if (interactive()) {
  context("Binder tests, part 1")

  # Defining the relative path to current inst ---------------------------------
  notebook_data_path <- system.file("notebook", package = "DIscBIO")
  FileName <- "CTCdataset"
  load(file.path(notebook_data_path, paste0(FileName, ".rda")))
  load(file.path(notebook_data_path, "SC.RData"))
  load(file.path(notebook_data_path, "Ndata.RData"))
  load(file.path(notebook_data_path, "expdata.RData"))
  DataSet <- get(FileName)

  test_that("Loading CTC dataset", {
    expect_equal(length(DataSet[, 1]), 13181)
    expect_equal(length(DataSet[1, ]), 1462)
  })

  sc <- DISCBIO(DataSet)
  S1 <- summary(colSums(DataSet, na.rm = TRUE))
  S2 <- summary(rowMeans(DataSet, na.rm = TRUE))
  minexpr <- S2[3]
  minnumber <- round(length(DataSet[1, ]) / 10)

  test_that("Handling datasets", {
    expect_true(is(sc, "DISCBIO"))
    expect_output(str(S1), " 'summaryDefault' Named num")
    expect_equal(minnumber, 146)
  })

  sc <- Normalizedata(
    sc,
    minexpr = minexpr, minnumber = minnumber, rseed = 17000
  )
  sc <- suppressMessages(FinalPreprocessing(sc, GeneFlitering = "ExpF"))
  sc <- SC
  sc@ndata <- Ndata
  sc@expdata <- expdata

  # Removing the unneeded objects
  rm(Ndata)
  rm(expdata)
  rm(DataSet)
  rm(SC)
  gc()

  long_test <- FALSE # switching to true runs slow tests below
  if (long_test) {
    sc <- Clustexp(sc, 4, bootnr = 2, B.gap = 2, quiet = TRUE, rseed = 17000)
    outlg <- round(length(sc@fdata[, 1]) * 0.05)
    Outliers <- FindOutliers(sc, 4, outlg = outlg, plot = FALSE, quiet = TRUE)
    jcrd <- Jaccard(sc, K = 4, plot = FALSE, R = 2)
    sc <- pseudoTimeOrdering(sc, quiet = TRUE)

    test_that("Post-processing", {
      expect_equivalent(jcrd, c(.422, .649, .335, .605))
      expect_output(
        object = str(sc, max.level = 1),
        expected = 'Formal class \'DISCBIO\' [package "DIscBIO"] with 21 slots'
      )
    })
  }
}