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

invivos/app.R

@@ -121,12 +121,17 @@ server <- function(input, output) {
       }
       table$Date<-format(table$Date, format="%d/%m/%Y")
       if ("sex" %in% colnames(table)){table<-select(table, -sex)}
+      if ("Abs" %in% colnames(table)){
+        table<-rename(table, "Volume"="Abs")
+      }else{
         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)
+      }
+
       if ("Cage" %in% colnames(table)){
         table$Animal<-paste0(table$Cage, table$Animal)
         table<-table[,-which(colnames(table) == "Cage")]
@@ -193,8 +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
 
@@ -223,7 +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{
@@ -244,12 +248,10 @@ 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") 
     }
@@ -330,12 +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(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(
@@ -407,11 +412,24 @@ server <- function(input, output) {
       
       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$taula<-table
     }
   })
@@ -419,7 +437,6 @@ server <- function(input, output) {
     if (!is.null(analysis$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)
     }
   })
@@ -431,14 +448,6 @@ server <- function(input, output) {
 
       table<-analysis$taula
       table<-table %>% filter(!is.na(Group))
-      if (input$increase_volume){
-        timepoints<-unique(table$Timepoint)
-        table<-table %>% select(-Major, -Minor) %>% 
-          spread(Timepoint, Volume) %>% 
-          mutate(across(all_of(timepoints), function(x){(x*100/`0`)-100})) %>%
-          gather(Timepoint, Volume, -`ID animal`, -`ID tumor`, -Group) %>% 
-          mutate(Volume=case_when(Volume < 0 ~ 0, T~Volume))
-      }
       table %>% group_by(Group, DayPostInoc, Side) %>% count() %>% spread(DayPostInoc, n)
     }
   })
@@ -448,7 +457,6 @@ server <- function(input, output) {
       observeEvent(analysis$taula, {})
       table<-analysis$taula
       
-      print(table)
       animals<-unique(table$Animal)
       sides<-unique(table$Side)
       groups<-table %>% select(Animal, Group) %>% unique() %>% pull(Group)
@@ -474,7 +482,7 @@ server <- function(input, output) {
           group_by(Side) %>% summarise(FirstOper=min(DayPostInoc))
         deadmice<-filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "+") %>% 
           pull(Animal)
-        print(deadmice)
+
         if (input$operated == TRUE & nrow(firstoper) > 0){
           for (i in 1:nrow(firstoper)){
             table<-table %>% filter(DayPostInoc < firstoper$FirstOper[i] | Side != firstoper$Side[i])
@@ -646,9 +654,9 @@ 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 (firstoper == Inf){firstoper<-c()}
         
-        if (input$operated == TRUE & nrow(firstoper) > 0){
+        if (input$operated == TRUE & length(firstoper) > 0){
           table<-table %>% filter(DayPostInoc < firstoper)
         }else{
           deadmice<-filter(table, !is.na(substr(Observations,1,1)) & substr(Observations,1,1) == "+") %>% 
@@ -688,8 +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(Animal), data=tableR)))
           }
         }
       }
@@ -749,7 +755,6 @@ server <- function(input, output) {
     },
     content = function(file){
       dtemplate<-analysis$taula
-      # print(str(dtemplate))
       write.xlsx(dtemplate,file, )
     }
   )
@@ -826,7 +831,6 @@ 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)
@@ -884,7 +888,6 @@ 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)
@@ -895,8 +898,6 @@ server <- function(input, output) {
                 table<-table %>% filter(!Animal %in% deadmice)
               }
             }
-            print("Table")
-            print(head(table))
 
             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)),
@@ -988,7 +989,6 @@ 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)