In calabrialab/ISAnalytics: Analyze gene therapy vector insertion sites data identified from genomics next generation sequencing reads for clonal tracking studies

knitr::opts_chunk$set(echo = FALSE, warning = FALSE)
options(DT.warn.size = FALSE)

File system alignment {data-orientation=rows}

Row1

Project/pool folders found

found_folders <- length(params$fs_align$Found[params$fs_align$Found == TRUE])
valueBox(found_folders, icon = "fa-folder-open")

Quantification folders found

paths_cols <- .path_cols_names()
quant_folders_found <- length(params$fs_align[[paths_cols$quant]][!is.na(params$fs_align[[paths_cols$quant]])])
valueBox(quant_folders_found, icon = "fa-table")

VISPA2 stats folders found

stats_folders_found <- length(params$fs_align[[paths_cols$iss]][!is.na(params$fs_align[[paths_cols$iss]])])
valueBox(stats_folders_found, icon = "fa-chart-bar")

Row2

Project/pool folders found on total

found_folder_perc <- (found_folders / length(params$fs_align$Found)) * 100
gauge(value = round(found_folder_perc, digits = 1), min = 0, max = 100, symbol = "%", sectors = gaugeSectors(success = c(100, 100), danger = c(0, 99)))

Quantification folders found on total

quant_folders_perc <- (quant_folders_found / length(params$fs_align$Path_quant)) * 100
gauge(value = round(quant_folders_perc, digits = 1), min = 0, max = 100, symbol = "%", abbreviateDecimals = 2, sectors = gaugeSectors(success = c(100, 100), danger = c(0, 99)))

VISPA2 stats folders found on total

stats_folders_perc <- (stats_folders_found / length(params$fs_align$Path_iss)) * 100
gauge(value = round(stats_folders_perc, digits = 1), min = 0, max = 100, symbol = "%", abbreviateDecimals = 2, sectors = gaugeSectors(success = c(100, 100), danger = c(0, 99)))

Row3 {.tabset .tabset-fade}

File system alignment results

datatable(
  data = params$fs_align,
  class = "stripe",
  filter = "top", 
  rownames = FALSE,
  options = list(
    order = list(list(3, 'asc')),
    scrollY = "450px"
  )
) |>
  formatStyle(columns = "Found", 
              color = styleEqual(
                levels = c(TRUE, FALSE),
                values = c(found_color, not_found_color)
              ), fontWeight = "bold", textTransform = "uppercase")