library(shiny)
library(openxlsx)
library(readxl)
library(ggplot2)
library(reshape2)
library(dplyr)
library(ggbeeswarm)
library(magrittr)
library(flextable)
source("funcions.R")

ui <- fluidPage(
    
    # Application title
    titlePanel("ELISPOTs"),
    
    sidebarLayout(
        sidebarPanel(
            fileInput(inputId = "file1", label = "Dades", multiple = F),
            selectInput(inputId = "test", "Test Estadístic", selected = "Ttest", choices = c("T-test (adj Holm)","Wilcoxon (adj Holm)")),
            sliderInput(inputId = "umbral_pos", "Mínimo para positivo:", min = 0, max=100, step = 5, value = 10),
            checkboxInput(inputId = "positive", label = "Mostrar positivitat", value = F),
            checkboxInput(inputId = "showstats", label = "Mostrar estadística", value = F),
            downloadButton("downloadData", "Descarregar Informe")
        ),
        
        mainPanel(
            plotOutput("distPlot"),
            uiOutput("flexstats")
        )
    )
)

# Define server logic required to draw a histogram
server <- function(input, output) {
    dades<-reactiveValues()
    dades$taula<-NULL
    dades$stats<-NULL
    observe({
        if (!is.null(input$file1)){ 
            dades$taula<-read_xlsx(input$file1$datapath)
        }
    })
    
    output$distPlot <- renderPlot({
        observeEvent(dades$taula, {})
        if (!is.null(dades$taula)){
            
            ctrl<-"Ctrl+"
            mock<-"Mock"
            
            table<-dades$taula[,colnames(dades$taula) != "Groups"]
            t_mean<-dcast(melt(table, id="Mice"),Mice~variable, mean, na.rm=T)
        
            t_substr<-data.frame("Mice"=t_mean[,1],
                                 as.data.frame(t(apply(t_mean[,2:ncol(table)], 1, function(x) x-x[mock])))
            )
            t_mean_group<-merge(t_mean, unique(dades$taula[c("Mice","Groups")]), id="Mice")
            mock_mean<-dcast(t_mean_group, Groups~., value.var=mock, mean)
            mock_mean[,2]<-mock_mean[,2]*2
            mock_mean[mock_mean$. < input$umbral_pos,2]<-input$umbral_pos
            
            t_substr<-merge(t_substr, unique(dades$taula[c("Mice","Groups")]), id="Mice")
            t_substr<-t_substr[,c(1, ncol(t_substr), 2:(ncol(t_substr)-1))]
            t_substr<-t_substr[,c("Mice", "Groups", colnames(t_substr)[!colnames(t_substr) %in% c("Mice", "Groups")])]
            t_substr[,3:ncol(t_substr)]<-apply(t_substr[,3:ncol(t_substr)],2, function(x) replace(x, which(x < 0),0))
            colnames(t_substr)<-c("Mice", "Groups", colnames(t_mean)[2:ncol(t_mean)])
            
            t_substr_gp<-t_substr
            t_substr_gp[3:ncol(t_substr)]<-apply(t_substr[3:ncol(t_substr)], 2, function(x) gsub(".",",",x, fixed=T))
            t_substr_gp<-t_substr_gp[order(factor(t_substr_gp$Mice, levels = unique(table$Mice))),]
            doc<-t(t_substr_gp)
            
            write.xlsx(doc, "data4graphpad.xlsx",rowNames=T)
            
            t<-melt(t_substr[,!colnames(t_substr) %in% c(ctrl, mock)])
            if (input$test == "T-test (adj Holm)"){
                t_stats<-multi_stats(t, "value", "variable", "Groups", stat.test = "ttest")
            }
            if (input$test == "Wilcoxon (adj Holm)"){
                t_stats<-multi_stats(t, "value", "variable", "Groups", stat.test = "wilcox")
            }
            
            dades$stats<<-t_stats
            t_stats<-t_stats %>% filter(p.signif != "ns")
            
            t_maps<-generate_labstats(t_stats, t, "value", "variable", "Groups")
            
            if (input$showstats == F){
                t_stats<-as.data.frame(matrix(nrow=0, ncol=6))
                colnames(t_stats)<-c("variable", "group1", "group2", "p.adj", "p.signif", "Method")
                t_maps<-list()
                t_maps[["label"]]<-as.data.frame(matrix(nrow = 0, ncol=2))
                colnames(t_maps$label)<-c("x", "y")
                t_maps[["brackets"]]<-as.data.frame(matrix(nrow = 0, ncol=4))
                colnames(t_maps$brackets)<-c("y1", "y2", "x1", "x2")
            }
            
            set.seed(123)
            if (input$positive == T){
                ggplot(melt(t_substr, id=c("Mice", ctrl, "Groups")), aes(variable, value))+
                    labs(x="", y="Spots/2.5*10^5 cells")+
                    # geom_errorbar(stat="summary", position=position_dodge(width=0.9), width=0.5, aes(fill=Groups))+
                    geom_hline(data=mock_mean, aes(color=Groups, yintercept = `.`))+
                    # geom_bar(stat="summary", position="dodge", color="black", aes(fill=Groups))+
                    geom_boxplot(color="black", aes(fill=Groups), alpha=0.4, outlier.alpha = 0)+
                    geom_jitter(position=position_jitterdodge(jitter.width = 0.2), shape=21, aes(fill=Groups), size=3)+
                    # geom_quasirandom(position = position_quasirandom(), shape=21)+
                    scale_x_discrete(limits=colnames(t_substr)[!colnames(t_substr) %in% c("Mice", "Groups", ctrl, mock)])+
                    geom_segment(data=t_maps$brackets, aes(x=x1, xend=x2, y=y1, yend=y2), color="black")+
                    geom_text(data=t_stats, aes(t_maps$label$x, t_maps$label$y, label=p.signif), color="black")+
                    theme_bw()+
                    theme(axis.text.x=element_text(angle=45, hjust=1))
            }else{
                ggplot(melt(t_substr, id=c("Mice", ctrl, "Groups")), aes(variable, value))+
                    labs(x="", y="Spots/2.5*10^5 cells")+
                    # geom_errorbar(stat="summary", position=position_dodge(width=0.9), width=0.5, aes(fill=Groups))+
                    # geom_bar(stat="summary", position="dodge", color="black", aes(fill=Groups))+
                    geom_boxplot(color="black", aes(fill=Groups), alpha=0.4, outlier.alpha = 0)+
                    geom_jitter(position=position_jitterdodge(jitter.width = 0.2), shape=21, aes(fill=Groups), size=3)+
                    # geom_quasirandom(width=0.2, position=position_dodge(), shape=21)+
                    scale_x_discrete(limits=colnames(t_substr)[!colnames(t_substr) %in% c("Mice", "Groups", ctrl, mock)])+
                    geom_segment(data=t_maps$brackets, aes(x=x1, xend=x2, y=y1, yend=y2), color="black")+
                    geom_text(data=t_stats, aes(t_maps$label$x, t_maps$label$y, label=p.signif), color="black")+
                    theme_bw()+
                    theme(axis.text.x=element_text(angle=45, hjust=1))
            }
        }
        
    })
    
    output$flexstats <- renderUI({
      observeEvent(dades$stats, {})
      t_stats<-dades$stats
      if (!is.null(dades$stats)){
        return(
          t_stats %>%
            flextable() %>%
            theme_vanilla() %>%
            fontsize(size=14, part="all") %>%
            padding(padding=10, part="all") %>%
            color(~ p.adj < 0.05, color = "red")%>%
            autofit()
        ) %>%
          htmltools_value()
      }
    })
    
    output$downloadData <- downloadHandler(
        filename = function() {
            paste("elispot", ".zip", sep="")
        },
        content = function(file){
            print(file)
            # tempReport <- file.path(tempdir(), "elispots.Rmd")
            # file.copy("elispots.Rmd", tempReport, overwrite = TRUE)
            params=list(file=input$file1$datapath, positive=input$positive, showstats=input$showstats, test=input$test, umbral_pos=input$umbral_pos)
            rmarkdown::render("elispots.Rmd", output_file="Results_elispot.html", params=params, envir = new.env(parent = globalenv()))
            zip(file,
                c("Results_elispot.html","data4graphpad.xlsx")
            )
            
        },
        contentType="application/zip"
    )
}

# Run the application 
shinyApp(ui = ui, server = server)