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435 lines
20 KiB
435 lines
20 KiB
library(shiny)
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library(openCyto)
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library(flowCore)
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library(flowWorkspace)
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library(CytoML)
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library(ggcyto)
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# library(reshape2)
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# library(CitFuns)
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library(openxlsx)
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library(tidyverse)
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# Define UI for application that draws a histogram
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ui <- fluidPage(
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# Application title
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titlePanel("Análisis Citometría ImmunoPreserve"),
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# Sidebar with a slider input for number of bins
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sidebarLayout(
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sidebarPanel(
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selectInput("phenotype", "Panel", selected="Panel1", choices=c("Panel1", "Panel2","Panel3","panel4")),
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),
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mainPanel(
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textInput("cytopath", label="Directorio fenotipo", value=""),
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actionButton("goButtonDir","Selecciona directorio fenotipo"),
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textOutput("session"),
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hr(),
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actionButton("fcsconvert", "Convertir a fcs"),
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hr(),
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actionButton("pngexport", "Exportar informes"),
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hr(),
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textInput("dbpath", label="Ruta Base de Dades", value=""),
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actionButton("goButtondbpath","Selecciona Ruta Base de Dades"),
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textOutput("sessiondbpath"),
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actionButton("popexport", "Actualizar BBDD")
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)
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)
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)
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# Define server logic required to draw a histogram
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server <- function(input, output) {
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observe({
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if(input$goButtonDir > 0){
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if (input$cytopath == ""){
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cito_dir<<-choose.dir() %>% gsub("\\","/",. ,fixed=T) %>% paste0("/") %>% stringi::stri_enc_tonative()
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}else{
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cito_dir<<-input$cytopath %>% gsub("\\","/",. ,fixed=T) %>% gsub("/$", "", .) %>% paste0("/") %>% stringi::stri_enc_tonative()
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}
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output$session <- renderText(
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cito_dir
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)
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}
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})
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observe({
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if(input$goButtondbpath > 0){
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if (input$dbpath == ""){
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db_path<<-choose.dir() %>% gsub("\\","/",. ,fixed=T) %>% paste0("/") %>% stringi::stri_enc_tonative()
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}else{
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db_path<<-input$dbpath %>% gsub("\\","/",. ,fixed=T) %>% gsub("/$", "", .) %>% paste0("/") %>% stringi::stri_enc_tonative()
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}
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output$sessiondbpath <- renderText(
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db_path
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)
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}
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})
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observeEvent(input$fcsconvert,{
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route<-cito_dir
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files<-list.files(route, ".LMD")
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for (lmd in files){
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fcs<-read.FCS(paste0(route,lmd), dataset = 2)
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keyword(fcs)['$FIL']<-paste0(gsub(".LMD","",lmd), ".fcs")
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write.FCS(fcs, paste0(route, gsub(".LMD","",lmd), ".fcs"))
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}
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print("Conversión completada")
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})
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observeEvent(input$pngexport,{
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# if (input$phenotype == "Pop"){
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# route<-cito_dir
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#
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# ws<-open_flowjo_xml(paste0(route,"Populations.wsp"))
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# gs<-flowjo_to_gatingset(ws, name="All Samples")
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#
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# sampleNames(gs)<-sapply(sampleNames(gs), function(x) strsplit(x, "Pop ")[[1]][2]) %>%
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# gsub("[[:space:]][0-9]*.fcs_.[0-9]*","", . , perl = T)
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#
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# for (samp in sampleNames(gs)){
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# print(samp)
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# p<-autoplot(gs[[samp]], bins=64)
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# ggsave(paste0(route, samp,".pop.png"),p,width = 10, height = 10)
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# }
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# }
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if (input$phenotype == "Panel1"){
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route<-cito_dir
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ws<-open_flowjo_xml(paste0(route,"Panel1.wsp"))
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gs<-flowjo_to_gatingset(ws, name="All Samples")
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sampleNames(gs)<-sapply(sampleNames(gs), function(x) strsplit(x, "Panel1 ")[[1]][2]) %>%
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gsub("[[:space:]][0-9]*.fcs_.[0-9]*","", . , perl = T)
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gs<-gs[sampleNames(gs)[!grepl("Iso|ISO|iso",sampleNames(gs))]]
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bool.comb<-apply(
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expand.grid(c("","!"), c("","!"), c("","!"), c("","!")),
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1,
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function(x) paste0(x[1],"CTLA4 & ",x[2],"LAG3 & ",x[3],"PD1 & ",x[4], "TIM3")
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)
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bool.name<-apply(
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expand.grid(c("+","-"), c("+","-"), c("+","-"), c("+","-")),
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1,
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function(x) paste0("CTLA4",x[1]," LAG3",x[2]," PD1",x[3]," TIM3",x[4])
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)
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print("Booleanos CD8")
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for (i in 1:length(bool.comb)){
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call<-substitute(booleanFilter(v), list(v=as.symbol(bool.comb[i])))
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boolgate<-eval(call)
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gs_pop_add(gs, boolgate, parent="_CD8", name = bool.name[i])
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}
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print("Booleanos CD4")
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for (i in 1:length(bool.comb)){
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call<-substitute(booleanFilter(v), list(v=as.symbol(bool.comb[i])))
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boolgate<-eval(call)
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gs_pop_add(gs, boolgate, parent="_CD4", name = bool.name[i])
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}
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recompute(gs)
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names<-sampleNames(gs) # %>% gsub("ab|Ab|AB|iso|Iso|ISO| ","",.) %>% unique()
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nodes<-gs_get_pop_paths(gs)
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# nodes<-gsub("â\u0081»", "-", nodes)
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# nodes<-gsub("â\u0081º", "+", nodes)
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nodes<-nodes[grepl("CTLA4", nodes)]
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nodes<-nodes[!grepl("_CD4$|_CD8$|CTLA4$|TIM3$|PD1$|LAG3$", nodes)]
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pop<-gs_pop_get_stats(gs, nodes=nodes,type="percent") %>% as.data.frame %>% mutate(percent=percent*100)
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pop$percent<-round(pop$percent, digits=2)
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# pop$pop<-gsub("â\u0081»", "n", pop$pop)
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# pop$pop<-gsub("â\u0081º", "p", pop$pop)
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pop$pop<-gsub("-", "n", pop$pop, fixed=T)
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pop$pop<-gsub("+", "p", pop$pop, fixed=T)
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pop$pop<-gsub(" ", "_", pop$pop)
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## Esto si no hay isotipo
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pop_sp<-pop
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pop_sp["Population"]<-str_extract(pop_sp$pop, "/_CD[4,8]{1}/") %>% gsub("/|_","",.)
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pop_sp$pop<-sapply(strsplit(pop_sp$pop, "/"), tail, 1)
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pop_sp<-pop_sp %>% spread(pop, percent)
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## Esto si hay Isotipo
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# pop["Type"]<-"ab"
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# pop[grepl("iso|ISO|Iso",pop$sample),"Type"]<-"iso"
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# pop$sample<-gsub("iso|ISO|Iso|ab|AB|Ab| ","",pop$sample)
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# pop_sp<-pop %>% spread(Type, percent)
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# pop_sp["Net"]<-pop_sp$ab
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# 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$pop),"iso"]
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# pop_sp$Net[pop_sp$Net < 0]<-0
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# pop_sp["Population"]<-str_extract(pop_sp$pop, "/CD[4,8]{1}/") %>% gsub("/","",.)
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# pop_sp$pop<-sapply(strsplit(pop_sp$pop, "/"), tail, 1)
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#
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# pop_sp<-pop_sp %>% select(-ab,-iso) %>% spread(pop,Net)
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# pop_sp$CTLA4n_LAG3n_PD1n_TIGITn_TIM3n<- pop_sp %>% select(-CTLA4n_LAG3n_PD1n_TIGITn_TIM3n) %>% group_by(sample,Population) %>%
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# gather(pop, value, -sample,-Population) %>% summarise(n=100-sum(value)) %>% pull(n)
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# if (input$dbtype == "OV"){
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# pop_sp <- rename(pop_sp, "samples"="sample")
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# }
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# if (input$dbtype %in% c("UM", "CC")){
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# pop_sp <- rename(pop_sp, "CODIGO"="sample")
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#
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pop_sql<-read.xlsx(paste0(db_path,"Panel1.xlsx"), sheet = "IC")
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pop_sp<-pop_sp %>% merge(pop_sql %>% slice(0), all=T) %>% select(colnames(pop_sql))
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for (id in names){
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print(id)
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# iso<-sampleNames(gs)[grepl(id, sampleNames(gs)) & grepl("iso|Iso|ISO",sampleNames(gs))]
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# ab<-sampleNames(gs)[grepl(id, sampleNames(gs)) & grepl("ab|Ab|AB",sampleNames(gs))]
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data<-pop_sp %>% filter(sample == id)
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data1<-data %>% gather(phen, value, -sample, -Population)
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data1$phen<-gsub("p","+",data1$phen)
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data1$phen<-gsub("n","-",data1$phen)
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data1$phen<-gsub("_"," ",data1$phen)
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data1$phen<-gsub("n","-",data1$phen, fixed = T)
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data1$phen<-gsub("p","+",data1$phen, fixed = T)
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data1$phen<-gsub("_"," ",data1$phen)
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data1[data1$value < 1, "phen"]<-"Other"
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data1$phen<-gsub("[A-Z]*-*[0-9T]- *", "", data1$phen)
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data1$phen<-gsub("+ $", "", data1$phen)
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data1$phen[data1$phen == ""]<-"All Negative"
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data1["phen1"]<-"PD1"
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data1[!grepl("PD1+", data1$phen),"phen1"]<-NA
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data1["phen2"]<-"TIM3"
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data1[!grepl("TIM3+", data1$phen),"phen2"]<-NA
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data1["phen3"]<-"CTLA4"
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data1[!grepl("CTLA4+", data1$phen),"phen3"]<-NA
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data1["phen4"]<-"LAG3"
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data1[!grepl("LAG3+", data1$phen),"phen4"]<-NA
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data1<-data1 %>% arrange(desc(value))
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data2<-data1 %>% filter(!phen %in% c("All Negative","Other"))
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data1<-rbind(data2, data1 %>% filter(phen %in% c("All Negative","Other")) %>% arrange(desc(phen)))
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data_cd8<-data1 %>% filter(Population == "CD8")
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data_cd4<-data1 %>% filter(Population == "CD4")
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data_cd8$ymax<-cumsum(data_cd8$value)
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data_cd8$ymin<-c(0, head(data_cd8$ymax, n=-1))
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data_cd4$ymax<-cumsum(data_cd4$value)
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data_cd4$ymin<-c(0, head(data_cd4$ymax, n=-1))
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data1<-rbind(data_cd8, data_cd4)
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color<-c(c("CTLA4+ LAG3+ PD1+ TIM3+"="black","All Negative"="grey90","Other"="grey50", "PD1+"="#C07AFF", "CTLA4+"="#3EB3DE","TIM3+"="#5EF551","LAG3+"="#DEBB3E"),
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c("CTLA4+ PD1+"="#6666FF","PD1+ TIM3+"="#849CA8", "LAG3+ PD1+"="#C47F9F", "CTLA4+ TIM3+"="#4ED498", "CTLA4+ LAG3+"="#8EB78E", "LAG3+ TIM3+"="#9ED848"),
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c("CTLA4+ PD1+ TIM3+"="#B81515", "LAG3+ PD1+ TIM3+"="#0f5860"))
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basic.color<-color[c("PD1+","TIM3+","CTLA4+","LAG3+")]
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names(basic.color)<-c("PD1","TIM3","CTLA4","LAG3")
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# Make the plot
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g_coex<-ggplot(data1)+
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facet_grid(.~factor(Population, levels=c("CD8","CD4")))+
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geom_rect(aes(ymax=ymax, ymin=ymin, xmax=4.5, xmin=0), fill=color[data1$phen])+
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geom_rect(aes(ymax=ymax, ymin=ymin, xmax=5.4, xmin=5, fill=factor(phen1, levels=c("PD1","TIM3","CTLA4","LAG3"))))+
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geom_rect(aes(ymax=ymax, ymin=ymin, xmax=5.9, xmin=5.5, fill=factor(phen2, levels=c("PD1","TIM3","CTLA4","LAG3"))))+
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geom_rect(aes(ymax=ymax, ymin=ymin, xmax=6.4, xmin=6, fill=factor(phen3, levels=c("PD1","TIM3","CTLA4","LAG3"))))+
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geom_rect(aes(ymax=ymax, ymin=ymin, xmax=6.9, xmin=6.5, fill=factor(phen4, levels=c("PD1","TIM3","CTLA4","LAG3"))))+
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scale_fill_manual(values = basic.color, na.value="#FFFFFF00", drop=F, limits=c("PD1","TIM3","CTLA4","LAG3"), name="IC")+
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coord_polar(theta="y") + # Try to remove that to understand how the chart is built initially
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xlim(c(0, 8)) +# Try to remove that to see how to make a pie chart
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theme_classic()+
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theme(strip.background = element_blank(),
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strip.text = element_text(size=12, face="bold"),
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axis.line = element_blank(),
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axis.ticks = element_blank(),
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# plot.margin = margin(-200,0,0,0),
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axis.text = element_blank())
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nodes<-gs_get_pop_paths(gs)
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nodes_parent<-nodes[!grepl("CTLA4|LAG3|PD1|TIM3|root$", nodes)]
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nodes_cd4<-nodes[grepl("CTLA4$|LAG3$|PD1$|TIM3$", nodes) & grepl("/_CD4/",nodes)]
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nodes_cd8<-nodes[grepl("CTLA4$|LAG3$|PD1$|TIM3$", nodes) & grepl("/_CD8/",nodes)]
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g1<-ggcyto_arrange(autoplot(gs[[id]], nodes_parent), nrow=2)
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g2<-ggcyto_arrange(autoplot(gs[[id]], nodes_cd8), nrow=1)
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g3<-ggcyto_arrange(autoplot(gs[[id]], nodes_cd4), nrow=1)
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g_dots<-gridExtra::gtable_rbind(g1,g2,g3)
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g_all<-ggpubr::ggarrange(g_dots, g_coex, ncol=1, heights=c(0.75,0.25))
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ggsave(paste0(route,id,".IC.png"), g_all, width = 10, height = 14)
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ggsave(paste0(db_path, "Informes/",id,".IC.png"), g_all, width = 10, height = 14)
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}
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print("Informes finalizados!")
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}
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})
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observeEvent(input$popexport,{
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if (input$phenotype == "Pop"){
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route<-cito_dir
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ws<-open_flowjo_xml(paste0(route,"Populations.wsp"))
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gs<-flowjo_to_gatingset(ws, name="All Samples")
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sampleNames(gs)<-sapply(sampleNames(gs), function(x) strsplit(x, "Pop ")[[1]][2]) %>%
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gsub("[[:space:]][0-9]*.fcs_.[0-9]*","", . , perl = T)
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nodes<-sapply(strsplit(gs_get_pop_paths(gs), "/"), tail, 1)
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nodes<-nodes[grepl("_",nodes)]
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pop<-gs_pop_get_stats(gs, nodes=nodes,type="percent") %>% as.data.frame %>% mutate(percent=percent*100)
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pop[,"pop"]<-gsub("_","",pop$pop)
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pop$pop<-gsub(" ","_",pop$pop)
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pop$pop<-gsub("+","pos",pop$pop, fixed=T)
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pop$pop<-gsub("-","neg",pop$pop, fixed=T)
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pop<-rename(pop, "samples"="sample")
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pop$percent<-round(pop$percent, digits=2)
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pop_sp<-pop %>% spread(pop, percent)
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pop_sql<-sqlFetch(dta, "POPULATIONS") %>% slice(0)
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pop_sp<-pop_sp %>% merge(pop_sql, all=T) %>% select(colnames(pop_sql))
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vartypes<-rep("Number", pop_sp %>% select(-samples) %>% colnames %>% length)
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names(vartypes)<-pop_sp %>% select(-samples) %>% colnames
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sqlSave(dta, pop_sp, tablename="POPULATIONS", append = T, varTypes = vartypes, rownames = F)
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print("Tabla POPULATIONS sincronizada.")
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}
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if (input$phenotype == "Panel1"){
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route<-cito_dir
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ws<-open_flowjo_xml(paste0(route,"Panel1.wsp"))
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gs<-flowjo_to_gatingset(ws, name="All Samples")
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sampleNames(gs)<-sapply(sampleNames(gs), function(x) strsplit(x, "Panel1 ")[[1]][2]) %>%
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gsub("[[:space:]][0-9]*.fcs_.[0-9]*","", . , perl = T)
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gs<-gs[sampleNames(gs)[!grepl("Iso|ISO|iso",sampleNames(gs))]]
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bool.comb<-apply(
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expand.grid(c("","!"), c("","!"), c("","!"), c("","!")),
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1,
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function(x) paste0(x[1],"CTLA4 & ",x[2],"LAG3 & ",x[3],"PD1 & ",x[4], "TIM3")
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)
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bool.name<-apply(
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expand.grid(c("+","-"), c("+","-"), c("+","-"), c("+","-")),
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1,
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function(x) paste0("CTLA4",x[1]," LAG3",x[2]," PD1",x[3]," TIM3",x[4])
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)
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print("Booleanos CD8")
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for (i in 1:length(bool.comb)){
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call<-substitute(booleanFilter(v), list(v=as.symbol(bool.comb[i])))
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boolgate<-eval(call)
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gs_pop_add(gs, boolgate, parent="_CD8", name = bool.name[i])
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}
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print("Booleanos CD4")
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for (i in 1:length(bool.comb)){
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call<-substitute(booleanFilter(v), list(v=as.symbol(bool.comb[i])))
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boolgate<-eval(call)
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gs_pop_add(gs, boolgate, parent="_CD4", name = bool.name[i])
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}
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recompute(gs)
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names<-sampleNames(gs) # %>% gsub("ab|Ab|AB|iso|Iso|ISO| ","",.) %>% unique()
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nodes<-gs_get_pop_paths(gs)
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# nodes<-gsub("â\u0081»", "-", nodes)
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# nodes<-gsub("â\u0081º", "+", nodes)
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nodes<-nodes[grepl("CTLA4", nodes)]
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nodes<-nodes[!grepl("_CD4$|_CD8$|CTLA4$|TIM3$|PD1$|LAG3$", nodes)]
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pop<-gs_pop_get_stats(gs, nodes=nodes,type="percent") %>% as.data.frame %>% mutate(percent=percent*100)
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pop$percent<-round(pop$percent, digits=2)
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# pop$pop<-gsub("â\u0081»", "n", pop$pop)
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# pop$pop<-gsub("â\u0081º", "p", pop$pop)
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pop$pop<-gsub("-", "n", pop$pop, fixed=T)
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pop$pop<-gsub("+", "p", pop$pop, fixed=T)
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pop$pop<-gsub(" ", "_", pop$pop)
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## Esto si no hay isotipo
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pop_sp<-pop
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pop_sp["Population"]<-str_extract(pop_sp$pop, "/_CD[4,8]{1}/") %>% gsub("/|_","",.)
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pop_sp$pop<-sapply(strsplit(pop_sp$pop, "/"), tail, 1)
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pop_sp<-pop_sp %>% spread(pop, percent)
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## Esto si hay Isotipo
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# pop["Type"]<-"ab"
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# pop[grepl("iso|ISO|Iso",pop$sample),"Type"]<-"iso"
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# pop$sample<-gsub("iso|ISO|Iso|ab|AB|Ab| ","",pop$sample)
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# pop_sp<-pop %>% spread(Type, percent)
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# pop_sp["Net"]<-pop_sp$ab
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# pop_sp[!grepl("CTLA4n_LAG3n_PD1n_TIGITn_TIM3n",pop_sp$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"]
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# pop_sp$Net[pop_sp$Net < 0]<-0
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# pop_sp["Population"]<-str_extract(pop_sp$pop, "/CD[4,8]{1}/") %>% gsub("/","",.)
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# pop_sp$pop<-sapply(strsplit(pop_sp$pop, "/"), tail, 1)
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#
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# pop_sp<-pop_sp %>% select(-ab,-iso) %>% spread(pop,Net)
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|
# pop_sp$CTLA4n_LAG3n_PD1n_TIGITn_TIM3n<- pop_sp %>% select(-CTLA4n_LAG3n_PD1n_TIGITn_TIM3n) %>% group_by(sample,Population) %>%
|
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# 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")
|
|
#
|
|
|
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pop_sql<-read.xlsx(paste0(db_path,"Panel1.xlsx"), sheet = "IC")
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|
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)
|