library(shiny)
library(rhandsontable)
library(openCyto)
library(flowCore)
library(flowWorkspace)
library(CytoML)
library(ggcyto)
library(reshape2)
library(Matrix)
library(CitFuns)
library(BDCIT)
library(tidyverse)

print(getwd())
source("../sqlFunctions.R", encoding = "UTF-8")

DF<-data.frame("NHC"="","Samples"="")
samples<-data.frame("UMID"="","UM"="")
CLINICS<-data.frame("UMID"="","UM"="")
cnag<-data.frame("UMID"="","UM"="")
rna<-data.frame("UMID"="","UM"="")

# Cargar dependencias
sqlInitialize(ruta="../ruta_database.R")


# UI ----

ui <- fluidPage(

    # Application title
    #titlePanel("BDAccess"),
    
    #sidebarLayout(
    #Navbar
    navbarPage("BDAccess",

## Update ----
        tabPanel("Update",
            sidebarPanel(
                selectInput("dbtype", "", selected="UM", choices=c("UM", "OV","CC")),
                checkboxInput(inputId = "backup", label="Backup", value=F),
                actionButton("butdbtype", "Carrega BD"),
                hr(),
                fileInput(inputId = "file_query", label = "Plantilla", multiple = F),
                actionButton("impNHC", "Importa NHC"),
                actionButton("goButton", "Genera PATID"),
                hr(),
                actionButton("filltemplate", "Plantilla"),
                hr(),
                actionButton("synctemplate", "Sincronizar")
            ),
    
            mainPanel(
                tabsetPanel(
                    tabPanel("NHC", rHandsontableOutput("hot")),
                    tabPanel("Samples",rHandsontableOutput("samples")),
                    tabPanel("CLINICS",rHandsontableOutput("CLINICS")),
                    tabPanel("CNAG",rHandsontableOutput("cnag")),
                    tabPanel("RNADNA",rHandsontableOutput("rna")),
                )
            )
        ),

## Visor ----
        tabPanel("Visor",
            sidebarPanel(
                radioButtons("nhc", label = h3("Código"),
                             choices = list("NHC" = 1, "UMID/OVID" = 2, "UM/OV"=3), 
                             selected = 2),
                textInput("id", label = "ID", value = ""),
                actionButton("nitrosync", "Actualiza Nitrógeno")
            ),
            mainPanel(
                htmlOutput("report"),
                h3("Nitrogen"),
                tableOutput("nitrogen"),
                plotOutput("visorplot", height = "1000px")
            )
        ),

## Citometría ----
        tabPanel("Citometría",
                 sidebarPanel(
                     selectInput("phenotype", "Tipo de análisis", selected="Pop", choices=c("Pop", "IC")),
                 ),
                 mainPanel(
                     tabsetPanel(
                         tabPanel("Entrada",
                             actionButton("goButtonDir","Selecciona directorio fenotipo"),
                             textOutput("session"),
                             hr(),
                             actionButton("fcsconvert", "Convertir a fcs"),
                             hr(),
                             actionButton("pngexport", "Exportar informes"),
                             actionButton("popexport", "Actualizar BBDD")
                        ),
                        tabPanel("Visor",

                        )
                     )
                 )
        ),

## scRNAseq ----
        tabPanel("scRNAseq",
                 sidebarPanel(
                     textInput("sqlquery", label = "sqlquery", value = ""),
                     uiOutput("PATID"),
                     checkboxInput("sct_sel", "Mostrar filtrados"),
                     checkboxInput("cd45_chk", "Purificación CD45"),
                     textInput("genes", label="genes", value = "")
                 ),
                 mainPanel(
                     tabsetPanel(
                         tabPanel("Table", tableOutput("sc_table")),
                         tabPanel("Plots", 
                                  plotOutput("sc_plot", height = "1000px"),
                                  plotOutput("sc_expr"), height = "600px")
                     )
                 )
        )
    )
)

# Define server logic required to draw a histogram
# Server ----
server <- function(input, output) {

## Update ----

    values <- reactiveValues()
    values[["DF"]]<-DF
    values[["samples"]]<-samples
    values[["CLINICS"]]<-CLINICS
    values[["cnag"]]<-cnag
    values[["rna"]]<-rna
    values[["Excel"]]<-""
    
    observeEvent(input$butdbtype, {
        print(UMfile)
        print(OVfile)
        print(CCfile)
        if (input$dbtype == "UM"){
            dta<<-odbcConnectAccess2007(access.file = UMfile, 
                                        pwd = .rs.askForPassword("Enter password:"))
        }
        if (input$dbtype == "OV"){
            dta<<-odbcConnectAccess2007(access.file = OVfile, 
                                        pwd = .rs.askForPassword("Enter password:"))
        }
        if (input$dbtype == "CC"){
            dta<<-odbcConnectAccess2007(access.file = CCfile, 
                                        pwd = .rs.askForPassword("Enter password:"))
        }
        print(dta)
        if (input$backup == T){
            if (! input$dbtype %in% c("UM","OV")){
                sqlBackUp(bu.dir="CC_BU")
            }else{
                sqlBackUp()   
            }
                
        }
    })
    
    # observe({
    #     if (!is.null(input$file_access)){ 
    #         # Inicializar conexión
    #         dta<<-odbcConnectAccess2007(access.file = file, 
    #                                    pwd = .rs.askForPassword("Enter password:"))
    #         print(dta)
    #         sqlBackUp()
    #     }
    # })
    
    observe({
        if (!is.null(input$file_query)){
            ## Importamos los NHC de las muestras nuevas
            values[["Excel"]]<-read.xlsx(input$file_query$datapath, sheet = "NHC") %>% pull(NHC) %>% as.character()
            print(values[["Excel"]])
        }
    })
    observeEvent(input$impNHC, {
        values[["DF"]]<-merge(values[["DF"]], data.frame("NHC"=values[["Excel"]]), all.y=T)
    })
    
    ## Handsontable
    observe({
        if (!is.null(input$hot)) {
            DF = hot_to_r(input$hot)
        } else {
            if (is.null(values[["DF"]])){
                DF <- DF
            }
            else{
                DF <- values[["DF"]]
            }
        }
        values[["DF"]] <- DF
    })
    
    output$hot <- renderRHandsontable({
        if (!is.null(DF)){
            rhandsontable(values[["DF"]], stretchH = "all", readOnly = F, useTypes = T)   
        }
    })
    
    observe({
        if (!is.null(input$samples)) {
            samples = hot_to_r(input$samples)
        } else {
            if (is.null(values[["samples"]])){
                samples <- samples
            }
            else{
                samples <- values[["samples"]]
            }
        }
        values[["samples"]] <- samples
    })
    
    output$samples <- renderRHandsontable({
        if (!is.null(samples)){
            rhandsontable(values[["samples"]], stretchH = "all", readOnly = F, useTypes = T)
        }
    })
    
    observe({
        if (!is.null(input$CLINICS)) {
            CLINICS = hot_to_r(input$CLINICS)
        } else {
            if (is.null(values[["CLINICS"]])){
                CLINICS <- CLINICS
            }
            else{
                CLINICS <- values[["CLINICS"]]
            }
        }
        values[["CLINICS"]] <- CLINICS
    })
    
    output$CLINICS <- renderRHandsontable({
        if (!is.null(CLINICS)){
            rhandsontable(values[["CLINICS"]], stretchH = "all", readOnly = F, useTypes = T) %>% 
                hot_col(values[["CLINICS"]] %>% select(lubridate::is.Date) %>% colnames, 
                        dateFormat = "DD/MM/YYYY", type = "date")
        }
    })
    
    observe({
        if (!is.null(input$cnag)) {
            cnag = hot_to_r(input$cnag)
        } else {
            if (is.null(values[["cnag"]])){
                cnag <- cnag
            }
            else{
                cnag <- values[["cnag"]]
            }
        }
        values[["cnag"]] <- cnag
    })
    
    output$cnag <- renderRHandsontable({
        if (!is.null(cnag)){
            rhandsontable(values[["cnag"]], stretchH = "all", readOnly = F, useTypes = T)   
        }
    })
    
    observe({
        if (!is.null(input$rna)) {
            rna = hot_to_r(input$rna)
        } else {
            if (is.null(values[["rna"]])){
                rna <- rna
            }
            else{
                rna <- values[["rna"]]
            }
        }
        values[["rna"]] <- rna
    })
    
    output$rna <- renderRHandsontable({
        if (!is.null(rna)){
            rhandsontable(values[["rna"]], stretchH = "all", readOnly = F, useTypes = T)   
        }
    })
    
    observeEvent(input$goButton, {

        if (input$dbtype %in% c("UM","OV")){
            sqlGenOVID(dta, nhcs = values[["DF"]]$NHC, sinc=T)
        }
        if (input$dbtype %in% c("CC")){
            sqlGenOVID(dta, nhcs = values[["DF"]]$NHC, sinc=T, dbtype = input$dbtype)
        }
            
        if (input$dbtype == "UM"){
            values[["DF"]]<-merge(values[["DF"]], sqlFetch(dta, "UMID"))
        }
        if (input$dbtype == "OV"){
            values[["DF"]]<-merge(values[["DF"]], sqlFetch(dta, "OVID"))
        }
        if (input$dbtype == "CC"){
            values[["DF"]]<-merge(values[["DF"]], sqlFetch(dta, "PATID"))
        }
        print(values[["DF"]])
    })

    observeEvent(input$filltemplate,{
        today=T
        if (input$dbtype == "UM"){
            upd.umid<-sqlFetch(dta, "UMID") %>% filter(NHC %in% values[["DF"]]$NHC)
            ## Generar código para las nuevas muestras
            samples<-sqlFetch(dta, "MUESTRAS")
            if(sum(grepl(paste0("UM",Sys.time() %>% format("%y")), samples$CODIGO)) > 0){
                next.samp<-gsub(paste0("UM",Sys.time() %>% format("%y")),"", samples$CODIGO) %>% as.numeric %>% max(na.rm=T)+1  
            }else{
                next.samp<-1
            }
            last.samp<-next.samp+(length(values[["DF"]]$NHC)-1)
            new.samp<-sprintf("UM%s%02d",Sys.time() %>% format("%y"),next.samp:last.samp)
            new.samp.df<-data.frame("NHC"=values[["DF"]]$NHC, "CODIGO"=new.samp) %>% merge(sqlFetch(dta,"UMID"), all.x=T) %>% arrange(CODIGO)
            samples.exp<-merge(samples %>% slice(0), new.samp.df %>% select(-NHC), all=T) %>% select(colnames(samples)) %>% arrange(CODIGO)
            if (today==TRUE){
                samples.exp$FECHA_RECEPCION<-format(Sys.Date(), "%d/%m/%y")
            }
            
            nhc.table<-values[["DF"]]
            
            if (any(sapply(nhc.table$Samples, function(x) "cnag" %in% strsplit(x,",")[[1]]) == T)){
                nhcs.cnag<-nhc.table[sapply(nhc.table$Samples, function(x) "cnag" %in% strsplit(x,",")[[1]]),"NHC"]
                umid.cnag<-sqlFetch(dta, "UMID") %>% filter(NHC %in% nhcs.cnag) %>% pull(UMID)
                sample.cnag<-samples.exp %>% filter(UMID %in% umid.cnag) %>% pull(CODIGO)
                cnag.exp<-merge(data.frame("UMID"=umid.cnag, "CODIGO"=sample.cnag), sqlFetch(dta, "CNAG") %>% slice(0), all=T)
                if (today==TRUE){
                    cnag.exp$FECHA_ENVIO<-format(Sys.Date(), "%d/%m/%y")
                }
            }else{
                cnag.exp<-sqlFetch(dta, "CNAG") %>% slice(0) %>% 
                    mutate(across(lubridate::is.POSIXct, as.character))
                }
            if (any(sapply(nhc.table$Samples, function(x) "rna" %in% strsplit(x,",")[[1]]) == T)){
                nhcs.rna<-nhc.table[sapply(nhc.table$Samples, function(x) "rna" %in% strsplit(x,",")[[1]]),"NHC"]
                umid.rna<-sqlFetch(dta, "UMID") %>% filter(NHC %in% nhcs.rna) %>% pull(UMID)
                sample.rna<-samples.exp %>% filter(UMID %in% umid.rna) %>% pull(CODIGO)
                rna.exp<-merge(data.frame("UMID"=umid.rna, "CODIGO"=sample.rna), sqlFetch(dta, "RNADNA") %>% slice(0)%>% 
                                   mutate(across(lubridate::is.POSIXct, as.character)), all=T)
            }else{
                rna.exp<-sqlFetch(dta, "RNADNA") %>% slice(0) %>% 
                    mutate(across(lubridate::is.POSIXct, as.character))
                }
            
            ## Importar los datos clínicos de pacientes existentes y generar nueva entrada par los nuevos
            upd.clinics<-sqlFetch(dta, "CLINICOS")
            umid.new<-sqlFetch(dta, "UMID") %>% filter(NHC %in% values[["DF"]]$NHC)
            upd.clinics<-merge(umid.new,upd.clinics, all.x=T, by="UMID")
            upd.clinics$NHC<-as.character(upd.clinics$NHC)
            for (i in colnames(upd.clinics)[sapply(upd.clinics, lubridate::is.POSIXct)]){upd.clinics[,i]<-as.Date(upd.clinics[,i])}
            
            values[["samples"]]<-samples.exp
            values[["CLINICS"]]<-upd.clinics
            values[["cnag"]]<-cnag.exp
            values[["rna"]]<-rna.exp
        }
        if (input$dbtype == "OV"){
            upd.umid<-sqlFetch(dta, "OVID") %>% filter(NHC %in% values[["DF"]]$NHC)
            ## Generar código para las nuevas muestras
            samples<-sqlFetch(dta, "SAMPLES")
            if(sum(grepl(paste0("OV",Sys.time() %>% format("%y")), samples$samples)) > 0){
                next.samp<-gsub(paste0("OV",Sys.time() %>% format("%y")),"", samples$samples) %>% as.numeric %>% max(na.rm=T)+1  
            }else{
                next.samp<-1
            }
            last.samp<-next.samp+(length(values[["DF"]]$NHC)-1)
            new.samp<-sprintf("OV%s%02d",Sys.time() %>% format("%y"),next.samp:last.samp)
            new.samp.df<-data.frame("NHC"=values[["DF"]]$NHC, "samples"=new.samp) %>% merge(sqlFetch(dta,"OVID"), all.x=T) %>% arrange(samples)
            samples.exp<-merge(samples %>% slice(0), new.samp.df %>% select(-NHC), all=T) %>% select(colnames(samples)) %>% arrange(samples)
            if (today==TRUE){
                samples.exp$IQ_date<-format(Sys.Date(), "%d/%m/%y")
            }
            
            nhc.table<-values[["DF"]]
            
            ## Importar los datos clínicos de pacientes existentes y generar nueva entrada par los nuevos
            upd.clinics<-sqlFetch(dta, "CLINICS")
            umid.new<-sqlFetch(dta, "OVID") %>% filter(NHC %in% values[["DF"]]$NHC)
            upd.clinics<-merge(umid.new,upd.clinics, all.x=T, by="OVID")
            upd.clinics$NHC<-as.character(upd.clinics$NHC)
            for (i in colnames(upd.clinics)[sapply(upd.clinics, lubridate::is.POSIXct)]){upd.clinics[,i]<-as.Date(upd.clinics[,i])}
            
            values[["samples"]]<-samples.exp %>% mutate(across(lubridate::is.POSIXct, as.character))
            values[["CLINICS"]]<-upd.clinics %>% mutate(across(lubridate::is.POSIXct, as.character))
        }
        
        if (input$dbtype %in% c("CC")){
            upd.umid<-sqlFetch(dta, "PATID") %>% filter(NHC %in% values[["DF"]]$NHC)
            ## Generar código para las nuevas muestras
            samples<-sqlFetch(dta, "MUESTRAS")
            if(sum(grepl(paste0(input$dbtype,Sys.time() %>% format("%y")), samples$CODIGO)) > 0){
                next.samp<-gsub(paste0(input$dbtype,Sys.time() %>% format("%y")),"", samples$CODIGO) %>% as.numeric %>% max(na.rm=T)+1  
            }else{
                next.samp<-1
            }
            last.samp<-next.samp+(length(values[["DF"]]$NHC)-1)
            new.samp<-sprintf("%s%s%02d",input$dbtype,Sys.time() %>% format("%y"),next.samp:last.samp)
            new.samp.df<-data.frame("NHC"=values[["DF"]]$NHC, "CODIGO"=new.samp) %>% merge(sqlFetch(dta,"PATID"), all.x=T) %>% arrange(CODIGO)
            samples.exp<-merge(samples %>% slice(0), new.samp.df %>% select(-NHC), all=T) %>% select(colnames(samples)) %>% arrange(CODIGO)
            if (today==TRUE){
                samples.exp$FECHA_RECEPCION<-format(Sys.Date(), "%d/%m/%y")
            }
            
            nhc.table<-values[["DF"]]
            
            if (any(sapply(nhc.table$Samples, function(x) "cnag" %in% strsplit(x,",")[[1]]) == T)){
                nhcs.cnag<-nhc.table[sapply(nhc.table$Samples, function(x) "cnag" %in% strsplit(x,",")[[1]]),"NHC"]
                umid.cnag<-sqlFetch(dta, "PATID") %>% filter(NHC %in% nhcs.cnag) %>% pull(PATID)
                sample.cnag<-samples.exp %>% filter(PATID %in% umid.cnag) %>% pull(CODIGO)
                cnag.exp<-merge(data.frame("PATID"=umid.cnag, "CODIGO"=sample.cnag), sqlFetch(dta, "CNAG") %>% slice(0), all=T)
                if (today==TRUE){
                    cnag.exp$FECHA_ENVIO<-format(Sys.Date(), "%d/%m/%y")
                }
            }else{
                cnag.exp<-sqlFetch(dta, "CNAG") %>% slice(0) %>% 
                    mutate(across(lubridate::is.POSIXct, as.character))
            }
            if (any(sapply(nhc.table$Samples, function(x) "rna" %in% strsplit(x,",")[[1]]) == T)){
                nhcs.rna<-nhc.table[sapply(nhc.table$Samples, function(x) "rna" %in% strsplit(x,",")[[1]]),"NHC"]
                umid.rna<-sqlFetch(dta, "PATID") %>% filter(NHC %in% nhcs.rna) %>% pull(PATID)
                sample.rna<-samples.exp %>% filter(PATID %in% umid.rna) %>% pull(CODIGO)
                rna.exp<-merge(data.frame("PATID"=umid.rna, "CODIGO"=sample.rna), sqlFetch(dta, "RNADNA") %>% slice(0)%>% 
                                   mutate(across(lubridate::is.POSIXct, as.character)), all=T)
            }else{
                rna.exp<-sqlFetch(dta, "RNADNA") %>% slice(0) %>% 
                    mutate(across(lubridate::is.POSIXct, as.character))
            }
            
            ## Importar los datos clínicos de pacientes existentes y generar nueva entrada par los nuevos
            upd.clinics<-sqlFetch(dta, "CLINICOS")
            umid.new<-sqlFetch(dta, "PATID") %>% filter(NHC %in% values[["DF"]]$NHC)
            upd.clinics<-merge(umid.new,upd.clinics, all.x=T, by="PATID")
            upd.clinics$NHC<-as.character(upd.clinics$NHC)
            for (i in colnames(upd.clinics)[sapply(upd.clinics, lubridate::is.POSIXct)]){upd.clinics[,i]<-as.Date(upd.clinics[,i])}
            
            values[["samples"]]<-samples.exp
            values[["CLINICS"]]<-upd.clinics
            values[["cnag"]]<-cnag.exp
            values[["rna"]]<-rna.exp
        }
        
    })
    
    observeEvent(input$synctemplate,{
        if (input$dbtype == "UM"){
            # conn=dta, filetemp="queryOV.xlsx", sinc.samples=F, sinc.clinics=F, dbtype=NULL
            
            ## Nuevas entradas en MUESTRAS
            nsamples<-values[["samples"]] %>% nrow
            upd.samples<-values[["samples"]]
            if (nrow(upd.samples) > 0){rownames(upd.samples)<-(nsamples+1):(nsamples+nrow(upd.samples)) %>% as.character}
            
            if (nrow(upd.samples) > 0){
                upd.samples$FECHA_RECEPCION<-lubridate::parse_date_time(upd.samples$FECHA_RECEPCION, c("d/m/Y","d/m/y")) %>% as.Date()
                upd.samples$TIPO<-as.character(upd.samples$TIPO)
                upd.samples$OBS<-as.character(upd.samples$OBS)
                ### !! Atención, esto cambia la base de datos:
                sqlSave(dta, upd.samples, tablename="MUESTRAS", append = T, varTypes = c("FECHA_RECEPCION"="Date"), rownames = F)
                print("Tabla MUESTRAS sincronizada.")
            }
        
            ## Entradas modificadas en CLINICOS
            upd.clinics<-values[["CLINICS"]]
            umid.mod<-upd.clinics$UMID[upd.clinics$UMID %in% (sqlFetch(dta, "CLINICOS") %>% pull(UMID))]
            rnames<-sqlFetch(dta, "CLINICOS") %>% filter(UMID %in% umid.mod) %>% rownames
            clinics.mod<-upd.clinics %>% filter(UMID %in% umid.mod) %>% select(-NHC)
            rownames(clinics.mod)<-rnames
            
            ### !! Atención, esto cambia la base de datos:
            fechas<-colnames(clinics.mod)[grepl("date|MET_DX|DoB", colnames(clinics.mod), ignore.case = T)]
            for (i in fechas){
                clinics.mod[,i]<-lubridate::parse_date_time(clinics.mod[,i], c("d/m/Y","d/m/y")) %>% as.Date()
            }
            sqlUpdate(dta, clinics.mod,"CLINICOS", index="UMID")
            print("Tabla CLINICOS modificada.")
            
            ## Nuevas entradas en CLINICOS
            nsamples.clin<-sqlFetch(dta, "CLINICOS") %>% nrow
            umid.new<-upd.clinics$UMID[!upd.clinics$UMID %in% (sqlFetch(dta, "CLINICOS") %>% pull(UMID))]
            clinics.new<-upd.clinics %>% filter(UMID %in% umid.new) %>% select(-NHC)
            if (length(umid.new) > 0){rownames(clinics.new)<-(nsamples.clin+1):(nsamples.clin+nrow(clinics.new)) %>% as.character}
            
            ### !! Atención, esto cambia la base de datos:
            fechas<-colnames(clinics.new)[grepl("date|MET_DX|DoB", colnames(clinics.new), ignore.case = T)]
            varTypes<-rep("Date",length(fechas))
            names(varTypes)<-fechas
            for (i in fechas){
                clinics.new[,i]<-lubridate::parse_date_time(clinics.new[,i], c("d/m/Y","d/m/y","Y-m-d")) %>% as.Date()
            }
            sqlSave(dta, clinics.new, tablename="CLINICOS", append = T, varTypes = varTypes, rownames = F)
            print("Tabla CLINICOS sincronizada.")
            
            ## Nuevas entradas en CNAG
            if (nrow(values[["cnag"]]) > 0){
                cnag.sync<-values[["cnag"]]
                fechas<-colnames(cnag.sync)[sqlFetch(dta, "CNAG") %>% sapply(lubridate::is.POSIXct)]
                varTypes<-rep("Date",length(fechas))
                names(varTypes)<-fechas
                print(fechas)
                for (i in fechas){
                    cnag.sync[,i]<-lubridate::parse_date_time(cnag.sync[,i], c("d/m/Y","d/m/y","Y-m-d")) %>% as.Date()
                }
                sqlSave(dta, cnag.sync, tablename="CNAG", append = T, varTypes = varTypes, rownames = F)
            }
            
            ## Nuevas entradas en RNADNA
            if (nrow(values[["rna"]]) > 0){
                rna.sync<-values[["rna"]]
                fechas<-colnames(rna.sync)[sqlFetch(dta, "RNADNA") %>% sapply(lubridate::is.POSIXct)]
                varTypes<-rep("Date",length(fechas))
                names(varTypes)<-fechas
                for (i in fechas){
                    rna.sync[,i]<-lubridate::parse_date_time(rna.sync[,i], c("d/m/Y","d/m/y","Y-m-d")) %>% as.Date()
                }
                sqlSave(dta, rna.sync, tablename="RNADNA", append = T, varTypes = varTypes, rownames = F)
            }
        }
        if (input$dbtype == "OV"){
            ## Nuevas entradas en SAMPLES
            nsamples<-values[["samples"]] %>% nrow
            upd.samples<-values[["samples"]]
            if (nrow(upd.samples) > 0){rownames(upd.samples)<-(nsamples+1):(nsamples+nrow(upd.samples)) %>% as.character}
            
            if (nrow(upd.samples) > 0){
                fechas<-colnames(upd.samples)[sqlFetch(dta, "SAMPLES") %>% sapply(lubridate::is.POSIXct)]
                for (i in fechas){
                    upd.samples[,i]<-lubridate::parse_date_time(upd.samples[,i], c("d/m/Y","d/m/y","Y-m-d")) %>% as.Date()
                }
                varTypes<-rep("Date",length(fechas))
                names(varTypes)<-fechas
                # upd.samples$TIPO<-as.character(upd.samples$TIPO)
                # upd.samples$OBS<-as.character(upd.samples$OBS)
                ### !! Atención, esto cambia la base de datos:
                sqlSave(dta, upd.samples, tablename="SAMPLES", append = T, varTypes = varTypes, rownames = F)
                print("Tabla SAMPLES sincronizada.")
            }
            
            ## Entradas modificadas en CLINICOS
            upd.clinics<-values[["CLINICS"]]
            umid.mod<-upd.clinics$OVID[upd.clinics$OVID %in% (sqlFetch(dta, "CLINICS") %>% pull(OVID))]
            rnames<-sqlFetch(dta, "CLINICS") %>% filter(OVID %in% umid.mod) %>% rownames
            clinics.mod<-upd.clinics %>% filter(OVID %in% umid.mod) %>% select(-NHC)
            rownames(clinics.mod)<-rnames
            
            ### !! Atención, esto cambia la base de datos:
            print(clinics.mod)
            fechas<-colnames(clinics.mod)[sqlFetch(dta, "CLINICS") %>% sapply(lubridate::is.POSIXct)]
            for (i in fechas){
                clinics.mod[,i]<-lubridate::parse_date_time(clinics.mod[,i], c("d/m/Y","d/m/y","Y-m-d")) %>% as.Date()
            }
            varTypes<-rep("Date",length(fechas))
            names(varTypes)<-fechas
            print(clinics.mod)
            sqlUpdate(dta, clinics.mod,"CLINICS", index="OVID")
            print("Tabla CLINICS modificada.")
            
            ## Nuevas entradas en CLINICOS
            nsamples.clin<-sqlFetch(dta, "CLINICS") %>% nrow
            umid.new<-upd.clinics$OVID[!upd.clinics$OVID %in% (sqlFetch(dta, "CLINICS") %>% pull(OVID))]
            clinics.new<-upd.clinics %>% filter(OVID %in% umid.new) %>% select(-NHC)
            if (length(umid.new) > 0){rownames(clinics.new)<-(nsamples.clin+1):(nsamples.clin+nrow(clinics.new)) %>% as.character}
            
            ### !! Atención, esto cambia la base de datos:
            fechas<-colnames(clinics.new)[sqlFetch(dta, "CLINICS") %>% sapply(lubridate::is.POSIXct)]
            for (i in fechas){
                clinics.new[,i]<-lubridate::parse_date_time(clinics.new[,i], c("d/m/Y","d/m/y","Y-m-d")) %>% as.Date()
            }
            varTypes<-rep("Date",length(fechas))
            names(varTypes)<-fechas
            print(varTypes)
            print(clinics.new)
            sqlSave(dta, clinics.new, tablename="CLINICS", append = T, varTypes = varTypes, rownames = F)
            print("Tabla CLINICS sincronizada.")
        }
        if (input$dbtype %in% c("CC")){
            ## Nuevas entradas en MUESTRAS
            nsamples<-values[["samples"]] %>% nrow
            upd.samples<-values[["samples"]]
            if (nrow(upd.samples) > 0){rownames(upd.samples)<-(nsamples+1):(nsamples+nrow(upd.samples)) %>% as.character}
            
            if (nrow(upd.samples) > 0){
                upd.samples$FECHA_RECEPCION<-lubridate::parse_date_time(upd.samples$FECHA_RECEPCION, c("d/m/Y","d/m/y")) %>% as.Date()
                upd.samples$TIPO<-as.character(upd.samples$TIPO)
                upd.samples$OBS<-as.character(upd.samples$OBS)
                ### !! Atención, esto cambia la base de datos:
                sqlSave(dta, upd.samples, tablename="MUESTRAS", append = T, varTypes = c("FECHA_RECEPCION"="Date"), rownames = F)
                print("Tabla MUESTRAS sincronizada.")
            }
            
            ## Entradas modificadas en CLINICOS
            upd.clinics<-values[["CLINICS"]]
            PATID.mod<-upd.clinics$PATID[upd.clinics$PATID %in% (sqlFetch(dta, "CLINICOS") %>% pull(PATID))]
            rnames<-sqlFetch(dta, "CLINICOS") %>% filter(PATID %in% PATID.mod) %>% rownames
            clinics.mod<-upd.clinics %>% filter(PATID %in% PATID.mod) %>% select(-NHC)
            rownames(clinics.mod)<-rnames
            
            ### !! Atención, esto cambia la base de datos:
            fechas<-colnames(clinics.mod)[grepl("date|MET_DX|DoB", colnames(clinics.mod), ignore.case = T)]
            for (i in fechas){
                clinics.mod[,i]<-lubridate::parse_date_time(clinics.mod[,i], c("d/m/Y","d/m/y")) %>% as.Date()
            }
            sqlUpdate(dta, clinics.mod,"CLINICOS", index="PATID")
            print("Tabla CLINICOS modificada.")
            
            ## Nuevas entradas en CLINICOS
            nsamples.clin<-sqlFetch(dta, "CLINICOS") %>% nrow
            PATID.new<-upd.clinics$PATID[!upd.clinics$PATID %in% (sqlFetch(dta, "CLINICOS") %>% pull(PATID))]
            clinics.new<-upd.clinics %>% filter(PATID %in% PATID.new) %>% select(-NHC)
            if (length(PATID.new) > 0){rownames(clinics.new)<-(nsamples.clin+1):(nsamples.clin+nrow(clinics.new)) %>% as.character}
            
            ### !! Atención, esto cambia la base de datos:
            fechas<-colnames(clinics.new)[grepl("date|MET_DX|DoB", colnames(clinics.new), ignore.case = T)]
            varTypes<-rep("Date",length(fechas))
            names(varTypes)<-fechas
            for (i in fechas){
                clinics.new[,i]<-lubridate::parse_date_time(clinics.new[,i], c("d/m/Y","d/m/y","Y-m-d")) %>% as.Date()
            }
            sqlSave(dta, clinics.new, tablename="CLINICOS", append = T, varTypes = varTypes, rownames = F)
            print("Tabla CLINICOS sincronizada.")
            
            ## Nuevas entradas en CNAG
            if (nrow(values[["cnag"]]) > 0){
                cnag.sync<-values[["cnag"]]
                fechas<-colnames(cnag.sync)[sqlFetch(dta, "CNAG") %>% sapply(lubridate::is.POSIXct)]
                varTypes<-rep("Date",length(fechas))
                names(varTypes)<-fechas
                print(fechas)
                for (i in fechas){
                    cnag.sync[,i]<-lubridate::parse_date_time(cnag.sync[,i], c("d/m/Y","d/m/y","Y-m-d")) %>% as.Date()
                }
                sqlSave(dta, cnag.sync, tablename="CNAG", append = T, varTypes = varTypes, rownames = F)
            }
            
            ## Nuevas entradas en RNADNA
            if (nrow(values[["rna"]]) > 0){
                rna.sync<-values[["rna"]]
                fechas<-colnames(rna.sync)[sqlFetch(dta, "RNADNA") %>% sapply(lubridate::is.POSIXct)]
                varTypes<-rep("Date",length(fechas))
                names(varTypes)<-fechas
                for (i in fechas){
                    rna.sync[,i]<-lubridate::parse_date_time(rna.sync[,i], c("d/m/Y","d/m/y","Y-m-d")) %>% as.Date()
                }
                sqlSave(dta, rna.sync, tablename="RNADNA", append = T, varTypes = varTypes, rownames = F)
            }
        }
    })
    

## Visor ----

    output$report<-renderUI({
        samples<-sqlFetch(dta, "samples")
        if (input$nhc == 1){samples_sel<-samples %>% filter(OVID == input$id)}
        if (input$nhc == 2){samples_sel<-samples %>% filter(OVID == input$id)}
        if (input$nhc == 3){samples_sel<-samples %>% filter(samples == input$id)}
        
        print(input$id)
        print(samples_sel)
        
        if (input$nhc == 3){
            HTML(paste0(
            "
            <style>
            table {
              font-family: Arial, Helvetica, sans-serif;
              border-collapse: collapse;
              width: 100%;
            }
            
            table td, table th {
              border: 1px solid #ddd;
              padding: 8px;
            }
            
            table tr:nth-child(even){background-color: #f2f2f2;}
            
            table tr:hover {background-color: #ddd;}
            
            table th {
              padding-top: 12px;
              padding-bottom: 12px;
              text-align: left;
              background-color: #04AA6D;
              color: white;
            }
            </style>
            ",
            "<h3>Muestra: ",input$id,"</h3>",
            "<b>OVID</b>: ",samples_sel$OVID,"<br>",
            "<b>Fecha</b>: ",samples_sel$IQ_date,"<br>",
            "<b>Tipo de tejido: </b>",samples_sel$Tissue,"<br><br>",
            "<b>AP: </b>",samples_sel$AP,"<br><br>",
            "<b>Comments:</b>","<br>   ",samples_sel$Coments,"<br><br>",
            
            "<table style='width:auto;'>
                <tg>
                    <th><b>Hist</b></th>
                    <th><b>RNA</b></th>
                    <th><b>Slide</b></th>
                    <th><b>Frag</b></th>
                    <th><b>Disg</b></th>
                </tr>
                <tr>
                    <td>",samples_sel$Hist_dic,"</td>
                    <td>",samples_sel$RNA_dic,"</td>
                    <td>",samples_sel$Slide_dic,"</td>
                    <td>",samples_sel$Frag_vial,"</td>
                    <td>",samples_sel$Disg_vial,"</td>
            "
            ))
        }
        #**AP**: `r samples_sel$AP`
        
        #**Macro**:
         #   `r samples_sel$Macro`
        
        #**Despcripción**:
        #    `r samples_sel$Description`
        
        #**Procesado**:
        #    `r samples_sel$Process`
    })
    
    output$nitrogen<-renderTable({
        nitro<-sqlFetch(dta, "NITROGEN")
        if (input$nhc == 3){nitro<-nitro %>% filter(CODIGO == input$id)}
        else{nitro<-as.data.frame(matrix(ncol=0, nrow=0))}
        nitro
    })
    
    observeEvent(input$nitrosync, {
        
        if (input$dbtype == "UM"){
            ## Copia de backup
            
            if (!dir.exists(NitroRoute)){
                dir.create(NitroRoute)
                print(paste0("Back Up directory ", NitroRoute, " created"))
            }
            
            write.xlsx(
                sqlFetch(dta, "NITROGEN"),
                file=paste0(NitroRoute, format(Sys.time(), format="%Y%m%d"),"-","UM-Nitrogen.xlsx")
            )
            
            table<-read.xlsx(paste0(gsub("/BU_NITRO/", "", NitroRoute),"/Nitrogen_ICO.xlsx"))
            
            table.um<-table %>% filter( grepl("UM|MU", Nombre) | grepl("Met|Prim|hep|Enn",Nombre, ignore.case = T) |
                                            Nombre == "TILs f. 21/09/20" | Nombre == "TILS DISG f. 03/07/20")
            
            table.um<-add_column(table.um,.before=1, "CODIGO"=str_extract(table.um$Nombre, "UM[0-9]{4}"))
            
            table.samp<-sqlQuery(dta, "SELECT U.NHC,M.* FROM MUESTRAS M INNER JOIN UMID U ON M.UMID=U.UMID")
            table.samp$FECHA_RECEPCION<-table.samp$FECHA_RECEPCION+24*60*60
            
            
            table.um<-add_column(table.um, .after=1,
                                 "FECHA"=str_extract(table.um$Nombre, "[0-9]{2}[\\./][0-9]{2}[\\./][0-9]{2}") %>% gsub("\\.","/",.))
            table.um$FECHA<-as.POSIXct(table.um$FECHA, format="%d/%m/%y")
            
            table.um<-merge(table.um, table.samp %>% select(CODIGO,FECHA_RECEPCION), by.x="FECHA", by.y="FECHA_RECEPCION", all.x=T)
            table.um<-table.um %>% mutate(CODIGO=case_when(is.na(CODIGO.x)~CODIGO.y, TRUE~CODIGO.x), .before=1) %>% select(-CODIGO.x,-CODIGO.y)
            
            table.um[table.um$Nombre == "MU Met f. 10/02/20","CODIGO"]<-"UM0009"
            table.um[table.um$Nombre == "TILs Diss Met","CODIGO"]<-"UM0020"
            table.um[table.um$Nombre == "UM Met","CODIGO"]<-"UM0020"
            table.um[table.um$Nombre == "UM MET NHC 11489341","CODIGO"]<-"UM0044"
            table.um[table.um$Nombre == "UM Primary 20278822","CODIGO"]<-"UM0029"
            table.um[table.um$Nombre == "Hip Nod Hep NHC11489341","CODIGO"]<-"UM0044"
            
            ## Actualización
            
            sqlDrop(dta, "NITROGEN")
            sqlSave(dta, table.um %>% select(-FECHA) %>% filter(!is.na(CODIGO)), tablename="NITROGEN", rownames=F)
        }
        if (input$dbtype == "OV"){
            ## Copia de backup

            if (!dir.exists(NitroRoute)){
                dir.create(NitroRoute)
                print(paste0("Back Up directory ", NitroRoute, " created"))
            }
            
            write.xlsx(
                sqlFetch(dta, "NITROGEN"),
                file=paste0(NitroRoute, format(Sys.time(), format="%Y%m%d"),"-","OV-Nitrogen.xlsx")
            )
            
            ## Lectura del excel
            table<-read.xlsx(paste0(gsub("/BU_NITRO/", "", NitroRoute),"/Nitrogen_ICO.xlsx"))
            
            table.ov<-table %>% filter(grepl("OV",Nombre))
            table.ov<-filter(table.ov, !grepl("OVA",Nombre))
            
            table.ov<-add_column(table.ov,.before=1, "CODIGO"=str_extract(table.ov$Nombre, "OV[0-9]{4}"))
            table.ov[table.ov$Nombre == "Ascitis OV","CODIGO"]<-"OV2105"
            
            table.ov<-table.ov %>% add_column(SampType=NA, .after=1)
            table.ov[grepl("TIL",table.ov$Nombre, ignore.case = T),"SampType"]<-"TILs"
            table.ov[grepl("frag",table.ov$Nombre, ignore.case = T)|grepl("frag",table.ov$Observaciones, ignore.case = T),"SampType"]<-"FRAG"
            table.ov[grepl("slide",table.ov$Nombre, ignore.case = T)|grepl("slide",table.ov$Observaciones, ignore.case = T),"SampType"]<-"SLIDE"
            table.ov[(is.na(table.ov$SampType) | !(table.ov$SampType == "TILs")) & 
                         (grepl("disg|diss",table.ov$Nombre, ignore.case = T)|
                              grepl("disg|diss",table.ov$Observaciones, ignore.case = T)),"SampType"]<-"DISG"
            table.ov[table.ov$Nombre == "Ascitis OV", "SampType"]<-"ASC"
            table.ov[20:25,"SampType"]<-"DISG"
            table.ov[63:68,"SampType"]<-"DISG"
            
            ## Actualización
            
            sqlDrop(dta, "NITROGEN")
            sqlSave(dta, table.ov, tablename="NITROGEN", rownames=F)
        }

    })
    
    output$visorplot<-renderPlot({
        if (input$nhc == 3){
            
            data<-sqlFetch(dta, "IC") %>% filter(samples == input$id)
            data1<-data %>% gather(phen, value, -samples, -Population)
            
            data1$phen<-gsub("p","+",data1$phen)
            data1$phen<-gsub("n","-",data1$phen)
            data1$phen<-gsub("_"," ",data1$phen)
            
            data1$phen<-gsub("n","-",data1$phen, fixed = T)
            data1$phen<-gsub("p","+",data1$phen, fixed = T)
            data1$phen<-gsub("_"," ",data1$phen)
            data1[data1$value < 0.5, "phen"]<-"Other"
            data1$phen<-gsub("[A-Z]*-*[0-9T]- *", "", data1$phen)
            data1$phen<-gsub("+ $", "", data1$phen)
            data1$phen[data1$phen == ""]<-"All Negative"
            
            # data1<-data1 %>% filter(value > 0.5)
            
            data1["phen1"]<-"PD1"
            data1[!grepl("PD1+", data1$phen),"phen1"]<-NA
            
            data1["phen2"]<-"TIM3"
            data1[!grepl("TIM3+", data1$phen),"phen2"]<-NA
            
            data1["phen3"]<-"CTLA4"
            data1[!grepl("CTLA4+", data1$phen),"phen3"]<-NA
            
            data1["phen4"]<-"TIGIT"
            data1[!grepl("TIGIT+", data1$phen),"phen4"]<-NA
            
            data1["phen5"]<-"LAG3"
            data1[!grepl("LAG3+", data1$phen),"phen5"]<-NA
            
            data1<-data1 %>% arrange(desc(value))
            data2<-data1 %>% filter(!phen %in% c("All Negative","Other"))
            data1<-rbind(data2, data1 %>% filter(phen %in% c("All Negative","Other")) %>% arrange(desc(phen)))
            
            data_cd8<-data1 %>% filter(Population == "CD8")
            data_cd4<-data1 %>% filter(Population == "CD4")
            
            data_cd8$ymax<-cumsum(data_cd8$value)
            data_cd8$ymin<-c(0, head(data_cd8$ymax, n=-1))
            
            data_cd4$ymax<-cumsum(data_cd4$value)
            data_cd4$ymin<-c(0, head(data_cd4$ymax, n=-1))
            
            data1<-rbind(data_cd8, data_cd4)
            
            
            color<-c(c("CTLA4+ LAG3+ PD1+ TIGIT+ TIM3+"="black","All Negative"="grey90","Other"="grey50", "PD1+"="#C07AFF", "CTLA4+"="#3EB3DE","TIM3+"="#5EF551","LAG3+"="#DEBB3E","TIGIT+"="#FA7055"),
                     c("CTLA4+ PD1+"="#6666FF","PD1+ TIM3+"="#849CA8", "LAG3+ PD1+"="#C47F9F","PD1+ TIGIT+"="#D259AA", "CTLA4+ TIM3+"="#4ED498", "CTLA4+ LAG3+"="#8EB78E", "CTLA4+ TIGIT+"="#9C929A", "LAG3+ TIM3+"="#9ED848", "TIGIT+ TIM3+"="#ACB353", "LAG3+ TIGIT+"="#EC964A"),
                     c("CTLA4+ PD1+ TIGIT+"="#B86B6A","CTLA4+ PD1+ TIGIT+ TIM3+"="#B81515","LAG3+ PD1+ TIGIT+"="#007D8A", "PD1+ TIGIT+ TIM3+"="#D64545", "LAG3+ PD1+ TIGIT+ TIM3+"="#0f5860", "LAG3+ TIGIT+ TIM3+"="#50cad3"))
            basic.color<-color[c("PD1+","TIGIT+","TIM3+","CTLA4+","LAG3+")]
            names(basic.color)<-c("PD1","TIGIT","TIM3","CTLA4","LAG3")
            # Make the plot
            g1<-ggplot(data1)+
                facet_wrap(.~Population)+
                geom_rect(aes(ymax=ymax, ymin=ymin, xmax=4.5, xmin=0), fill=color[data1$phen])+
                geom_rect(aes(ymax=ymax, ymin=ymin, xmax=5.4, xmin=5, fill=factor(phen1, levels=c("PD1","TIGIT","TIM3","CTLA4","LAG3"))))+
                geom_rect(aes(ymax=ymax, ymin=ymin, xmax=5.9, xmin=5.5, fill=factor(phen4, levels=c("PD1","TIGIT","TIM3","CTLA4","LAG3"))))+
                geom_rect(aes(ymax=ymax, ymin=ymin, xmax=6.4, xmin=6, fill=factor(phen2, levels=c("PD1","TIGIT","TIM3","CTLA4","LAG3"))))+
                geom_rect(aes(ymax=ymax, ymin=ymin, xmax=6.9, xmin=6.5, fill=factor(phen3, levels=c("PD1","TIGIT","TIM3","CTLA4","LAG3"))))+
                geom_rect(aes(ymax=ymax, ymin=ymin, xmax=7.4, xmin=7, fill=factor(phen5, levels=c("PD1","TIGIT","TIM3","CTLA4","LAG3"))))+
                scale_fill_manual(values = basic.color, na.value="#FFFFFF00", drop=F, limits=c("PD1","TIGIT","TIM3","CTLA4","LAG3"), name="IC")+
                coord_polar(theta="y") + # Try to remove that to understand how the chart is built initially
                xlim(c(0, 8)) +# Try to remove that to see how to make a pie chart
                theme_classic()+
                theme(strip.background = element_blank(),
                      strip.text = element_text(size=12, face="bold"),
                      axis.line = element_blank(),
                      axis.ticks = element_blank(),
                      plot.margin = margin(-200,0,0,0),
                      axis.text = element_blank())
            
            # df.color<-data.frame("phen"=names(color), "color"=color)
            # df.color<-rbind(
            #     df.color %>% filter(!phen %in% c("All Negative","Other")) %>% arrange(phen),
            #     df.color %>% filter(phen %in% c("All Negative","Other")) %>% arrange(desc(phen))
            # )
            # 
            # g2<-ggplot(df.color, aes(phen, 1))+
            #     geom_tile(fill=df.color$color)+
            #     scale_x_discrete(limits=df.color$phen)+
            #     ggtitle("Phenotype Combination")+
            #     theme(axis.text.x = element_text(angle=90, hjust=1, vjust=0.5),
            #           axis.text.y = element_blank(),
            #           axis.ticks = element_blank(),
            #           axis.title = element_blank(),
            #           panel.background = element_blank())+
            #     coord_equal()
            
            # g_IC<-ggpubr::ggarrange(g1,g2,ncol=1)
            g_IC<-g1
            
            pops<-sqlFetch(dta, "POPULATIONS")

            g_pop<-pops %>% dplyr::filter(samples == input$id) %>% gather(pop,value,-samples) %>%
                mutate(pop=factor(pop, levels=c("CD45pos_Alive","T_cells","CD8","CD4","DN","NK", "B_cells",
                                                "CD45neg_LDneg","EpCAMneg_HLAIneg","EpCAMneg_HLAIpos","EpCAMpos_HLAIpos"))) %>%
                ggplot(aes(pop, value))+
                    geom_bar(stat="identity", color="black", fill="grey70")+
                    labs(title = input$id, y="% parent", x="")+
                    theme_bw()+
                    theme(axis.text.x = element_text(angle=90, hjust=1, vjust=0.5))
            # tl<-sqlFetch(dta, "IC") %>% filter(samples == input$id)
            # 
            # mtl<-melt(tl, variable.name = "Receptors")
            # mtl$Receptors<-as.character(mtl$Receptors) #Para poder depurar bien el texto, lo pasamos a tipo character
            # mtl$Receptors<-gsub("n","-",mtl$Receptors, fixed = T)
            # mtl$Receptors<-gsub("p","+",mtl$Receptors, fixed = T)
            # mtl$Receptors<-gsub("_"," ",mtl$Receptors)
            # mtl[mtl$value < 1, "Receptors"]<-"Other"
            # mtl$Receptors<-gsub("[A-Z]*-*[0-9T]- *", "", mtl$Receptors)
            # mtl$Receptors<-gsub("+ $", "", mtl$Receptors)
            # mtl$Receptors[mtl$Receptors == ""]<-"All Negative"
            # 
            # mtl$Receptors<-factor(mtl$Receptors)
            # mtl$Population<-factor(mtl$Population, levels = c("CD8", "CD4"))
            # 
            # # colorCount<-length(unique(mtl$Receptors))
            # # getPalette = colorRampPalette(RColorBrewer::brewer.pal(12, "Set3"))
            # 
            # color<-c(c("CTLA4+ LAG3+ PD1+ TIGIT+ TIM3+"="black","All Negative"="white","Other"="grey50", "PD1+"="#C07AFF", "CTLA4+"="#3EB3DE","TIM3+"="#5EF551","LAG3+"="#DEBB3E","TIGIT+"="#FA7055"),
            #          c("CTLA4+ PD1+"="#6666FF","PD1+ TIM3+"="#849CA8", "LAG3+ PD1+"="#C47F9F","PD1+ TIGIT+"="#D259AA", "CTLA4+ TIM3+"="#4ED498", "CTLA4+ LAG3+"="#8EB78E", "CTLA4+ TIGIT+"="#9C929A", "LAG3+ TIM3+"="#9ED848", "TIGIT+ TIM3+"="#ACB353", "LAG3+ TIGIT+"="#EC964A"),
            #          c("CTLA4+ PD1+ TIGIT+"="#B86B6A","CTLA4+ PD1+ TIGIT+ TIM3+"="#B81515","LAG3+ PD1+ TIGIT+"="#007D8A", "PD1+ TIGIT+ TIM3+"="#D64545", "LAG3+ PD1+ TIGIT+ TIM3+"="#0f5860", "LAG3+ TIGIT+ TIM3+"="#50cad3"))
            # 
            # g_IC<-ggplot(mtl, aes(samples, value, fill=Receptors))+
            #     geom_bar(stat="summary", fun="sum",color="black")+
            #     labs(x="Patient", y="% CD8+", fill="")+
            #     facet_grid(.~Population)+
            #     scale_fill_manual(values = color[levels(mtl$Receptors)[levels(mtl$Receptors) %in% unique(mtl$Receptors)]])+
            #     theme_bw()+
            #     theme(axis.text.x=element_text(angle=45, hjust=1))
            ggpubr::ggarrange(g_pop, g_IC, heights = c(0.4, 0.6), ncol = 1)
        }
    })
    

## Citometría ----

    observe({
        if(input$goButtonDir > 0){
            cito_dir<<-choose.dir() %>% gsub("\\","/",. ,fixed=T) %>% paste0("/")

            output$session <- renderText(
                    cito_dir
                )
        }
    })

    observeEvent(input$fcsconvert,{
        route<-cito_dir
        
        files<-list.files(route, ".LMD")
        for (lmd in files){
            fcs<-read.FCS(paste0(route,lmd), dataset = 2)
            # fcs@parameters$desc<-c("FS-A","SS-A", paste("FL",1:10,"-A", sep = ""), "TIME")
            # fcs@parameters$desc<-c("FS-H","FS-A","FS-W","SS-H","SS-A","TIME", paste("FL",1:10,"-A", sep = ""))
            keyword(fcs)['$FIL']<-paste0(gsub(".LMD","",lmd), ".fcs")
            write.FCS(fcs, paste0(route, gsub(".LMD","",lmd), ".fcs"))
        }
    })
    
    observeEvent(input$pngexport,{
        if (input$phenotype == "Pop"){
            route<-cito_dir
            
            ws<-open_flowjo_xml(paste0(route,"Populations.wsp"))
            gs<-flowjo_to_gatingset(ws, name="All Samples")
            
            sampleNames(gs)<-sapply(sampleNames(gs), function(x) strsplit(x, "Pop ")[[1]][2]) %>% 
                gsub("[[:space:]][0-9]*.fcs_.[0-9]*","", . , perl = T)
            
            for (samp in sampleNames(gs)){
                print(samp)
                p<-autoplot(gs[[samp]], bins=64)
                ggsave(paste0(route, samp,".pop.png"),p,width = 10, height = 10)
            }
        }
        
        if (input$phenotype == "IC"){
            route<-cito_dir
            
            ws<-open_flowjo_xml(paste0(route,"IC.wsp"))
            gs<-flowjo_to_gatingset(ws, name="All Samples")
            
            sampleNames(gs)<-sapply(sampleNames(gs), function(x) strsplit(x, "ICs ")[[1]][2]) %>% 
                gsub("[[:space:]][0-9]*.fcs_.[0-9]*","", . , perl = T)
            
            bool.comb<-apply(
                expand.grid(c("","!"), c("","!"),c("","!"), c("","!"), c("","!")),
                1,
                function(x) paste0(x[1],"CTLA4 & ",x[2],"LAG3 & ",x[3],"PD1 & ",x[4], "TIGIT & ",x[5], "TIM3")
            )
            
            bool.name<-apply(
                expand.grid(c("+","-"), c("+","-"),c("+","-"), c("+","-"), c("+","-")),
                1,
                function(x) paste0("CTLA4",x[1]," LAG3",x[2]," PD1",x[3]," TIGIT",x[4]," TIM3",x[5])
            )
            
            print("Booleanos CD8")
            for (i in 1:length(bool.comb)){
                call<-substitute(booleanFilter(v), list(v=as.symbol(bool.comb[i])))
                boolgate<-eval(call)
                gs_pop_add(gs, boolgate, parent="CD8", name = bool.name[i])
            }
            
            print("Booleanos CD4")
            for (i in 1:length(bool.comb)){
                call<-substitute(booleanFilter(v), list(v=as.symbol(bool.comb[i])))
                boolgate<-eval(call)
                gs_pop_add(gs, boolgate, parent="CD4", name = bool.name[i])
            }
            
            recompute(gs)
            
            names<-sampleNames(gs) %>% gsub("ab|Ab|AB|iso|Iso|ISO| ","",.) %>% unique()
            
            nodes<-gs_get_pop_paths(gs)
            # nodes<-gsub("â\u0081»", "-", nodes)
            # nodes<-gsub("â\u0081º", "+", nodes)
            nodes<-nodes[grepl("CTLA4", nodes)]
            nodes<-nodes[!grepl("CD4$|CD8$|CTLA4$|TIM3$|PD1$|LAG3$|TIGIT$", nodes)]
            
            pop<-gs_pop_get_stats(gs, nodes=nodes,type="percent") %>% as.data.frame %>% mutate(percent=percent*100)
            pop$percent<-round(pop$percent, digits=2)
            
            # pop$pop<-gsub("â\u0081»", "n", pop$pop)
            # pop$pop<-gsub("â\u0081º", "p", pop$pop)
            pop$pop<-gsub("-", "n", pop$pop, fixed=T)
            pop$pop<-gsub("+", "p", pop$pop, fixed=T)
            pop$pop<-gsub(" ", "_", pop$pop)
            
            pop["Type"]<-"ab"
            pop[grepl("iso|ISO|Iso",pop$sample),"Type"]<-"iso"
            pop$sample<-gsub("iso|ISO|Iso|ab|AB|Ab| ","",pop$sample)
            
            pop_sp<-pop %>% spread(Type, percent)
            pop_sp["Net"]<-pop_sp$ab
            pop_sp[!grepl("CTLA4n_LAG3n_PD1n_TIGITn_TIM3n",pop_sp$pop),"Net"]<-pop_sp[!grepl("CTLA4n_LAG3n_PD1n_TIGITn_TIM3n",pop_sp$pop),"ab"]-pop_sp[!grepl("CTLA4n_LAG3n_PD1n_TIGITn_TIM3n",pop_sp$pop),"iso"]
            pop_sp$Net[pop_sp$Net < 0]<-0
            pop_sp["Population"]<-str_extract(pop_sp$pop, "/CD[4,8]{1}/") %>% gsub("/","",.)
            pop_sp$pop<-sapply(strsplit(pop_sp$pop, "/"), tail, 1)
            
            pop_sp<-pop_sp %>% select(-ab,-iso) %>% spread(pop,Net)
            pop_sp$CTLA4n_LAG3n_PD1n_TIGITn_TIM3n<- pop_sp %>% select(-CTLA4n_LAG3n_PD1n_TIGITn_TIM3n) %>% group_by(sample,Population) %>% 
                gather(pop, value, -sample,-Population) %>% summarise(n=100-sum(value)) %>% pull(n)
            if (input$dbtype == "OV"){
                pop_sp <- rename(pop_sp, "samples"="sample")
            }
            if (input$dbtype %in% c("UM", "CC")){
                pop_sp <- rename(pop_sp, "CODIGO"="sample")
            }
            
            pop_sql<-sqlFetch(dta, "IC") %>% slice(0)
            pop_sp<-pop_sp %>% merge(pop_sql, all=T) %>% select(colnames(pop_sql))
            
            for (id in names){
                print(id)
                iso<-sampleNames(gs)[grepl(id, sampleNames(gs)) & grepl("iso|Iso|ISO",sampleNames(gs))]
                ab<-sampleNames(gs)[grepl(id, sampleNames(gs)) & grepl("ab|Ab|AB",sampleNames(gs))]
                
                if (input$dbtype == "OV"){
                    data<-pop_sp %>% filter(samples == id)
                    data1<-data %>% gather(phen, value, -samples, -Population)
                }
                if (input$dbtype %in% c("UM", "CC")){
                    data<-pop_sp %>% filter(CODIGO == id)
                    data1<-data %>% gather(phen, value, -CODIGO, -Population)
                }
                
                data1$phen<-gsub("p","+",data1$phen)
                data1$phen<-gsub("n","-",data1$phen)
                data1$phen<-gsub("_"," ",data1$phen)
                
                data1$phen<-gsub("n","-",data1$phen, fixed = T)
                data1$phen<-gsub("p","+",data1$phen, fixed = T)
                data1$phen<-gsub("_"," ",data1$phen)
                data1[data1$value < 0.5, "phen"]<-"Other"
                data1$phen<-gsub("[A-Z]*-*[0-9T]- *", "", data1$phen)
                data1$phen<-gsub("+ $", "", data1$phen)
                data1$phen[data1$phen == ""]<-"All Negative"
                
                # data1<-data1 %>% filter(value > 0.5)
                
                data1["phen1"]<-"PD1"
                data1[!grepl("PD1+", data1$phen),"phen1"]<-NA
                
                data1["phen2"]<-"TIM3"
                data1[!grepl("TIM3+", data1$phen),"phen2"]<-NA
                
                data1["phen3"]<-"CTLA4"
                data1[!grepl("CTLA4+", data1$phen),"phen3"]<-NA
                
                data1["phen4"]<-"TIGIT"
                data1[!grepl("TIGIT+", data1$phen),"phen4"]<-NA
                
                data1["phen5"]<-"LAG3"
                data1[!grepl("LAG3+", data1$phen),"phen5"]<-NA
                
                data1<-data1 %>% arrange(desc(value))
                data2<-data1 %>% filter(!phen %in% c("All Negative","Other"))
                data1<-rbind(data2, data1 %>% filter(phen %in% c("All Negative","Other")) %>% arrange(desc(phen)))
                
                data_cd8<-data1 %>% filter(Population == "CD8")
                data_cd4<-data1 %>% filter(Population == "CD4")
                
                data_cd8$ymax<-cumsum(data_cd8$value)
                data_cd8$ymin<-c(0, head(data_cd8$ymax, n=-1))
                
                data_cd4$ymax<-cumsum(data_cd4$value)
                data_cd4$ymin<-c(0, head(data_cd4$ymax, n=-1))
                
                data1<-rbind(data_cd8, data_cd4)
                
                
                color<-c(c("CTLA4+ LAG3+ PD1+ TIGIT+ TIM3+"="black","All Negative"="grey90","Other"="grey50", "PD1+"="#C07AFF", "CTLA4+"="#3EB3DE","TIM3+"="#5EF551","LAG3+"="#DEBB3E","TIGIT+"="#FA7055"),
                         c("CTLA4+ PD1+"="#6666FF","PD1+ TIM3+"="#849CA8", "LAG3+ PD1+"="#C47F9F","PD1+ TIGIT+"="#D259AA", "CTLA4+ TIM3+"="#4ED498", "CTLA4+ LAG3+"="#8EB78E", "CTLA4+ TIGIT+"="#9C929A", "LAG3+ TIM3+"="#9ED848", "TIGIT+ TIM3+"="#ACB353", "LAG3+ TIGIT+"="#EC964A"),
                         c("CTLA4+ PD1+ TIGIT+"="#B86B6A","CTLA4+ PD1+ TIGIT+ TIM3+"="#B81515","LAG3+ PD1+ TIGIT+"="#007D8A", "PD1+ TIGIT+ TIM3+"="#D64545", "LAG3+ PD1+ TIGIT+ TIM3+"="#0f5860", "LAG3+ TIGIT+ TIM3+"="#50cad3"))
                basic.color<-color[c("PD1+","TIGIT+","TIM3+","CTLA4+","LAG3+")]
                names(basic.color)<-c("PD1","TIGIT","TIM3","CTLA4","LAG3")
                # Make the plot
                g_coex<-ggplot(data1)+
                    facet_grid(factor(Population, levels=c("CD8","CD4"))~.)+
                    geom_rect(aes(ymax=ymax, ymin=ymin, xmax=4.5, xmin=0), fill=color[data1$phen])+
                    geom_rect(aes(ymax=ymax, ymin=ymin, xmax=5.4, xmin=5, fill=factor(phen1, levels=c("PD1","TIGIT","TIM3","CTLA4","LAG3"))))+
                    geom_rect(aes(ymax=ymax, ymin=ymin, xmax=5.9, xmin=5.5, fill=factor(phen4, levels=c("PD1","TIGIT","TIM3","CTLA4","LAG3"))))+
                    geom_rect(aes(ymax=ymax, ymin=ymin, xmax=6.4, xmin=6, fill=factor(phen2, levels=c("PD1","TIGIT","TIM3","CTLA4","LAG3"))))+
                    geom_rect(aes(ymax=ymax, ymin=ymin, xmax=6.9, xmin=6.5, fill=factor(phen3, levels=c("PD1","TIGIT","TIM3","CTLA4","LAG3"))))+
                    geom_rect(aes(ymax=ymax, ymin=ymin, xmax=7.4, xmin=7, fill=factor(phen5, levels=c("PD1","TIGIT","TIM3","CTLA4","LAG3"))))+
                    scale_fill_manual(values = basic.color, na.value="#FFFFFF00", drop=F, limits=c("PD1","TIGIT","TIM3","CTLA4","LAG3"), name="IC")+
                    coord_polar(theta="y") + # Try to remove that to understand how the chart is built initially
                    xlim(c(0, 8)) +# Try to remove that to see how to make a pie chart
                    theme_classic()+
                    theme(strip.background = element_blank(),
                          strip.text = element_text(size=12, face="bold"),
                          axis.line = element_blank(),
                          axis.ticks = element_blank(),
                          # plot.margin = margin(-200,0,0,0),
                          axis.text = element_blank())
                
                nodes<-gs_get_pop_paths(gs)
                nodes_parent<-nodes[!grepl("CTLA4|LAG3|PD1|TIGIT|TIM3|root$", nodes)]
                nodes_cd4<-nodes[grepl("CTLA4$|LAG3$|PD1$|TIGIT$|TIM3$", nodes) & grepl("/CD4/",nodes)]
                nodes_cd8<-nodes[grepl("CTLA4$|LAG3$|PD1$|TIGIT$|TIM3$", nodes) & grepl("/CD8/",nodes)]
                
                # g1<-ggcyto_arrange(autoplot(gs[[ab]], nodes_parent, bins=128), nrow=1)
                # g2<-ggcyto_arrange(autoplot(gs[[iso]], nodes_cd8, bins=64), nrow=1)
                # g3<-ggcyto_arrange(autoplot(gs[[ab]], nodes_cd8, bins=64), nrow=1)
                # g4<-ggcyto_arrange(autoplot(gs[[iso]], nodes_cd4, bins=64), nrow=1)
                # g5<-ggcyto_arrange(autoplot(gs[[ab]], nodes_cd4, bins=64), nrow=1)
                g1<-ggcyto_arrange(autoplot(gs[[ab]], nodes_parent), nrow=1)
                g2<-ggcyto_arrange(autoplot(gs[[iso]], nodes_cd8), nrow=1)
                g3<-ggcyto_arrange(autoplot(gs[[ab]], nodes_cd8), nrow=1)
                g4<-ggcyto_arrange(autoplot(gs[[iso]], nodes_cd4), nrow=1)
                g5<-ggcyto_arrange(autoplot(gs[[ab]], nodes_cd4), nrow=1)
                g_dots<-gridExtra::gtable_rbind(g1,g2,g3,g4,g5)
                
                g_all<-ggpubr::ggarrange(g_dots, g_coex, nrow=1, widths=c(0.65,0.35))
                ggsave(paste0(route,id,".IC.png"), g_all, width = 14, height = 10)
            }
        }
    })
        
    observeEvent(input$popexport,{
        if (input$phenotype == "Pop"){
            route<-cito_dir
            
            ws<-open_flowjo_xml(paste0(route,"Populations.wsp"))
            gs<-flowjo_to_gatingset(ws, name="All Samples")
            
            sampleNames(gs)<-sapply(sampleNames(gs), function(x) strsplit(x, "Pop ")[[1]][2]) %>% 
                gsub("[[:space:]][0-9]*.fcs_.[0-9]*","", . , perl = T)
            
            nodes<-sapply(strsplit(gs_get_pop_paths(gs), "/"), tail, 1)
            nodes<-nodes[grepl("_",nodes)]
            pop<-gs_pop_get_stats(gs, nodes=nodes,type="percent") %>% as.data.frame %>% mutate(percent=percent*100)
            
            pop[,"pop"]<-gsub("_","",pop$pop)
            pop$pop<-gsub(" ","_",pop$pop)
            pop$pop<-gsub("+","pos",pop$pop, fixed=T)
            pop$pop<-gsub("-","neg",pop$pop, fixed=T)
            pop<-rename(pop, "samples"="sample")
            pop$percent<-round(pop$percent, digits=2)
            pop_sp<-pop %>% spread(pop, percent)
            
            pop_sql<-sqlFetch(dta, "POPULATIONS") %>% slice(0)
            pop_sp<-pop_sp %>% merge(pop_sql, all=T) %>% select(colnames(pop_sql))
            
            vartypes<-rep("Number", pop_sp %>% select(-samples) %>% colnames %>% length)
            names(vartypes)<-pop_sp %>% select(-samples) %>% colnames
            
            sqlSave(dta, pop_sp, tablename="POPULATIONS", append = T, varTypes = vartypes, rownames = F)
            print("Tabla POPULATIONS sincronizada.")
        }
        if (input$phenotype == "IC"){
            route<-cito_dir
            
            ws<-open_flowjo_xml(paste0(route,"IC.wsp"))
            gs<-flowjo_to_gatingset(ws, name="All Samples")
            
            sampleNames(gs)<-sapply(sampleNames(gs), function(x) strsplit(x, "ICs ")[[1]][2]) %>% 
                gsub("[[:space:]][0-9]*.fcs_.[0-9]*","", . , perl = T)
            
            bool.comb<-apply(
                expand.grid(c("","!"), c("","!"),c("","!"), c("","!"), c("","!")),
                1,
                function(x) paste0(x[1],"CTLA4 & ",x[2],"LAG3 & ",x[3],"PD1 & ",x[4], "TIGIT & ",x[5], "TIM3")
            )
            
            bool.name<-apply(
                expand.grid(c("+","-"), c("+","-"),c("+","-"), c("+","-"), c("+","-")),
                1,
                function(x) paste0("CTLA4",x[1]," LAG3",x[2]," PD1",x[3]," TIGIT",x[4]," TIM3",x[5])
            )
            
            for (i in 1:length(bool.comb)){
                print("Booleanos CD8")
                call<-substitute(booleanFilter(v), list(v=as.symbol(bool.comb[i])))
                boolgate<-eval(call)
                gs_pop_add(gs, boolgate, parent="CD8", name = bool.name[i])
            }
            
            for (i in 1:length(bool.comb)){
                print("Booleanos CD4")
                call<-substitute(booleanFilter(v), list(v=as.symbol(bool.comb[i])))
                boolgate<-eval(call)
                gs_pop_add(gs, boolgate, parent="CD4", name = bool.name[i])
            }
            
            recompute(gs)
            
            nodes<-gs_get_pop_paths(gs)
            # nodes<-gsub("â\u0081»", "-", nodes)
            # nodes<-gsub("â\u0081º", "+", nodes)
            nodes<-nodes[grepl("CTLA4", nodes)]
            nodes<-nodes[!grepl("CD4$|CD8$|CTLA4$|TIM3$|PD1$|LAG3$|TIGIT$", nodes)]
            
            pop<-gs_pop_get_stats(gs, nodes=nodes,type="percent") %>% as.data.frame %>% mutate(percent=percent*100)
            pop$percent<-round(pop$percent, digits=2)
            
            # pop$pop<-gsub("â\u0081»", "n", pop$pop)
            # pop$pop<-gsub("â\u0081º", "p", pop$pop)
            pop$pop<-gsub("-", "n", pop$pop, fixed=T)
            pop$pop<-gsub("+", "p", pop$pop, fixed=T)
            pop$pop<-gsub(" ", "_", pop$pop)
            
            pop["Type"]<-"ab"
            pop[grepl("iso|ISO|Iso",pop$sample),"Type"]<-"iso"
            pop$sample<-gsub("iso|ISO|Iso|ab|AB|Ab| ","",pop$sample)
            
            pop_sp<-pop %>% spread(Type, percent)
            pop_sp["Net"]<-pop_sp$ab
            pop_sp[!grepl("CTLA4n_LAG3n_PD1n_TIGITn_TIM3n",pop_sp$pop),"Net"]<-pop_sp[!grepl("CTLA4n_LAG3n_PD1n_TIGITn_TIM3n",pop_sp$pop),"ab"]-pop_sp[!grepl("CTLA4n_LAG3n_PD1n_TIGITn_TIM3n",pop_sp$pop),"iso"]
            pop_sp$Net[pop_sp$Net < 0]<-0
            pop_sp["Population"]<-str_extract(pop_sp$pop, "/CD[4,8]{1}/") %>% gsub("/","",.)
            pop_sp$pop<-sapply(strsplit(pop_sp$pop, "/"), tail, 1)
            
            pop_sp<-pop_sp %>% select(-ab,-iso) %>% spread(pop,Net)
            pop_sp$CTLA4n_LAG3n_PD1n_TIGITn_TIM3n<- pop_sp %>% select(-CTLA4n_LAG3n_PD1n_TIGITn_TIM3n) %>% group_by(sample,Population) %>% 
                gather(pop, value, -sample,-Population) %>% summarise(n=100-sum(value)) %>% pull(n)
            if (input$dbtype == "OV"){
                pop_sp <- rename(pop_sp, "samples"="sample")
            }
            if (input$dbtype %in% c("UM", "CC")){
                pop_sp <- rename(pop_sp, "CODIGO"="sample")
            }
            
            pop_sql<-sqlFetch(dta, "IC") %>% slice(0)
            pop_sp<-pop_sp %>% merge(pop_sql, all=T) %>% select(colnames(pop_sql))
            
            if (input$dbtype == "OV"){
                vartypes<-rep("Number", pop_sp %>% select(-samples, -Population) %>% colnames %>% length)
                names(vartypes)<-pop_sp %>% select(-samples, -Population) %>% colnames
            }
            if (input$dbtype %in% c("UM", "CC")){
                vartypes<-rep("Number", pop_sp %>% select(-CODIGO, -Population) %>% colnames %>% length)
                names(vartypes)<-pop_sp %>% select(-CODIGO, -Population) %>% colnames
            }
            

            
            sqlSave(dta, pop_sp, tablename="IC", append = T, varTypes = vartypes, rownames = F)
            print("Tabla IC sincronizada.")
        }
    }) 


## scRNAseq ----

    output$PATID = renderUI({
        observeEvent(input$goButton, {})
        sc_cod<-sqlFetch(dta, "CNAG") %>% pull(CODIGO)
        selectizeInput("sc_cod", "CÓDIGO", sc_cod, multiple = T)
    })
    
    output$sc_table<-renderTable({
        if (input$sct_sel){
            if (input$sqlquery != ""){
                print(input$sqlquery)
                sqlQuery(dta, input$sqlquery)
            }else{
                if (!is.null(input$sc_cod)){
                    sqlFetch(dta, "CNAG") %>% filter(CODIGO %in% input$sc_cod)
                }else{
                    sqlFetch(dta, "CNAG")
                }
            }
        }else{
            sqlFetch(dta, "CNAG")
        }

    })
    
    output$sc_plot <-renderPlot({
        meta<<-readRDS(paste0(scRNAseqRoute,"metadata_full_object.rds"))
        
        if (input$sqlquery != ""){
            sc_codigos<-sqlQuery(dta, input$sqlquery) %>% pull(CNAG_NAME)
        }else{
            if (!is.null(input$sc_cod)){
                sc_codigos<-sqlFetch(dta, "CNAG") %>% filter(CODIGO %in% input$sc_cod) %>% pull(CNAG_NAME)
            }else{
                sc_codigos<-sqlFetch(dta, "CNAG") %>% pull(CNAG_NAME)
            }
        }
        sc_codigos<-gsub(" _","_", sc_codigos )
        sc_codigos<-gsub("_ ","_", sc_codigos )
        sc_codigos<-gsub(" ","_", sc_codigos )
        
        meta<-meta %>% mutate(sample2=gsub("_CD45", "", sample)) %>% filter(sample2 %in% sc_codigos)
        if (isFALSE(input$cd45_chk)){ meta<-meta %>% filter(!grepl("_CD45", sample))}
        
        g1<-ggplot(meta, aes(coord_x, coord_y, color=predicted.id))+
            geom_point(size=0.2)+
            guides(colour = guide_legend(override.aes = list(size=2)))+
            theme_bw()+
            theme(aspect.ratio = 1)
        
        meta_perc<-meta %>% group_by(sample, predicted.id) %>% summarise(N=n()) %>% mutate(N=perc(N)) %>% 
            spread(predicted.id, N) %>% gather("predicted.id","N",-sample) %>% mutate(N=case_when(is.na(N)~0,TRUE~N))
        g2<-ggheatmap(meta_perc, "sample","predicted.id", "N", color = "grey50")
        ggpubr::ggarrange(g1,g2, ncol=1, heights = c(0.3, 0.7))
    })

    output$sc_expr <-renderPlot({
        if (input$genes != ""){
            expr<-readRDS(paste0(scRNAseqRoute,"expression_full_object.rds"))
            genes<-strsplit(input$genes, ",")[[1]]

            if (length(genes) > 1){
                df.expr<-as.data.frame(as.matrix(expr[genes,]))
                df.expr["Gene"]<-rownames(df.expr)
                mdf.expr<-melt(df.expr)
            }else{
                df.expr<-as.data.frame(t(as.matrix(expr[genes[1],])))
                df.expr["Gene"]<-genes[1]
                mdf.expr<-melt(df.expr)
            }
            
            alldata<-merge(meta, mdf.expr, by.x="barcode", by.y = "variable")
            
        }
        
        # order <- clustsort(alldata %>% spread(Gene, value) %>% select(predicted.id, all_of(genes)) %>%  
        #                        group_by(predicted.id) %>% summarise(across(all_of(genes), mean)) %>%  as.data.frame)
        # 
        # g1<-ggplot(alldata, aes(predicted.id, value, fill=predicted.id))+
        #     geom_violin(scale = "width")+
        #     geom_jitter(width=0.2, size=0.1, alpha=0.3)+
        #     scale_x_discrete(limits=order$x)+
        #     guides(fill=F)+
        #     facet_wrap(.~Gene)+
        #     theme_bw()+
        #     theme(axis.text.x = element_text(angle=90, hjust=1, vjust = 0.5))
        g2<-ggheatmap(alldata, x="predicted.id",y="Gene",value="value", color="grey")+coord_equal()
        # ggpubr::ggarrange(g1,g2, ncol=1)
        g2
    })
}

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