"Añadir análisis no vacunación"

invivos/app.R

@@ -213,7 +213,7 @@ server <- function(input, output) {
   analysis$taula_def<-NULL
   observe({
     if (!is.null(input$file_analy)){ 
-      analysis$taula<-read.xlsx(input$file_analy$datapath, sheet = 1)
+      analysis$taula<-read.xlsx(input$file_analy$datapath, sheet = 1, check.names = F, sep.names = " ")
     }
   })
   output$ntable<-renderTable({
@@ -224,23 +224,28 @@ server <- function(input, output) {
       cutoff<-750
       
       table<-analysis$taula
-      table<- table %>% add_column("0"=0, .before="12")
-      table[table$ID.tumor == "R","0"]<-NA
-      table<-melt(table, id=colnames(table)[1:6], variable.name = "Timepoint")
+      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$ID.tumor == "R","0"]<-NA
+      col_nodays<-c("ID", "Cage","Group", "ID.animal","ID animal", "ID.tumor", "ID tumor", "TS","DPV", "Absorbance")
+      table<-melt(table, id=colnames(table)[colnames(table) %in% col_nodays], variable.name = "Timepoint")
+      table$Timepoint<-gsub("[A-Za-z ]","",table$Timepoint)
+      table$Timepoint<-factor(table$Timepoint, levels=mixedsort(as.numeric(as.character(unique(table$Timepoint)))))
       if ("DPV" %in% colnames(table)){
-        table<-dcast(table, Cage+ID.animal+ID.tumor+Group+Timepoint~DPV, value.var = "value")
+        table<-dcast(table, Cage+`ID animal`+`ID tumor`+Group+Timepoint~DPV, value.var = "value")
         table$Major<-table$Major/1000
         table$Minor<-table$Minor/1000
         table["Volume"]<-((table$Major*table$Minor*table$Minor)*(pi/6))*1000
       }
       if ("TS" %in% colnames(table)){
-        table<-dcast(table, Cage+ID.animal+ID.tumor+Group+Timepoint~TS, value.var = "value")
+        table<-dcast(table, Cage+`ID animal`+`ID tumor`+Group+Timepoint~TS, value.var = "value")
         table["Volume"]<-table$`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))
       analysis$taula_def<-table
-
-      table_plot<-dcast(dcast(table %>% filter(!is.na(Volume)), Cage+`ID.animal`+Group+Timepoint~., value.var = "Volume", fun.aggregate = mean), Group~Timepoint)
+      table_plot<-dcast(dcast(table %>% filter(!is.na(Volume)), `ID animal`+Group+Timepoint~., value.var = "Volume", fun.aggregate = mean), Group~Timepoint)
       table_plot
     }
   })
@@ -248,30 +253,55 @@ server <- function(input, output) {
     if (!is.null(input$file_analy) & !is.null(analysis$taula_def)){
       observeEvent(analysis$taula_def, {})
       table<-analysis$taula_def
-      ggplot(table, aes(as.numeric(as.character(Timepoint)), Volume, color=Group, group=Group))+
-        geom_errorbar(stat="summary", width=0.05)+
-        geom_line(stat="summary")+
-        geom_point(stat="summary")+
-        facet_grid(factor(ID.tumor, labels = c("Vaccination", "Rechallenge"))~., scale="free_y")+
-        labs(x="Days after tumor challenge")+
-        scale_y_continuous(expand = expansion(mult = c(0,0.05)))+
-        scale_x_continuous(expand = expansion(mult = c(0,0.05)), limits = c(0, (round(max(as.numeric(as.character(table$Timepoint))) / 5)+1)*5))+
-        theme_bw()
+      if (input$vacc == "Sí"){
+        ggplot(table, aes(as.numeric(as.character(Timepoint)), Volume, color=Group, group=Group))+
+          geom_errorbar(stat="summary", width=0.05)+
+          geom_line(stat="summary")+
+          geom_point(stat="summary")+
+          facet_grid(factor(`ID tumor`, labels = c("Vaccination", "Rechallenge"))~., scale="free_y")+
+          labs(x="Days after tumor challenge")+
+          scale_y_continuous(expand = expansion(mult = c(0,0.05)))+
+          scale_x_continuous(expand = expansion(mult = c(0,0.05)), limits = c(0, (round(max(as.numeric(as.character(table$Timepoint))) / 5)+1)*5))+
+          theme_bw()  
+      }else{
+        ggplot(table, aes(Timepoint, 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))
+      }
+      
     }
   })
   output$cin_indiv<-renderPlot({
     if (!is.null(input$file_analy) & !is.null(analysis$taula_def)){
       observeEvent(analysis$taula_def, {})
       table<-analysis$taula_def
-      ggplot(table, aes(as.numeric(as.character(Timepoint)), Volume, color=Group, group=paste0(Cage,ID.animal)))+
-        # geom_errorbar(stat="summary", width=0.05)+
-        geom_line()+
-        geom_point()+
-        scale_y_continuous(expand = expansion(mult = c(0,0.05)))+
-        scale_x_continuous(expand = expansion(mult = c(0,0.05)), limits = c(0, (round(max(as.numeric(as.character(table$Timepoint))) / 5)+1)*5))+
-        facet_grid(factor(ID.tumor, labels = c("Vaccination", "Rechallenge"))~Group, scale="free_y")+
-        labs(x="Days after tumor challenge")+
-        theme_bw()
+      if (input$vacc == "Sí"){
+        ggplot(table, aes(as.numeric(as.character(Timepoint)), Volume, color=Group, group=`ID animal`))+
+          # geom_errorbar(stat="summary", width=0.05)+
+          geom_line()+
+          geom_point()+
+          scale_y_continuous(expand = expansion(mult = c(0,0.05)))+
+          scale_x_continuous(expand = expansion(mult = c(0,0.05)), limits = c(0, (round(max(as.numeric(as.character(table$Timepoint))) / 5)+1)*5))+
+          facet_grid(factor(`ID tumor`, labels = c("Vaccination", "Rechallenge"))~Group, scale="free_y")+
+          labs(x="Days after tumor challenge")+
+          theme_bw()  
+      }else{
+        ggplot(table, aes(Timepoint, Volume, color=Group, group=`ID animal`))+
+          # geom_errorbar(stat="summary", width=0.05)+
+          geom_line()+
+          geom_point()+
+          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(as.numeric(as.character(table$Timepoint))) / 5)+1)*5))+
+          facet_wrap(.~Group)+
+          labs(x="Days after tumor challenge")+
+          theme_bw()+
+          theme(axis.text.x=element_text(angle=45, hjust=1))
+      }
     }
   })
   output$stats<-renderPrint({
@@ -281,16 +311,16 @@ server <- function(input, output) {
     if (!is.null(input$file_analy) & !is.null(analysis$taula_def)){
       observeEvent(analysis$taula_def, {})
       table<-analysis$taula_def
-      if (oneside != ""){
-        tableR<-filter(table, ID.tumor == rechallenge) %>% filter(!is.na(Volume))
-        summary(aov(Volume~Group+Timepoint+Error(ID.animal), data=table[table$ID.tumor == oneside,]))
+      if (input$vacc == "No"){
+        table<-filter(table, !is.na(Volume))
+        summary(aov(Volume~Group+Timepoint+Error(`ID animal`), data=table))
       }else{
         for (side in c("L","R")){
-          tableR<-filter(table, ID.tumor == side) %>% filter(!is.na(Volume))
+          tableR<-filter(table, `ID tumor` == side) %>% filter(!is.na(Volume))
           if (length(unique(tableR$Volume)) > 1 & length(unique(tableR$Timepoint)) > 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+Timepoint+Error(paste0(ID animal,Cage)), data=tableR)))
+            print(summary(aov(Volume~Group+Timepoint+Error(`ID animal`), data=tableR)))
           }
         }
       }
@@ -303,20 +333,37 @@ server <- function(input, output) {
     if (!is.null(input$file_analy) & !is.null(analysis$taula_def)){
       table<-analysis$taula_def
       table_stats<-list()
-      for (side in c("L","R")){
-        tableR<-filter(table, ID.tumor == side) %>% filter(!is.na(Volume))
-        if (length(unique(tableR$Volume)) > 1){
-          table_stats[[side]]<-multi_stats(tableR, "Volume", "Timepoint", "Group", stat.test=stattest)  
+      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_kw<-as.data.frame(matrix(nrow=0, ncol=2))
-        for (point in unique(tableR$Timepoint)){
-          len_group<-length(unique(tableR %>% filter(Timepoint == point) %>% pull(Group)))
+        for (point in unique(table$Timepoint)){
+          len_group<-length(unique(table %>% filter(Timepoint == 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(table %>% filter(Timepoint == point) %>% pull(Volume), table %>% filter(Timepoint == point) %>% pull(Group))[3][[1]]))
           }
         }
         colnames(table_kw)<-c("Timepoint", "KW-p.val")
-        table_stats[[side]]<-merge(table_stats[[side]], table_kw)
+        table_stats<-merge(table_stats, table_kw)
+        
+      }else{
+        for (side in c("L","R")){
+          tableR<-filter(table, `ID tumor` == side) %>% filter(!is.na(Volume))
+          if (length(unique(tableR$Volume)) > 1){
+            table_stats[[side]]<-multi_stats(tableR, "Volume", "Timepoint", "Group", stat.test=stattest)  
+          }
+          table_kw<-as.data.frame(matrix(nrow=0, ncol=2))
+          for (point in unique(tableR$Timepoint)){
+            len_group<-length(unique(tableR %>% filter(Timepoint == point) %>% pull(Group)))
+            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]]))
+            }
+          }
+          colnames(table_kw)<-c("Timepoint", "KW-p.val")
+          table_stats[[side]]<-merge(table_stats[[side]], table_kw)
+        }
       }
       table_stats_def<-bind_rows(table_stats, .id = "ID tumor")
       if (input$filter_stats == T){
@@ -329,5 +376,4 @@ server <- function(input, output) {
 }
 
 # Run the application 
-shinyApp(ui = ui, server = server)
-
+shinyApp(ui = ui, server = server)