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Visor scRNAseq.

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Costa 2 years ago
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commit
b14fddf8fe
1 changed files with 67 additions and 0 deletions
  1. +67
    -0
      BDAccess/app.R

+ 67
- 0
BDAccess/app.R

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

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