library(shiny) library(openCyto) library(flowCore) library(flowWorkspace) library(CytoML) library(ggcyto) # 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 == "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$phenotype == "Panel1"){ route<-cito_dir ws<-open_flowjo_xml(paste0(route,"Panel1.wsp")) gs<-flowjo_to_gatingset(ws, name="All Samples") sampleNames(gs)<-sapply(sampleNames(gs), function(x) strsplit(x, "Panel1 ")[[1]][2]) %>% gsub("[[:space:]][0-9]*.fcs_.[0-9]*","", . , perl = T) gs<-gs[sampleNames(gs)[!grepl("Iso|ISO|iso",sampleNames(gs))]] bool.comb<-apply( expand.grid(c("","!"), c("","!"), c("","!"), c("","!")), 1, function(x) paste0(x[1],"CTLA4 & ",x[2],"LAG3 & ",x[3],"PD1 & ",x[4], "TIM3") ) bool.name<-apply( expand.grid(c("+","-"), c("+","-"), c("+","-"), c("+","-")), 1, function(x) paste0("CTLA4",x[1]," LAG3",x[2]," PD1",x[3]," TIM3",x[4]) ) print("Booleanos CD8") for (i in 1:length(bool.comb)){ call<-substitute(booleanFilter(v), list(v=as.symbol(bool.comb[i]))) boolgate<-eval(call) gs_pop_add(gs, boolgate, parent="_CD8", name = bool.name[i]) } print("Booleanos CD4") for (i in 1:length(bool.comb)){ call<-substitute(booleanFilter(v), list(v=as.symbol(bool.comb[i]))) boolgate<-eval(call) gs_pop_add(gs, boolgate, parent="_CD4", name = bool.name[i]) } recompute(gs) names<-sampleNames(gs) # %>% gsub("ab|Ab|AB|iso|Iso|ISO| ","",.) %>% unique() nodes<-gs_get_pop_paths(gs) # nodes<-gsub("â\u0081»", "-", nodes) # nodes<-gsub("â\u0081º", "+", nodes) nodes<-nodes[grepl("CTLA4", nodes)] nodes<-nodes[!grepl("_CD4$|_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!") } }) 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 == "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.") } }) } # Run the application shinyApp(ui = ui, server = server)