diff --git a/invivos/app.R b/invivos/app.R
deleted file mode 100755
index 820db34..0000000
--- a/invivos/app.R
+++ /dev/null
@@ -1,588 +0,0 @@
-library(shiny)
-library(ggplot2)
-library(reshape2)
-library(openxlsx)
-library(dplyr)
-library(car)
-library(ggbeeswarm)
-library(gtools)
-library(gridExtra)
-source("../../funcions.R")
-library(survminer)
-library(survival)
-
-# Define UI for application
-ui <- fluidPage(
-   
-   #Navbar
-   navbarPage("Seguimiento in vivos",
-              tabPanel("Diseño",
-                sidebarPanel(
-                  fileInput(inputId = "file_sizes", label = "Hoja de tamaños", multiple = F),
-                  selectInput(inputId = "measure_sys", "Sistema de medida", selected = "L-W-D", choices = c("L-W-D","Min-Max","Absorbance")),
-                  uiOutput('ncages'),
-                  uiOutput('lowcut'),
-                  uiOutput('upcut'),
-                  uiOutput('goButton'),
-                  uiOutput('iterations'),
-                  downloadButton("downloadData", "Descargar Excel")
-                  ),
-                mainPanel(
-                  plotOutput("firstPlot"),
-                  plotOutput("distPlot") 
-                )
-              ),
-              tabPanel("Análisis",
-                       sidebarPanel(
-                         fileInput(inputId = "file_analy", label = "Hoja de análisis", multiple = F),
-                         selectInput(inputId = "vacc", "Experimento de Vacunación", selected = "No", choices = c("Sí","No")),
-                         sliderInput("cutoff", "Cutoff para Survival", min=100, max=1500, step=50, value=750),
-                         checkboxInput("filter_stats","Filtrar Estadística")
-                       ),
-                       mainPanel(
-                         h3('Ratones'),
-                         tableOutput('ntable'),
-                         h3('Cinéticas'),
-                         plotOutput('cin_group'),
-                         plotOutput('cin_indiv'),
-                         plotOutput('survival', height="800px"),
-                         h3('Estadística'),
-                         verbatimTextOutput('stats'),
-                         tableOutput('tab_stats')
-                       )),
-              tabPanel("Exportar",
-                       sidebarPanel(width=2,
-                                    h3('Seleccionar figura'),
-                                    selectInput("fig_id", "", selected="", choices=c("Cinética Grupo", "Cinética Individual", "Survival")),
-                                    h3('Formato'),
-                                    sliderInput("width", "Ancho", min=1000, max=20000, step=1000, value=10000),
-                                    sliderInput("height", "Altura", min=1000, max=20000, step=1000, value=6000),
-                                    textInput("colors", label="Colors", value=""),
-                                    sliderInput("errorbar-width", "% Ancho errorbars", min=0.05, max=1, step=0.05, value=0.05),
-                                    sliderInput("point-size", "Tamaño puntos", min=1, max=10, step=1, value=3),
-                                    sliderInput("font-size", "Tamaño textos", min=5, max=30, step=1, value=11),
-                                    checkboxInput(inputId = "legend", label = "Mostrar llegenda", value = T),
-                                    selectInput("theme", "Seleccionar Tema", selected="BW", choices=c("BW", "Default", "Classic")),
-                                    downloadButton("downloadPicture", "Exportar")
-                       ),
-                       mainPanel(
-                         uiOutput("expPlotUI")
-                       )
-              )
-              )
-   
-   )
-
-# Define server logic required to draw a histogram
-server <- function(input, output) {
-  
-  # Diseño
-  dades<-reactiveValues()
-  dades$taula<-NULL
-  dades$groups<-NULL
-  dades$db<-NULL
-  observe({
-    if (!is.null(input$file_sizes)){ 
-      dades$taula<-read.xlsx(input$file_sizes$datapath, sheet = 1)
-      dades$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)
-    }
-  })
-  
-  output$iterations<-renderUI({
-    if (!is.null(dades$taula)){
-      sliderInput("iterations", "Iteraciones", min=100, max=2000, step=100, value=100) 
-    }
-  })
-  output$lowcut<-renderUI({
-    if (!is.null(dades$taula)){
-      sliderInput("lowcut", "Corte inferior", min=0, max=1000, step=5, value=0)
-    }
-  })
-  output$upcut<-renderUI({
-    if (!is.null(dades$taula)){
-      sliderInput("upcut", "Corte superior", min=0, max=1000, step=5, value=400)
-    }
-  })
-  output$goButton<-renderUI({
-    if (!is.null(dades$taula)){
-      actionButton("goButton", "Selecciona")
-    }
-  })
-  output$ncages<-renderUI({
-    if (is.null(dades$taula)){
-      sliderInput("ncages", "Cajas", min=1, max=10, value=1)
-    }
-  })
-  grafic<-eventReactive(input$goButton,{
-    df<-dades$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$MouseID)
-    
-    s<-shapiro.test(df$Volumen)[[2]]
-    
-    ngroup<-length(dades$groups)
-    
-    ind.list<-list()
-    pval.list<-list()
-    lvn.list<-list()
-    test.list<-list()
-    for (data in 1:input$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$group) > ceiling(nrow(df_temp)/5))
-      }
-      ind.list[[data]]<-df_temp[,c("MouseID","group")]
-      lvn.list[data]<-leveneTest(Volumen ~ group, data = df_temp[,3:4])[[2]][1]
-      if (s < 0.05){
-        k<-kruskal.test(df_temp$Volumen,df_temp$group)
-        test.list[data]<-k[[1]][1]
-        pval.list[data]<-k[[3]][1]
-      }else{
-        res.aov<-aov(Volumen~group, data=df_temp)
-        pval.list[data]<-summary(res.aov)[[1]][[5]][1]
-        test.list[data]<-summary(res.aov)[[1]][[4]][1]
-      }
-    }
-    
-    index<-which(unlist(lvn.list) == min(unlist(lvn.list)[which(unlist(pval.list) %in% sort(unlist(pval.list), decreasing = T)[1:20])]))
-    df_def<-merge(df, ind.list[[index]])
-    dades$db<-df_def
-    
-    ggplot(df_def, aes(group, Volumen))+
-      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$Volumen)+10))
-  })
-  output$distPlot <- renderPlot({
-    observeEvent(dades$taula, {})
-    if (!is.null(dades$taula)){
-      grafic()
-    }
-  })
-  
-  output$downloadData <- downloadHandler(
-    
-    filename = function() {
-      paste("invivo", ".xlsx", sep="")
-    },
-    content = function(file){
-      ncages<-input$ncages
-      nrat_cage<-5
-      id_tumors<-c("L","R")
-      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$`ID animal`)
-        dtemplate[,5:ncol(dtemplate)]<-""
-      }else{
-        template<-expand.grid(LETTERS[1:ncages], 1:5, id_tumors, timepoint)[,-2]
-        colnames(template)<-c("Cage", "ID tumor", "Timepoint")
-        nids<-length(id_tumors)*length(timepoint)
-        template[order(template$Cage),"ID animal"]<-rep(1:(nrow(template)/(nids)), each=nids)
-        template<-template[order(template$Timepoint, template$Cage, template$`ID animal`),]
-        template["Group"]<-""
-        if (input$measure_sys == "L-W-D"){
-          template<-rbind(template, template, template)
-          template<-template[order(template$Timepoint, template$Cage, template$`ID animal`, template$`ID tumor`),]
-          template["TS"]<-rep(c("TS-Length", "TS-Width", "TS-Deep"), nrow(template)/3)
-          dtemplate<-dcast(template, Cage+`ID animal`+`ID tumor`+Group+TS~Timepoint) 
-        }
-        if (input$measure_sys == "Min-Max"){
-          template<-rbind(template, template)
-          template<-template[order(template$Timepoint, template$Cage, template$`ID animal`, template$`ID tumor`),]
-          template["DPV"]<-rep(c("Major", "Minor"), nrow(template)/2)
-          dtemplate<-dcast(template, Cage+`ID animal`+`ID tumor`+Group+DPV~Timepoint)  
-        }
-        dtemplate[,6:ncol(dtemplate)]<-""
-      }
-      write.xlsx(dtemplate,file)
-    }
-  )
-  
-  # Análisis
-  analysis<-reactiveValues()
-  analysis$taula<-NULL
-  analysis$taula_def<-NULL
-  observe({
-    if (!is.null(input$file_analy)){ 
-      analysis$taula<-read.xlsx(input$file_analy$datapath, sheet = 1, check.names = F, sep.names = " ")
-    }
-  })
-  output$ntable<-renderTable({
-    if (!is.null(input$file_analy)){
-      observeEvent(analysis$taula, {})
-      stattest<-"dunn"
-      oneside<-""
-      cutoff<-750
-      
-      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", "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){
-        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)
-      if ("DPV" %in% colnames(table)){
-        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$Minor)*(pi/6))*1000
-      }
-      if ("TS" %in% colnames(table)){
-        table<-dcast(table, Cage+`ID animal`+`ID tumor`+Group+Timepoint~TS, value.var = "value")
-        table["Volume"]<-table$`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$Timepoint)))))
-      analysis$taula_def<-table
-      table_plot<-dcast(dcast(table %>% filter(!is.na(Volume)), `ID animal`+Group+Timepoint~., value.var = "Volume", fun.aggregate = mean), Group~Timepoint)
-      table_plot
-    }
-  })
-  output$cin_group<-renderPlot({
-    if (!is.null(input$file_analy) & !is.null(analysis$taula_def)){
-      observeEvent(analysis$taula_def, {})
-      table<-analysis$taula_def
-      if (input$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
-      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$Timepoint))) / 5)+1)*5))+
-          facet_wrap(.~Group)+
-          labs(x="Days after tumor challenge")+
-          theme_bw()+
-          theme(axis.text.x=element_text(angle=45, hjust=1))
-      }
-    }
-  })
-  
-  output$survival<-renderPlot({
-    if (!is.null(input$file_analy) & !is.null(analysis$taula_def)){
-      observeEvent(analysis$taula_def, {})
-      table<-analysis$taula_def
-      if (input$vacc == "Sí"){
-        g<-list()
-        for (side in c("L","R")){
-          tableR<-filter(table, `ID tumor` == side) %>% filter(!is.na(Volume))
-          endtime<-dcast(tableR %>% filter(Volume < cutoff), Cage+`ID animal`+`ID tumor`+Group~., value.var = "Timepoint", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
-          endtime["Dead"]<-dcast(tableR, Cage+`ID animal`+`ID tumor`+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") > input$cutoff
-          table_tumor<<-endtime
-          
-          g[side]<-ggsurvplot(survfit(Surv(table_tumor$end, table_tumor$Dead) ~ table_tumor$Group, data=table_tumor),
-                              pval = T, pval.method = T,
-                              title = side,
-                              # legend.labs = paste(c("< median", ">= median"), "MICA"),
-                              ggtheme=theme_classic(base_size=15)
-                              # conf.int = TRUE,
-                              # Add risk table
-                              # risk.table = TRUE,
-                              # tables.height = 0.2,
-                              # tables.theme = theme_cleantable(),
-                              
-                              # Color palettes. Use custom color: c("#E7B800", "#2E9FDF"),
-                              # or brewer color (e.g.: "Dark2"), or ggsci color (e.g.: "jco")
-                              # palette = c("#E7B800", "#2E9FDF")
-          )
-        }
-        do.call(grid.arrange, g)
-        
-      }else{
-        tableR<-table %>% filter(!is.na(Volume))
-        endtime<-dcast(tableR %>% filter(Volume < cutoff), `ID animal`+Group~., value.var = "Timepoint", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
-        endtime["Dead"]<-dcast(tableR, `ID animal`+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") > input$cutoff
-        table_tumor<<-endtime
-        
-        g<-ggsurvplot(survfit(Surv(table_tumor$end, table_tumor$Dead) ~ table_tumor$Group, data=table_tumor),
-                            pval = T, pval.method = T,
-                            # legend.labs = paste(c("< median", ">= median"), "MICA"),
-                            ggtheme=theme_classic(base_size=15)
-                            # palette = c("#E7B800", "#2E9FDF")
-        )
-        g
-      }
-    }
-  })
-  
-  output$stats<-renderPrint({
-    stattest<-"dunn"
-    oneside<-""
-    cutoff<-750
-    if (!is.null(input$file_analy) & !is.null(analysis$taula_def)){
-      observeEvent(analysis$taula_def, {})
-      table<-analysis$taula_def
-      if (input$vacc == "No"){
-        table<-filter(table, !is.na(Volume))
-        summary(aov(Volume~Group+Timepoint+Error(`ID animal`), data=table))
-      }else{
-        for (side in c("L","R")){
-          tableR<-filter(table, `ID tumor` == side) %>% filter(!is.na(Volume))
-          if (length(unique(tableR$Volume)) > 1 & length(unique(tableR$Timepoint)) > 1){
-            print(paste0("Side: ",side))
-            # print(summary(aov(Volume~Group+Timepoint+Error(paste0(ID animal,Cage)), data=tableR)))
-            print(summary(aov(Volume~Group+Timepoint+Error(`ID animal`), data=tableR)))
-          }
-        }
-      }
-    }
-  })
-  output$tab_stats<-renderTable({
-    stattest<-"dunn"
-    oneside<-""
-    cutoff<-750
-    if (!is.null(input$file_analy) & !is.null(analysis$taula_def)){
-      table<-analysis$taula_def
-      table_stats<-list()
-      if (input$vacc == "No"){
-        table<-table%>%filter(!is.na(Volume))
-        if (length(unique(table$Volume)) > 1){
-          table_stats<-multi_stats(table, "Volume", "Timepoint", "Group", stat.test=stattest)  
-        }
-        table_kw<-as.data.frame(matrix(nrow=0, ncol=2))
-        for (point in unique(table$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(table %>% filter(Timepoint == point) %>% pull(Volume), table %>% filter(Timepoint == point) %>% pull(Group))[3][[1]]))
-          }
-        }
-        colnames(table_kw)<-c("Timepoint", "KW-p.val")
-        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$filter_stats == T){
-        table_stats_def %>% filter(p.adj < 0.05)
-      }else{
-        table_stats_def 
-      }
-    }
-  })
-  
-  output$expPlotUI<- renderUI({
-    observeEvent(analysis$taula_def, {})
-    if (!is.null(input$file_analy) & !is.null(analysis$taula_def)){
-      plotOutput("expPlot", width=paste0(input$width/10,"px"), height = paste0(input$height/10, "px"))
-    }
-  })
-  
-  output$expPlot <- renderPlot({
-    observeEvent(analysis$taula_def, {})
-    if (!is.null(input$file_analy) & !is.null(analysis$taula_def)){
-      table<-analysis$taula_def
-      
-      if (input$fig_id %in% c("Cinética Grupo", "Cinética Individual")){
-        if (input$fig_id == "Cinética Grupo"){
-          if (input$vacc == "Sí"){
-            g<-ggplot(table, aes(as.numeric(as.character(Timepoint)), Volume, color=Group, group=Group))+
-              scale_x_continuous(expand = expansion(mult = c(0,0.05)), limits = c(0, (round(max(as.numeric(as.character(table$Timepoint))) / 5)+1)*5))+
-              facet_grid(factor(`ID tumor`, labels = c("Vaccination", "Rechallenge"))~., scale="free_y")+
-              theme_bw()  
-          }else{
-            g<-ggplot(table, aes(Timepoint, Volume, color=Group, group=Group))+
-              theme_bw()
-          }
-        }
-        if (input$fig_id == "Cinética Individual"){
-          if (input$vacc == "Sí"){
-            g<-ggplot(table, aes(as.numeric(as.character(Timepoint)), Volume, color=Group, group=Group))+
-              scale_x_continuous(expand = expansion(mult = c(0,0.05)), limits = c(0, (round(max(as.numeric(as.character(table$Timepoint))) / 5)+1)*5))+
-              facet_grid(factor(`ID tumor`, labels = c("Vaccination", "Rechallenge"))~Group, scale="free_y")+
-              theme_bw()  
-          }else{
-            g<-ggplot(table, aes(Timepoint, Volume, color=Group, group=`ID animal`))+
-              facet_wrap(.~Group)+
-              theme_bw()
-          }
-        }
-        
-        g<-g+geom_errorbar(stat="summary", width=input$`errorbar-width`)+
-          geom_line(stat="summary")+
-          geom_point(stat="summary", size=input$`point-size`)+
-          labs(x="Days after tumor challenge")+
-          scale_y_continuous(expand = expansion(mult = c(0,0.05)))
-        
-        if (input$theme == "BW"){
-          g<-g+theme_bw(base_size = input$`font-size`)
-        }
-        if (input$theme == "Classic"){
-          g<-g+theme_classic(base_size = input$`font-size`)  
-        }
-        if (input$theme == "Default"){
-          g<-g+theme_gray(base_size = input$`font-size`)
-        }
-        # g<-g+theme(axis.text.x=element_text(angle=45, hjust=1))
-        if (input$legend == F){
-          g<-g+guides(color=FALSE, fill=FALSE)
-        }
-        if (input$colors != ""){
-          v_col<-strsplit(input$colors, ",")[[1]]
-          g<-g+scale_color_manual(values=v_col)+
-            scale_fill_manual(values=v_col)
-        }
-      }else{
-        gg_color_hue <- function(n, l=65) {
-          hues <- seq(15, 375, length=n+1)
-          hcl(h=hues, l=l, c=100)[1:n]
-        }
-        if (input$vacc == "Sí"){
-          g<-list()
-          count<-1
-          for (side in c("L","R")){
-            tableR<-filter(table, `ID tumor` == side) %>% filter(!is.na(Volume))
-            endtime<-dcast(tableR %>% filter(Volume < cutoff), Cage+`ID animal`+`ID tumor`+Group~., value.var = "Timepoint", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% rename("end"=".")
-            endtime["Dead"]<-dcast(tableR, Cage+`ID animal`+`ID tumor`+Group~., value.var = "Volume", fun.aggregate = function(x){max(as.numeric(as.character(x)))}) %>% pull(".") > input$cutoff
-            table_tumor<<-endtime
-            if (input$colors != ""){
-              col<-input$colors
-            }else{
-              col<-gg_color_hue(length(unique(endtime$Group)))
-            }
-            g[[count]]<-ggsurvplot(survfit(Surv(table_tumor$end, table_tumor$Dead) ~ table_tumor$Group, data=table_tumor),
-                                pval = T, pval.method = T,
-                                title = side,
-                                # legend.labs = paste(c("< median", ">= median"), "MICA"),
-                                ggtheme=theme_classic(base_size=input$`font-size`),
-                                palette = col
-            )
-            count<-count+1
-          }
-          g_surv_vacc<-g
-          
-        }else{
-          if (input$colors != ""){
-            col<-input$colors
-          }else{
-            col<-gg_color_hue(length(unique(table_tumor$Group)))
-          }
-          g<-ggsurvplot(survfit(Surv(table_tumor$end, table_tumor$Dead) ~ table_tumor$Group, data=table_tumor),
-                        pval = T, pval.method = T,
-                        # legend.labs = paste(c("< median", ">= median"), "MICA"),
-                        ggtheme=theme_classic(base_size=input$`font-size`),
-                        palette = col
-          )
-        }
-      }
-      
-      if (input$vacc == "Sí" & input$fig_id == "Survival"){
-        dades$plot<<-g_surv_vacc
-        arrange_ggsurvplots(g, nrow=2, ncol=1)
-      }else{
-          dades$plot<<-g
-          g
-      }
-    }
-  }, res=72)
-  
-  output$downloadPicture <- downloadHandler(
-    filename = function() {
-      paste("Figura", ".png", sep="")
-    },
-    content = function(file){
-      # tempReport <- file.path(tempdir(), "elispots.Rmd")
-      # file.copy("elispots.Rmd", tempReport, overwrite = TRUE)
-      png(file, width = input$width, height=input$height, units = "px", res=720)
-      if (input$fig_id == "Survival"){
-        if (input$vacc == "Sí"){
-          arrange_ggsurvplots(dades$plot, nrow=2, ncol=1) 
-        }else{
-          arrange_ggsurvplots(list(dades$plot), ncol=1)  
-        }
-        }else{plot(dades$plot)}
-      dev.off()
-      
-    })
-  
-}
-
-# Run the application 
-shinyApp(ui = ui, server = server)
\ No newline at end of file