Añadido curvas de superviviencia

invivos/app.R

@@ -8,6 +8,8 @@ library(ggbeeswarm)
 library(gtools)
 library(gridExtra)
 source("../../funcions.R")
+library(survminer)
+library(survival)
 
 # Define UI for application
 ui <- fluidPage(
@@ -34,6 +36,7 @@ ui <- fluidPage(
                        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(
@@ -42,6 +45,7 @@ ui <- fluidPage(
                          h3('Cinéticas'),
                          plotOutput('cin_group'),
                          plotOutput('cin_indiv'),
+                         plotOutput('survival', height="800px"),
                          h3('Estadística'),
                          verbatimTextOutput('stats'),
                          tableOutput('tab_stats')
@@ -248,7 +252,6 @@ server <- function(input, output) {
       if ("ID.tumor" %in% colnames(table)){table<-rename(table, "ID tumor"=`ID.tumor`)}
       # table[table$ID.tumor == "R","0"]<-NA
       col_nodays<-c("ID", "Cage","Group", "ID.animal","ID animal", "ID.tumor", "ID tumor", "TS","DPV", "Absorbance")
-      print(grep(0, colnames(table)[!colnames(table) %in% col_nodays]))
       if (length(grep(0, colnames(table)[!colnames(table) %in% col_nodays])) == 0){
         table["0"]<-0
       }
@@ -327,6 +330,54 @@ server <- function(input, output) {
       }
     }
   })
+  
+  output$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<-""
@@ -409,58 +460,106 @@ server <- function(input, output) {
     if (!is.null(input$file_analy) & !is.null(analysis$taula_def)){
       table<-analysis$taula_def
       
-      print(head(table))
-      
-      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 %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$colors, ",")[[1]]
+          g<-g+scale_color_manual(values=v_col)+
+            scale_fill_manual(values=v_col)
+        }
+      }else{
+        gg_color_hue <- function(n, l=65) {
+          hues <- seq(15, 375, length=n+1)
+          hcl(h=hues, l=l, c=100)[1:n]
         }
-      }
-      if (input$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()  
+          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{
-          g<-ggplot(table, aes(Timepoint, Volume, color=Group, group=`ID animal`))+
-            facet_wrap(.~Group)+
-            theme_bw()
+          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
+          )
         }
       }
       
-      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$colors, ",")[[1]]
-        g<-g+scale_color_manual(values=v_col)+
-          scale_fill_manual(values=v_col)
+      if (input$vacc == "Sí" & input$fig_id == "Survival"){
+        dades$plot<<-g_surv_vacc
+        arrange_ggsurvplots(g, nrow=2, ncol=1)
+      }else{
+          dades$plot<<-g
+          g
       }
-      dades$plot<<-g
-      g
     }
   }, res=72)
   
@@ -469,11 +568,16 @@ server <- function(input, output) {
       paste("Figura", ".png", sep="")
     },
     content = function(file){
-      print(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)
-      plot(dades$plot)
+      if (input$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()
       
     })