CitoProccess/CitoProcess/app.R

library(shiny)
library(openCyto)
library(flowCore)
library(flowWorkspace)
library(CytoML)
library(ggcyto)
library(RColorBrewer)
# library(reshape2)
# library(CitFuns)
library(openxlsx)
library(tidyverse)


# Define UI for application that draws a histogram
ui <- fluidPage(

    # Application title
    titlePanel("Análisis Citometría ImmunoPreserve"),

    # Sidebar with a slider input for number of bins 
    sidebarLayout(
        sidebarPanel(
            selectInput("phenotype", "Panel", selected="Panel1", choices=c("Panel1", "Panel2","Panel3","panel4")),
        ),
        mainPanel(
                 textInput("cytopath", label="Directorio fenotipo", value=""),
                 actionButton("goButtonDir","Selecciona directorio fenotipo"),
                 textOutput("session"),
                 hr(),
                 actionButton("fcsconvert", "Convertir a fcs"),
                 hr(),
                 actionButton("pngexport", "Exportar informes"),
                 hr(),
                 textInput("dbpath", label="Ruta Base de Dades", value=""),
                 actionButton("goButtondbpath","Selecciona Ruta Base de Dades"),
                 textOutput("sessiondbpath"),
                 actionButton("popexport", "Actualizar BBDD")
        )
    )
)

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

    observe({
        if(input$goButtonDir > 0){
            if (input$cytopath == ""){
                cito_dir<<-choose.dir() %>% gsub("\\","/",. ,fixed=T) %>% paste0("/") %>% stringi::stri_enc_tonative()
            }else{
                cito_dir<<-input$cytopath %>% gsub("\\","/",. ,fixed=T) %>% gsub("/$", "", .) %>% paste0("/") %>% stringi::stri_enc_tonative()
            }
            
            output$session <- renderText(
                cito_dir
            )
        }
    })
    
    observe({
        if(input$goButtondbpath > 0){
            if (input$dbpath == ""){
                db_path<<-choose.dir() %>% gsub("\\","/",. ,fixed=T) %>% paste0("/") %>% stringi::stri_enc_tonative()
            }else{
                db_path<<-input$dbpath %>% gsub("\\","/",. ,fixed=T) %>% gsub("/$", "", .) %>% paste0("/") %>% stringi::stri_enc_tonative()
            }
            
            output$sessiondbpath <- renderText(
                db_path
            )
        }
    })
    
    observeEvent(input$fcsconvert,{
        route<-cito_dir
        
        files<-list.files(route, ".LMD")
        for (lmd in files){
            fcs<-read.FCS(paste0(route,lmd), dataset = 2)
            keyword(fcs)['$FIL']<-paste0(gsub(".LMD","",lmd), ".fcs")
            write.FCS(fcs, paste0(route, gsub(".LMD","",lmd), ".fcs"))
        }
        print("Conversión completada")
    })
    
    observeEvent(input$pngexport,{
        
        if (input$phenotype == "Panel1"){
            route<-cito_dir
            
            ws<-open_flowjo_xml(paste0(route,"Panel1.wsp"))
            gs<-flowjo_to_gatingset(ws, name="All Samples")
            
            sampleNames(gs)<-sapply(sampleNames(gs), function(x) strsplit(x, "Panel1 ")[[1]][2]) %>% 
                gsub("[[:space:]][0-9]*.fcs_.[0-9]*","", . , perl = T)
            
            gs<-gs[sampleNames(gs)[!grepl("Iso|ISO|iso",sampleNames(gs))]]
            
            bool.comb<-apply(
                expand.grid(c("","!"), c("","!"), c("","!"), c("","!")),
                1,
                function(x) paste0(x[1],"CTLA4 & ",x[2],"LAG3 & ",x[3],"PD1 & ",x[4], "TIM3")
            )
            
            bool.name<-apply(
                expand.grid(c("+","-"), c("+","-"), c("+","-"), c("+","-")),
                1,
                function(x) paste0("CTLA4",x[1]," LAG3",x[2]," PD1",x[3]," TIM3",x[4])
            )
            
            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$|LAG3$", 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)
            
            ## Esto si no hay isotipo
            
            pop_sp<-pop
            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 %>% spread(pop, percent)
            
            ## Esto si hay Isotipo
            
            # 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<-read.xlsx(paste0(db_path,"Panel1.xlsx"), sheet = "IC")
            pop_sp<-pop_sp %>% merge(pop_sql %>% slice(0), 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))]
                
                data<-pop_sp %>% filter(sample == id)
                data1<-data %>% gather(phen, value, -sample, -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$value < 1, "phen"]<-"Other"
                data1$phen<-gsub("[A-Z]*-*[0-9T]- *", "", data1$phen)
                data1$phen<-gsub("+ $", "", data1$phen)
                data1$phen[data1$phen == ""]<-"All Negative"
                
                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"]<-"LAG3"
                data1[!grepl("LAG3+", data1$phen),"phen4"]<-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+ TIM3+"="black","All Negative"="grey90","Other"="grey50", "PD1+"="#C07AFF", "CTLA4+"="#3EB3DE","TIM3+"="#5EF551","LAG3+"="#DEBB3E"),
                         c("CTLA4+ PD1+"="#6666FF","PD1+ TIM3+"="#849CA8", "LAG3+ PD1+"="#C47F9F", "CTLA4+ TIM3+"="#4ED498", "CTLA4+ LAG3+"="#8EB78E", "LAG3+ TIM3+"="#9ED848"),
                         c("CTLA4+ PD1+ TIM3+"="#B81515", "LAG3+ PD1+ TIM3+"="#0f5860"))
                
                basic.color<-color[c("PD1+","TIM3+","CTLA4+","LAG3+")]
                names(basic.color)<-c("PD1","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","TIM3","CTLA4","LAG3"))))+
                    geom_rect(aes(ymax=ymax, ymin=ymin, xmax=5.9, xmin=5.5, fill=factor(phen2, levels=c("PD1","TIM3","CTLA4","LAG3"))))+
                    geom_rect(aes(ymax=ymax, ymin=ymin, xmax=6.4, xmin=6, fill=factor(phen3, levels=c("PD1","TIM3","CTLA4","LAG3"))))+
                    geom_rect(aes(ymax=ymax, ymin=ymin, xmax=6.9, xmin=6.5, fill=factor(phen4, levels=c("PD1","TIM3","CTLA4","LAG3"))))+
                    scale_fill_manual(values = basic.color, na.value="#FFFFFF00", drop=F, limits=c("PD1","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|TIM3|root$", nodes)]
                nodes_cd4<-nodes[grepl("CTLA4$|LAG3$|PD1$|TIM3$", nodes) & grepl("/_CD4/",nodes)]
                nodes_cd8<-nodes[grepl("CTLA4$|LAG3$|PD1$|TIM3$", nodes) & grepl("/_CD8/",nodes)]
                

                g1<-ggcyto_arrange(autoplot(gs[[id]], nodes_parent), nrow=2)
                g2<-ggcyto_arrange(autoplot(gs[[id]], nodes_cd8), nrow=1)
                g3<-ggcyto_arrange(autoplot(gs[[id]], nodes_cd4), nrow=1)
                
                g_dots<-gridExtra::gtable_rbind(g1,g2,g3)
                
                g_all<-ggpubr::ggarrange(g_dots, g_coex, ncol=1, heights=c(0.75,0.25))
                ggsave(paste0(route,id,".IC.png"), g_all, width = 10, height = 14)
                ggsave(paste0(db_path, "Informes/",id,".IC.png"), g_all, width = 10, height = 14)
            }
            print("Informes finalizados!")
        }
        
        if (input$phenotype == "Panel3"){
            route<-cito_dir
            
            ws<-open_flowjo_xml(paste0(route,"Panel3.wsp"))
            gs<-flowjo_to_gatingset(ws, name="All Samples")
            
            sampleNames(gs)<-sapply(sampleNames(gs), function(x) strsplit(x, "Panel3 ")[[1]][2]) %>% 
                gsub("[[:space:]][0-9]*.fcs_.[0-9]*","", . , perl = T)
            
            gs<-gs[sampleNames(gs)[!grepl("Iso|ISO|iso|NoBV421",sampleNames(gs))]]
            
            bool.comb<-apply(
                expand.grid(c("","!"), c("","!"), c("","!")),
                1,
                function(x) paste0(x[1],"CD38 & ",x[2],"HLADR & ",x[3],"GZMB")
            )
            
            bool.name<-apply(
                expand.grid(c("+","-"), c("+","-"), c("+","-")),
                1,
                function(x) paste0("CD38",x[1]," HLADR",x[2]," GZMB",x[3])
            )
            
            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])
            }
            
            print("Booleanos NK")
            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="NK", 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("CD38", nodes)]
            nodes<-nodes[!grepl("CD38$|HLADR$|GZMB$", 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)
            
            ## Esto si no hay isotipo
            
            pop_sp<-pop
            pop_sp["Population"]<-str_extract(pop_sp$pop, "/CD[4,8]{1}/") %>% gsub("/|_","",.)
            pop_sp$Population[is.na(pop_sp$Population)]<-"NK"
            pop_sp$pop<-sapply(strsplit(pop_sp$pop, "/"), tail, 1)
            pop_sp<-pop_sp %>% spread(pop, percent)
            
            pop_sql<-read.xlsx(paste0(db_path,"Panel3.xlsx"), check.names = F, sep.names = " ")
            pop_sp<-pop_sp %>% merge(pop_sql %>% slice(0), all=T) %>% select(colnames(pop_sql))
            
            for (id in names){
                print(id)

                data<-pop_sp %>% filter(sample == id)
                data1<-data %>% gather(phen, value, -sample, -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$value < 1, "phen"]<-"Other"
                data1$phen<-gsub("[A-Z0-9]*-", "", data1$phen)
                data1$phen<-gsub("  ", " ", data1$phen)
                data1$phen<-gsub("[ ]*$", "", data1$phen)
                data1$phen<-gsub("^[ ]*", "", data1$phen)
                data1$phen[data1$phen == ""]<-"All Negative"
                
                data1["phen1"]<-"CD38"
                data1[!grepl("CD38+", data1$phen),"phen1"]<-NA
                
                data1["phen2"]<-"HLADR"
                data1[!grepl("HLADR+", data1$phen),"phen2"]<-NA
                
                data1["phen3"]<-"GZMB"
                data1[!grepl("GZMB+", data1$phen),"phen3"]<-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_NK<-data1 %>% filter(Population == "NK")
                
                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))
                
                data_NK$ymax<-cumsum(data_NK$value)
                data_NK$ymin<-c(0, head(data_NK$ymax, n=-1))
                
                data1<-rbind(data_cd8, data_cd4, data_NK)
                
                
                # color<-c(c("CTLA4+ LAG3+ PD1+ TIM3+"="black","All Negative"="grey90","Other"="grey50", "PD1+"="#C07AFF", "CTLA4+"="#3EB3DE","TIM3+"="#5EF551","LAG3+"="#DEBB3E"),
                #          c("CTLA4+ PD1+"="#6666FF","PD1+ TIM3+"="#849CA8", "LAG3+ PD1+"="#C47F9F", "CTLA4+ TIM3+"="#4ED498", "CTLA4+ LAG3+"="#8EB78E", "LAG3+ TIM3+"="#9ED848"),
                #          c("CTLA4+ PD1+ TIM3+"="#B81515", "LAG3+ PD1+ TIM3+"="#0f5860"))
                
                # basic.color<-color[c("PD1+","TIM3+","CTLA4+","LAG3+")]
                # names(basic.color)<-c("PD1","TIM3","CTLA4","LAG3")
                # Make the plot
                
                color<-colorRampPalette(brewer.pal(8, "Set3"))(length(bool.name))
                names(color)<-bool.name %>% gsub("[A-Z0-9]*-", "", .) %>% gsub("  "," ",.) %>% gsub("[ ]*$", "", .) %>% gsub("^[ ]*", "", .) %>% gsub("^$","All Negative", .)
                color["All Negative"]<-"grey90"
                basic.color<-color[c("CD38+","HLADR+","GZMB+")]
                names(basic.color)<-c("CD38","HLADR","GZMB")
                g_coex<-ggplot(data1)+
                    facet_grid(.~factor(Population, levels=c("CD8","CD4","NK")))+
                    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("CD38","HLADR","GZMB"))))+
                    geom_rect(aes(ymax=ymax, ymin=ymin, xmax=5.9, xmin=5.5, fill=factor(phen2, levels=c("CD38","HLADR","GZMB"))))+
                    geom_rect(aes(ymax=ymax, ymin=ymin, xmax=6.4, xmin=6, fill=factor(phen3, levels=c("CD38","HLADR","GZMB"))))+
                    scale_fill_manual(values = basic.color, na.value="#FFFFFF00", drop=F, limits=c("CD38","HLADR","GZMB"), name="Activation")+
                    coord_polar(theta="y") + # Try to remove that to understand how the chart is built initially
                    xlim(c(0, 6.5)) +# 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("CD38|HLADR|GZMB|root$", nodes)]
                nodes_cd4<-nodes[grepl("CD38$|HLADR$|GZMB$", nodes) & grepl("/CD4/",nodes)]
                nodes_cd8<-nodes[grepl("CD38$|HLADR$|GZMB$", nodes) & grepl("/CD8/",nodes)]
                nodes_NK<-nodes[grepl("CD38$|HLADR$|GZMB$", nodes) & grepl("/NK/",nodes)]
                
                
                g1<-ggcyto_arrange(autoplot(gs[[id]], nodes_parent), nrow=3)
                g2<-ggcyto_arrange(autoplot(gs[[id]], nodes_cd8), nrow=1)
                g3<-ggcyto_arrange(autoplot(gs[[id]], nodes_cd4), nrow=1)
                g4<-ggcyto_arrange(autoplot(gs[[id]], nodes_NK), nrow=1)
                
                g_dots<-ggpubr::ggarrange(gridExtra::gtable_rbind(g1), NULL,
                                  gridExtra::gtable_rbind(g2,g3,g4), nrow=1, widths=c(0.35,0.1,0.55))
                
                # g_dots<-gridExtra::gtable_cbind(g1, gridExtra::gtable_rbind(g2,g3,g4))
                
                g_all<-ggpubr::ggarrange(g_dots, g_coex, ncol=1, heights=c(0.75,0.25))
                ggsave(paste0(route,id,".Panel3.png"), g_all, width = 14, height = 12)
                ggsave(paste0(db_path, "Informes/",id,".Panel3.png"), g_all, width = 14, height = 12)
            }
            print("Informes finalizados!")
        }
    })
    
    observeEvent(input$popexport,{
        if (input$phenotype == "Panel1"){
            route<-cito_dir
            
            ws<-open_flowjo_xml(paste0(route,"Panel1.wsp"))
            gs<-flowjo_to_gatingset(ws, name="All Samples")
            
            sampleNames(gs)<-sapply(sampleNames(gs), function(x) strsplit(x, "Panel1 ")[[1]][2]) %>% 
                gsub("[[:space:]][0-9]*.fcs_.[0-9]*","", . , perl = T)
            
            gs<-gs[sampleNames(gs)[!grepl("Iso|ISO|iso",sampleNames(gs))]]
            
            bool.comb<-apply(
                expand.grid(c("","!"), c("","!"), c("","!"), c("","!")),
                1,
                function(x) paste0(x[1],"CTLA4 & ",x[2],"LAG3 & ",x[3],"PD1 & ",x[4], "TIM3")
            )
            
            bool.name<-apply(
                expand.grid(c("+","-"), c("+","-"), c("+","-"), c("+","-")),
                1,
                function(x) paste0("CTLA4",x[1]," LAG3",x[2]," PD1",x[3]," TIM3",x[4])
            )
            
            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$|LAG3$", 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)
            
            ## Esto si no hay isotipo
            
            pop_sp<-pop
            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 %>% spread(pop, percent)
            
            ## Esto si hay Isotipo
            
            # 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<-read.xlsx(paste0(db_path,"Panel1.xlsx"), sheet = "IC")
            pop_sp<-pop_sp %>% merge(pop_sql %>% slice(0), all=T) %>% select(colnames(pop_sql))
            ic_sp<-rbind(pop_sql, pop_sp)
            
            nodes<-sapply(strsplit(gs_get_pop_paths(gs), "/"), tail, 1)
            nodes<-gs_get_pop_paths(gs)[grepl("_",nodes)]
            pop<-gs_pop_get_stats(gs, nodes=nodes,type="percent") %>% as.data.frame %>% mutate(percent=percent*100)
            pop<-pop %>% mutate(Population=str_extract(pop, "/_CD[4,8]{1}/"), 
                           Population=case_when(is.na(Population)~"",
                                                Population == "/_CD4/"~"_CD4",
                                                Population == "/_CD8/"~"_CD8",
                                                TRUE~Population),
                           pop=gsub("_","",pop),
                           pop=paste0(pop,Population)) %>% select(-Population)
            
            pop$pop<-sapply(strsplit(pop$pop, "/"), tail, 1)
            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<-read.xlsx(paste0(db_path,"Panel1.xlsx"), sheet = "POPULATIONS")
            pop_sp<-pop_sp %>% merge(pop_sql %>% slice(0), all=T) %>% select(colnames(pop_sql))
            pop_sp<-rbind(pop_sql,pop_sp)
            
            write.xlsx(list("IC"=ic_sp, "POPULATIONS"=pop_sp), paste0(db_path, "Panel1.xlsx"))
            print("Tabla Panel1 sincronizada.")
        }
        if (input$phenotype == "Panel3"){
            route<-cito_dir
            
            ws<-open_flowjo_xml(paste0(route,"Panel3.wsp"))
            gs<-flowjo_to_gatingset(ws, name="All Samples")
            
            sampleNames(gs)<-sapply(sampleNames(gs), function(x) strsplit(x, "Panel3 ")[[1]][2]) %>% 
                gsub("[[:space:]][0-9]*.fcs_.[0-9]*","", . , perl = T)
            
            gs<-gs[sampleNames(gs)[!grepl("Iso|ISO|iso|NoBV421",sampleNames(gs))]]
            
            bool.comb<-apply(
                expand.grid(c("","!"), c("","!"), c("","!")),
                1,
                function(x) paste0(x[1],"CD38 & ",x[2],"HLADR & ",x[3],"GZMB")
            )
            
            bool.name<-apply(
                expand.grid(c("+","-"), c("+","-"), c("+","-")),
                1,
                function(x) paste0("CD38",x[1]," HLADR",x[2]," GZMB",x[3])
            )
            
            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])
            }
            
            print("Booleanos NK")
            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="NK", 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("CD38", nodes)]
            nodes<-nodes[!grepl("CD38$|HLADR$|GZMB$", 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)
            
            ## Esto si no hay isotipo
            
            pop_sp<-pop
            pop_sp["Population"]<-str_extract(pop_sp$pop, "/CD[4,8]{1}/") %>% gsub("/|_","",.)
            pop_sp$Population[is.na(pop_sp$Population)]<-"NK"
            pop_sp$pop<-sapply(strsplit(pop_sp$pop, "/"), tail, 1)
            pop_sp<-pop_sp %>% spread(pop, percent)
            
            pop_sql<-read.xlsx(paste0(db_path,"Panel3.xlsx"), check.names = F, sep.names = " ")
            pop_sp<-pop_sp %>% merge(pop_sql %>% slice(0), all=T) %>% select(colnames(pop_sql))
            pop_sp<-rbind(pop_sql, pop_sp)
            
            write.xlsx(pop_sp, paste0(db_path, "Panel3.xlsx"))
            print("Tabla Panel3 sincronizada.")
        }
    }) 

}

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