04 Export

Our data analysis process generated different populations:

• the NonDebris population
• the GFP+ population
• the GFP-low, GFP-medium, GFP-high population
• the MyHC+

Each population is characterized by its size i.e the number of cells that met the gating criteria for this population. This information is saved as a population table which can be retrieved using the gs_pop_get_stats( ) function. We wrap this function into a map_df( ) call to extract and combine the population tables from each dataset in the GatingSet to a large and unique population table.

reactive({
  purrr::map_df(r$gs, \(x) as.data.frame(gs_pop_get_stats(x)))
})

Users are able to download the population table. We implemented this using Shiny’s downloadHandler( ) function as well as the write.table( ) function.

downloadHandler(filename = function() file_name(), # custom filename
                content = function(file){
                  writeLines(file,
                             text = text()) # metadata
                  write.table(population_table(), # population table
                              file = file,
                              sep = ",",
                              append = TRUE,
                              row.names = FALSE,
                              col.names = FALSE,
                              quote = FALSE)})

Users can customize the name of the downloaded file.

file_name <- reactive({
  if (isTruthy(input$filename)) {
    if (input$add_date == TRUE) {paste0(Sys.Date(), "_", input$filename,".csv")}
    else {paste0(input$filename, ".csv", sep = "")}
  }
  else {
    if (input$add_date == TRUE) {paste0(Sys.Date(), "_", "population_statistics.csv")}
    else {paste0("population_statistics.csv")}
  }
})