Nueva versión tabla nmice.

invivos/app.R

@@ -374,30 +374,7 @@ server <- function(input, output) {
       oneside<-""
 
       table<-analysis$taula
-      if ("ID.animal" %in% colnames(table)){table<-rename(table, "ID animal"=`ID.animal`)}
-      if ("ID" %in% colnames(table)){table<-rename(table, "ID animal"=ID)}
-      if ("ID.tumor" %in% colnames(table)){table<-rename(table, "ID tumor"=`ID.tumor`)}
-      # table[table$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 & input$vacc == "Sí"){
-        table["0"]<-0
-      }
-      table<-melt(table, id=colnames(table)[colnames(table) %in% col_nodays], variable.name = "Timepoint")
-      table$Timepoint<-gsub("[A-Za-z ]","",table$Timepoint)
-      # print(table)
-      if ("DPV" %in% colnames(table)){
-        table<-dcast(table, Cage+`ID animal`+`ID tumor`+Group+Timepoint~DPV, value.var = "value")
-        table$Major<-table$Major
-        table$Minor<-table$Minor
-        table["Volume"]<-((table$Major*table$Minor*table$Minor)*(pi/6))
-      }
-      if ("TS" %in% colnames(table)){
-        table<-dcast(table, Cage+`ID animal`+`ID tumor`+Group+Timepoint~TS, value.var = "value")
-        table["Volume"]<-table$`TS-Deep`*table$`TS-Length`*table$`TS-Width`*pi/6
-      }
-      if (!"Volume" %in% colnames(table)){table<-rename(table, "Volume"=value)}
       table<-table %>% filter(!is.na(Group))
-      table$Timepoint<-factor(table$Timepoint, levels=mixedsort(as.numeric(as.character(unique(table$Timepoint)))))
       if (input$increase_volume){
         timepoints<-unique(table$Timepoint)
         table<-table %>% select(-Major, -Minor) %>% 
@@ -406,11 +383,7 @@ server <- function(input, output) {
           gather(Timepoint, Volume, -Cage, -`ID animal`, -`ID tumor`, -Group) %>% 
           mutate(Volume=case_when(Volume < 0 ~ 0, T~Volume))
       }
-      table$Timepoint<-factor(table$Timepoint, levels=mixedsort(as.numeric(as.character(unique(table$Timepoint)))))
+      table %>% group_by(Group, DayPostInoc, Side) %>% count() %>% spread(DayPostInoc, n)
-      analysis$taula_def<-table
-      analysis$taula_vol<-dcast(table, Cage+`ID animal`+`ID tumor`~Timepoint,value.var = "Volume")
-      table_plot<-dcast(dcast(table %>% filter(!is.na(Volume)), `ID animal`+Group+Timepoint~., value.var = "Volume", fun.aggregate = mean), Group~Timepoint)
-      table_plot
     }
   })
   output$cin_group<-renderPlot({