From 5ce8a61b8e674d9d7f9855f266a712c82fadd5b9 Mon Sep 17 00:00:00 2001 From: marcelcosta Date: Thu, 21 Apr 2022 17:27:48 +0200 Subject: [PATCH] AInicio y Panel1 --- CitoProcess/app.R | 435 ++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 435 insertions(+) create mode 100644 CitoProcess/app.R diff --git a/CitoProcess/app.R b/CitoProcess/app.R new file mode 100644 index 0000000..fc04e54 --- /dev/null +++ b/CitoProcess/app.R @@ -0,0 +1,435 @@ +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)