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@ -1,5 +1,9 @@ |
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library(shiny) |
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library(rhandsontable) |
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library(tidyverse) |
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library(reshape2) |
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library(Matrix) |
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library(CitFuns) |
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print(getwd()) |
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source("../sqlFunctions.R", encoding = "UTF-8") |
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@ -59,6 +63,19 @@ ui <- fluidPage( |
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h3("Nitrogen"), |
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tableOutput("nitrogen") |
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) |
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), |
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tabPanel("scRNAseq", |
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sidebarPanel( |
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textInput("sqlquery", label = "sqlquery", value = ""), |
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uiOutput("PATID"), |
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checkboxInput("cd45_chk", "Purificación CD45") |
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), |
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mainPanel( |
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tabsetPanel( |
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tabPanel("Table", tableOutput("sc_table")), |
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tabPanel("Plots", plotOutput("sc_plot")) |
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) |
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) |
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) |
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) |
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) |
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@ -677,6 +694,56 @@ server <- function(input, output) { |
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## scRNAseq |
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output$PATID = renderUI({ |
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observeEvent(input$goButton, {}) |
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sc_cod<-sqlFetch(dta, "CNAG") %>% pull(CODIGO) |
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selectizeInput("sc_cod", "CÓDIGO", sc_cod, multiple = T) |
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}) |
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output$sc_table<-renderTable({ |
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if (input$sqlquery != ""){ |
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print(input$sqlquery) |
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sqlQuery(dta, input$sqlquery) |
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}else{ |
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if (!is.null(input$sc_cod)){ |
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sqlFetch(dta, "CNAG") %>% filter(CODIGO %in% input$sc_cod) |
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}else{ |
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sqlFetch(dta, "CNAG") |
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} |
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} |
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}) |
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output$sc_plot <-renderPlot({ |
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meta<-readRDS(paste0(scRNAseqRoute,"metadata_full_object.rds")) |
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if (input$sqlquery != ""){ |
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sc_codigos<-sqlQuery(dta, input$sqlquery) %>% pull(CNAG_NAME) |
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}else{ |
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if (!is.null(input$sc_cod)){ |
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sc_codigos<-sqlFetch(dta, "CNAG") %>% filter(CODIGO %in% input$sc_cod) %>% pull(CNAG_NAME) |
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}else{ |
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sc_codigos<-sqlFetch(dta, "CNAG") %>% pull(CNAG_NAME) |
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} |
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} |
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sc_codigos<-gsub(" _","_", sc_codigos ) |
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sc_codigos<-gsub("_ ","_", sc_codigos ) |
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sc_codigos<-gsub(" ","_", sc_codigos ) |
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meta<-meta %>% mutate(sample2=gsub("_CD45", "", sample)) %>% filter(sample2 %in% sc_codigos) |
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if (isFALSE(input$cd45_chk)){ meta<-meta %>% filter(!grepl("_CD45", sample))} |
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g1<-ggplot(meta, aes(coord_x, coord_y, color=predicted.id))+ |
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geom_point(size=0.2)+ |
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guides(colour = guide_legend(override.aes = list(size=2)))+ |
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theme_bw()+ |
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theme(aspect.ratio = 1) |
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meta_perc<-meta %>% group_by(sample, predicted.id) %>% summarise(N=n()) %>% mutate(N=perc(N)) %>% |
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spread(predicted.id, N) %>% gather("predicted.id","N",-sample) %>% mutate(N=case_when(is.na(N)~0,TRUE~N)) |
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g2<-ggheatmap(meta_perc, "sample","predicted.id", "N", color = "grey50") |
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ggpubr::ggarrange(g1,g2, ncol=1, heights = c(0.3, 0.7)) |
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}, height = 1000) |
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} |
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# Run the application |
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