Corregir asignador de grupos

invivos/app.R

@@ -84,14 +84,24 @@ server <- function(input, output) {
   dades$db<-NULL
   observe({
     if (!is.null(input$file_sizes)){ 
-      dades$taula<-read.xlsx(input$file_sizes$datapath, sheet = 1)
+      taula<-read.xlsx(input$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$Minor)*(pi/6))
+      }
+      dades$taula<-taula
       dades$groups<-read.xlsx(input$file_sizes$datapath, sheet = 2)[,1]
     }
   })
   output$firstPlot <- renderPlot({
     observeEvent(dades$taula, {})
     if (!is.null(dades$taula)){
-      ggplot(dades$taula, aes(x="1", y=Volumen))+geom_quasirandom(width=0.2)
+      ggplot(dades$taula, aes(x="1", y=Volume))+geom_quasirandom(width=0.2)
     }
   })
   
@@ -124,13 +134,14 @@ server <- function(input, output) {
     df<-dades$taula
     up_cuttof<-input$upcut
     low_cuttof<-input$lowcut
-    df<-df[df$Volumen < up_cuttof & df$Volumen > low_cuttof,]
-    df["Mouse"]<-gsub("[a-zA-Z]", "", df$MouseID)
+    df<-df[df$Volume <= up_cuttof & df$Volume >= low_cuttof,]
     
-    s<-shapiro.test(df$Volumen)[[2]]
     
-    ngroup<-length(dades$groups)
+    # df["Mouse"]<-gsub("[a-zA-Z]", "", df$MouseID)
+    print(df$Volume)
+    s<-shapiro.test(df$Volume)[[2]]
     
+    ngroup<-length(dades$groups)
     ind.list<-list()
     pval.list<-list()
     lvn.list<-list()
@@ -138,32 +149,39 @@ server <- function(input, output) {
     for (data in 1:input$iterations){
       interr=T
       while(interr == T){
-        ind<-sample(rep(dades$groups, each=7), length(unique(df$Mouse)))
-        df_temp<-merge(df, data.frame("Mouse"=unique(df$Mouse), "group"=as.factor(ind)))
-        interr<-any(table(df_temp$group) < floor(nrow(df_temp)/5) | table(df_temp$group) > ceiling(nrow(df_temp)/5))
+        ind<-sample(rep(dades$groups, each=ceiling(length(unique(df$`ID animal`))/ngroup)), length(unique(df$`ID animal`)))
+        df_temp<-merge(df[,c("ID animal", "ID tumor","Volume")], data.frame("ID animal"=unique(df$`ID animal`), "group"=as.factor(ind),check.names=F))
+        if ((nrow(df_temp)/ngroup) %% 2 == 0){
+          interr<-any(table(df_temp$group) < floor(nrow(df_temp)/ngroup) | table(df_temp$group) > ceiling(nrow(df_temp)/ngroup))  
+        }else{
+          interr<-any(table(df_temp$group) < (floor(nrow(df_temp)/ngroup)-1) | table(df_temp$group) > (ceiling(nrow(df_temp)/ngroup)+1))
+        }
       }
-      ind.list[[data]]<-df_temp[,c("MouseID","group")]
-      lvn.list[data]<-leveneTest(Volumen ~ group, data = df_temp[,3:4])[[2]][1]
+      ind.list[[data]]<-df_temp[,c("ID animal", "ID tumor","group","Volume")]
+      lvn.list[data]<-leveneTest(Volume ~ group, data = df_temp[,3:4])[[2]][1]
       if (s < 0.05){
-        k<-kruskal.test(df_temp$Volumen,df_temp$group)
+        k<-kruskal.test(df_temp$Volume,df_temp$group)
         test.list[data]<-k[[1]][1]
         pval.list[data]<-k[[3]][1]
       }else{
-        res.aov<-aov(Volumen~group, data=df_temp)
+        res.aov<-aov(Volume~group, data=df_temp)
         pval.list[data]<-summary(res.aov)[[1]][[5]][1]
         test.list[data]<-summary(res.aov)[[1]][[4]][1]
       }
     }
-    
     index<-which(unlist(lvn.list) == min(unlist(lvn.list)[which(unlist(pval.list) %in% sort(unlist(pval.list), decreasing = T)[1:20])]))
     df_def<-merge(df, ind.list[[index]])
+    if ("Group" %in% colnames(df_def)){
+      df_def<-df_def %>% select(-"Group") 
+    }
     dades$db<-df_def
+    print(df_def)
     
-    ggplot(df_def, aes(group, Volumen))+
+    ggplot(df_def, aes(group, Volume))+
       geom_boxplot(outlier.alpha = F)+
       geom_jitter(width=0.25)+
-      geom_point(stat="summary", color="blue", size=3)+
-      lims(y=c(0,max(df_def$Volumen)+10))
+      geom_point(stat="summary", color="blue", size=3)
+      # lims(y=c(0,max(df_def$Volume)+10))
   })
   output$distPlot <- renderPlot({
     observeEvent(dades$taula, {})
@@ -184,28 +202,31 @@ server <- function(input, output) {
       timepoint<-c(7,10,13,16,19,22,25)
       
       if (!is.null(input$file_sizes)){
-        template<-expand.grid(dades$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$`ID animal`)
-        dtemplate[,5:ncol(dtemplate)]<-""
+        dtemplate<-df$db %>% select(-Volume)
+        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")]
+        # 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)]<-""
       }else{
         template<-expand.grid(LETTERS[1:ncages], 1:5, id_tumors, timepoint)[,-2]
         colnames(template)<-c("Cage", "ID tumor", "Timepoint")