Adaptado la normalización a nuevo formato. Se puede indicar el día a normalizar.

invivos/app.R

@@ -26,6 +26,7 @@ ui <- fluidPage(
                   uiOutput('ncages'),
                   uiOutput('ntumors'),
                   # selectInput(inputId = "measure_sys", "Sistema de medida", selected = "L-W-D", choices = c("L-W-D","Min-Max","Absorbance")),
+                  uiOutput('day_vol'),
                   uiOutput('lowcut'),
                   uiOutput('upcut'),
                   uiOutput('goButton'),
@@ -103,22 +104,29 @@ server <- function(input, output) {
   dades$db<-NULL
   observe({
     if (!is.null(input$file_sizes)){ 
-      taula<-read.xlsx(input$file_sizes$datapath, sheet = 1, sep.names = " ")
-      if ("DPV" %in% colnames(taula)){
-        taula<-dcast(taula, Cage+`ID animal`+`ID tumor`+Group~DPV, value.var = "0")
-        # taula$Major<-taula$Major/1000
-        # taula$Minor<-taula$Minor/1000
-        # taula["Volume"]<-((taula$Major*taula$Minor*taula$Minor)*(pi/6))*1000
-        taula$Major<-taula$Major
-        taula$Minor<-taula$Minor
-        taula["Volume"]<-((taula$Major*taula$Minor*taula$Minor)*(pi/6))
+      table<-read.xlsx(input$file_sizes$datapath, sheet = 1, check.names = F, sep.names = " ", detectDates = T,cols=1:11)
+      if("ID.animal" %in% colnames(table)){
+        table<-table %>%
+          rename(Animal=`ID.animal`, Side=`ID.tumor`)
+        table<-table %>% gather(DayPostInoc, Value, which(!is.na(as.numeric(colnames(table))))) %>% 
+          relocate(DayPostInoc, .before = Group) %>% spread(DPV, Value) %>% 
+          rename(Long=Major, Wide=Minor) %>% 
+          add_column(Date="", .after = "Animal") %>% 
+          add_column(Weight="", .after="Group") %>% 
+          add_column(Volume="",Observations="") %>%
+          relocate(Side, .after = "Group")
+        table$DayPostInoc<-as.numeric(table$DayPostInoc)
       }
-      if ("TS" %in% colnames(taula)){
-        taula<-dcast(taula, Cage+`ID animal`+`ID tumor`+Group~TS, value.var = "0")
-        taula["Volume"]<-taula$`TS-Deep`*taula$`TS-Length`*taula$`TS-Width`*pi/6
+      table$Date<-format(table$Date, format="%d/%m/%Y")
+      if ("sex" %in% colnames(table)){table<-select(table, -sex)}
+      for (i in 1:nrow(table)){
+        long<-as.numeric(gsub(",",".",strsplit(as.character(table[i,"Long"]),"+", fixed = T)[[1]]))
+        wide<-as.numeric(gsub(",",".",strsplit(as.character(table[i,"Wide"]),"+", fixed = T)[[1]]))
+        table[i,"Volume"]<-sum(sapply(1:length(long), function(x) (long[x]*wide[x]*wide[x])*(pi/6)))
       }
-      dades$taula<-taula
-      dades$groups<-read.xlsx(input$file_sizes$datapath, sheet = 2, colNames=F)[,1]
+      table$Volume<-as.numeric(table$Volume)
+      dades$taula<-table
+      dades$groups<-read.xlsx(input$file_sizes$datapath, sheet = "Groups", colNames=F)[,1]
       if (readxl::excel_sheets(input$file_sizes$datapath) %>% length > 2){
         dades$sex<-read.xlsx(input$file_sizes$datapath, sheet = 3, sep.names = " ")
       }
@@ -127,7 +135,15 @@ server <- function(input, output) {
   output$firstPlot <- renderPlot({
     observeEvent(dades$taula, {})
     if (!is.null(dades$taula)){
-      ggplot(dades$taula, aes(x="1", y=Volume))+geom_hline(yintercept = c(input$lowcut, input$upcut), color="red")+geom_quasirandom(width=0.2)
+      ggplot(dades$taula %>% filter(DayPostInoc == input$day_vol), aes(x="1", y=Volume))+
+        geom_hline(yintercept = c(input$lowcut, input$upcut), color="red")+
+        geom_quasirandom(width=0.2)
+    }
+  })
+  
+  output$day_vol<-renderUI({
+    if (!is.null(dades$taula)){
+      selectInput("day_vol", "Día para volúmenes", choices = sort(unique(dades$taula$DayPostInoc))) 
     }
   })
   
@@ -138,15 +154,17 @@ server <- function(input, output) {
   })
   output$lowcut<-renderUI({
     if (!is.null(dades$taula)){
-      cut.max<-round(max(dades$taula$Volume, na.rm = T), 2)
-      step<-round(max(dades$taula$Volume, na.rm = T)/100, 2)
+      taula<-dades$taula %>% filter(DayPostInoc == input$day_vol)
+      cut.max<-round(max(taula$Volume, na.rm = T), 2)
+      step<-round(max(taula$Volume, na.rm = T)/100, 2)
       sliderInput("lowcut", "Corte inferior", min=0, max=cut.max, step=step, value=0)
     }
   })
   output$upcut<-renderUI({
     if (!is.null(dades$taula)){
-      cut.max<-round(max(dades$taula$Volume, na.rm = T), 2)+0.01
-      step<-round(max(dades$taula$Volume, na.rm = T)/20, 2)
+      taula<-dades$taula %>% filter(DayPostInoc == input$day_vol)
+      cut.max<-round(max(taula$Volume, na.rm = T), 2)+0.01
+      step<-round(max(taula$Volume, na.rm = T)/20, 2)
       sliderInput("upcut", "Corte superior", min=0, max=cut.max, step=step, value=cut.max)
     }
   })
@@ -167,11 +185,12 @@ server <- function(input, output) {
   })
   
   grafic<-eventReactive(input$goButton,{
-    df<-dades$taula
+    df<-dades$taula %>% filter(DayPostInoc == input$day_vol)
+    print(df)
     df<-df[!is.na(df$Volume),]
     up_cuttof<-input$upcut
     low_cuttof<-input$lowcut
-    # print(up_cuttof)
+
     df<-df[df$Volume < up_cuttof & df$Volume >= low_cuttof,]
     if (is.null(dades$sex)){
       df<-add_column(df, sex="undefined")
@@ -179,16 +198,14 @@ server <- function(input, output) {
       df<-merge(df, dades$sex)
     }
     
-    
     # df["Mouse"]<-gsub("[a-zA-Z]", "", df$MouseID)
     
     s<-shapiro.test(df$Volume)[[2]]
     
     ngroup<-length(dades$groups)
     df_def<-list()
-    # print(head(df))
+
     for (sex.var in unique(df$sex)){
-      # print(sex.var)
       df_sex<-df %>% filter(`sex` == sex.var)
       ind.list<-list()
       pval.list<-list()
@@ -197,8 +214,9 @@ server <- function(input, output) {
       for (data in 1:input$iterations){
         interr=T
         while(interr == T){
-          ind<-sample(rep(dades$groups, each=ceiling(length(unique(df_sex$`ID animal`))/ngroup)), length(unique(df_sex$`ID animal`)))
-          df_sex<-merge(df_sex[,c("ID animal", "ID tumor","Volume")], data.frame("ID animal"=unique(df_sex$`ID animal`), "group"=as.factor(ind),check.names=F))
+          ind<-sample(rep(dades$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$group) > ceiling(nrow(df_sex)/ngroup))  
           }else{
@@ -206,7 +224,7 @@ server <- function(input, output) {
             interr<-diff(range(table(ind))) > 1
           }
         }
-        ind.list[[data]]<-df_sex[,c("ID animal","ID tumor","group","Volume")]
+        ind.list[[data]]<-df_sex[,c("Animal","Side","group","Volume")]
         lvn.list[data]<-leveneTest(Volume ~ group, data = df_sex[,3:4])[[2]][1]
         if (s < 0.05){
           k<-kruskal.test(df_sex$Volume,df_sex$group)
@@ -229,23 +247,25 @@ server <- function(input, output) {
       df_def<-df_def %>% select(-"Group") 
     }
     df_def<-merge(
-      if(!is.null(dades$sex)){merge(dades$taula, dades$sex)}else{dades$taula %>% add_column(sex="undefined")} %>% select(-Group), 
-      df_def[,c("ID animal", "group")] %>% unique, all=T, by="ID animal")
-    if("DPV" %in% colnames(df_def)){df_def<-select(df_def, c(`ID animal`, `sex`,`ID tumor`, Volume, Cage, Major, Minor, group))}
-    if("TS-Deep" %in% colnames(df_def)){df_def<-select(df_def, c(`ID animal`, `sex`,`ID tumor`, Volume, Cage, `TS-Deep`,`TS-Length`,`TS-Width`, group))}
+      if(!is.null(dades$sex)){merge(dades$taula %>% filter(DayPostInoc == input$day_vol), dades$sex)}else{
+        dades$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<-select(df_def, Cage, Animal, 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))}
     
-    df_def[!paste0(df_def$`ID animal`, df_def$`ID tumor`) %in% paste0(df$`ID animal`, df$`ID tumor`),"group"]<-NA
+    df_def[!paste0(df_def$Animal, df_def$Side) %in% paste0(df$Animal, df$Side),"Group"]<-NA
     dades$db<-df_def
 
     if (is.null(dades$sex)){
-      ggplot(df_def, aes(group, Volume))+
+      ggplot(df_def, aes(Group, Volume))+
         geom_boxplot(outlier.alpha = F)+
         geom_jitter(width=0.25)+
         geom_point(stat="summary", color="blue", size=3)+
         theme(axis.text.x = element_text(angle=90, hjust=1, vjust=0.5))
     }else{
       ggarrange(
-        ggplot(df_def, aes(group, Volume))+
+        ggplot(df_def, aes(Group, Volume))+
           geom_boxplot(outlier.alpha = F)+
           geom_jitter(width=0.25, aes(color=sex))+
           geom_point(stat="summary", color="blue", size=3)+
@@ -255,7 +275,7 @@ server <- function(input, output) {
           ggplot(df_def, aes(sex, Volume))+
             geom_boxplot(outlier.alpha = F)+
             geom_quasirandom(width=0.3),
-          ggplot(df_def, aes(group, fill=sex))+
+          ggplot(df_def, aes(Group, fill=sex))+
             geom_bar(stat="count", color="black", position="dodge")+
             guides(fill="none")+
             theme(axis.text.x = element_text(angle=90, hjust=1, vjust=0.5)), ncol = 1, heights = c(0.35, 0.65)),
@@ -275,8 +295,8 @@ server <- function(input, output) {
     observeEvent(dades$db, {})
     if (!is.null(dades$db)){
       df<-dades$db
-      df_sum<-dcast(df, group~., value.var = "Volume", fun.aggregate = mean, na.rm=T) %>% rename("Mean"=".")
-      df_sum["SEM"]<-dcast(df, group~., value.var = "Volume", fun.aggregate = std.error, na.rm=T) %>% pull(`.`)
+      df_sum<-dcast(df, Group~., value.var = "Volume", fun.aggregate = mean, na.rm=T) %>% rename("Mean"=".")
+      df_sum["SEM"]<-dcast(df, Group~., value.var = "Volume", fun.aggregate = std.error, na.rm=T) %>% pull(`.`)
       df_sum
     }
   })
@@ -284,7 +304,7 @@ server <- function(input, output) {
     observeEvent(dades$db, {})
     if (!is.null(dades$db)){
       df<-dades$db
-      df %>% arrange(group)
+      df %>% arrange(Group)
     }
   })
   
@@ -300,31 +320,12 @@ server <- function(input, output) {
       # timepoint<-c(7,10,13,16,19,22,25)
       
       if (!is.null(input$file_sizes)){
-        # dtemplate<-dades$db %>% select(-Volume,-sex)
-        # dtemplate<-melt(dtemplate, id=c("Cage", "ID animal", "ID tumor", "group"), variable.name = "DPV", value.name = "0") %>% rename("Group"="group")
-        # dtemplate<-dtemplate[,c("Cage", "ID animal", "ID tumor", "Group", "DPV", "0")] %>% arrange(`ID animal`, `ID tumor`)
-        # template<-expand.grid(dades$db$MouseID, timepoint)
-        # colnames(template)<-c("MouseID", "Timepoint")
-        # template<-template[order(template$Timepoint, template$MouseID),]
-        # template<-merge(template, dades$db[c("MouseID", "group")])
-        # if (input$measure_sys == "L-W-D"){
-        #   template<-rbind(template, template, template)
-        #   template<-template[order(template$Timepoint, template$MouseID),]
-        #   template["TS"]<-rep(c("TS-Length", "TS-Width", "TS-Deep"), nrow(template)/3)
-        #   dtemplate<-dcast(template, MouseID+group+TS~Timepoint) 
-        #   dtemplate<-dtemplate[mixedorder(as.character(dtemplate$MouseID)),]
-        # }
-        # if (input$measure_sys == "Min-Max"){
-        #   template<-rbind(template, template)
-        #   template<-template[order(template$Timepoint, template$MouseID),]
-        #   template["DPV"]<-rep(c("Major", "Minor"), nrow(template)/2)
-        #   dtemplate<-dcast(template, MouseID+group+DPV~Timepoint)
-        #   dtemplate<-dtemplate[mixedorder(as.character(dtemplate$MouseID)),]
-        # }
-        # dtemplate<-dtemplate %>% add_column(.after="MouseID", "ID tumor"=dtemplate$MouseID)%>% rename(`ID animal`=MouseID)
-        # dtemplate["ID tumor"]<-gsub("[[:digit:]]","",dtemplate$`ID tumor`)
-        # dtemplate["ID animal"]<-gsub("[LR]","",dtemplate$`ID animal`)
-        # dtemplate[,5:ncol(dtemplate)]<-""
+        template<-dades$db %>% filter(!is.na(Group)) %>% 
+          select(Animal, Group) %>% unique()
+        dtemplate<-merge(dades$taula %>% select(-Group), template) %>% 
+          arrange(DayPostInoc, Animal, Side) %>% 
+          select(Cage, Animal, Date, DayPostInoc, Group, Side, 
+                 Weight, Long, Wide, Volume, Observations)
       }else{
         
         template<-data.frame(