ server <- function(input, output) {
         }
         if (input$fig_id == "Cinética Individual"){
           if (input$vacc == "Sí"){
-            g<-ggplot(table, aes(as.numeric(as.character(Timepoint)), Volume, color=Group, group=`ID animal`))+
+            g<-ggplot(table, aes(as.numeric(as.character(DayPostInoc)), Volume, color=Group, group=Animal))+
               scale_x_continuous(expand = expansion(mult = c(0,0.0)),
-                                 breaks=sort(unique(as.numeric(as.character(table$Timepoint)))),
-                                 limits = c(0, (round(max(as.numeric(as.character(table$Timepoint))) / 5)+1)*5))+
-              facet_grid(factor(`ID tumor`, labels = c("Vaccination", "Rechallenge"))~Group, scale="free_y")+
+                                 breaks=sort(unique(as.numeric(as.character(table$DayPostInoc)))),
+                                 limits = c(0, (round(max(as.numeric(as.character(table$DayPostInoc))) / 5)+1)*5))+
+              facet_grid(factor(Side, labels = c("Vaccination", "Rechallenge"))~Group, scale="free_y")+
               theme_bw()
           }else{
-            g<-ggplot(table, aes(as.numeric(as.character(Timepoint)), Volume, color=Group, group=`ID animal`))+
+            g<-ggplot(table, aes(as.numeric(as.character(DayPostInoc)), Volume, color=Group, group=Animal))+
               scale_x_continuous(expand = expansion(mult = c(0,0.0)),
-                                 breaks=sort(unique(as.numeric(as.character(table$Timepoint)))),
-                                 limits = c(0,max(as.numeric(as.character(table$Timepoint)))*1.1))+
+                                 breaks=sort(unique(as.numeric(as.character(table$DayPostInoc)))),
+                                 limits = c(0,max(as.numeric(as.character(table$DayPostInoc)))*1.1))+
               facet_wrap(.~Group)+
               theme_bw()
           }
@@ -730,9 +750,9 @@ server <- function(input, output) {
           g<-list()
           count<-1
           for (side in c("L","R")){
-            tableR<-filter(table, `ID tumor` == side) %>% filter(!is.na(Volume))
-            endtime<-dcast(tableR %>% filter(Volume < input$cutoff), Cage+`ID animal`+`ID tumor`+Group~., value.var = "Timepoint", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
-            endtime["Dead"]<-dcast(tableR, Cage+`ID animal`+`ID tumor`+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") > input$cutoff
+            tableR<-filter(table, Side == side) %>% filter(!is.na(Volume))
+            endtime<-dcast(tableR %>% filter(Volume < input$cutoff), Cage+Animal+Side+Group~., value.var = "DayPostInoc", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
+            endtime["Dead"]<-dcast(tableR, Cage+Animal+Side+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") > input$cutoff
             table_tumor<-endtime
             if (input$colors != ""){
               col<-input$colors
@@ -752,8 +772,8 @@ 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 %>% filter(Volume < input$cutoff), Animal+Group~., value.var = "DayPostInoc", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
+          endtime["Dead"]<-dcast(tableR, Animal+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") > input$cutoff
           table_tumor<-endtime
           if (input$colors != ""){
             col<-input$colors