tests/testthat/test-rank_response.R

In BrentLab/brentlabRnaSeqTools: Management/QC for brentlab RNAseq data

# Test create_partitions
test_that("create_partitions creates correct partitions", {
  expect_equal(create_partitions(14, 3), c(rep(1, 3), rep(2, 3),
                                           rep(3, 3), rep(4, 3),
                                           rep(5, 2)))
  expect_equal(create_partitions(10, 4), c(rep(1, 4), rep(2, 4), rep(3, 2)))
  expect_equal(create_partitions(15, 5), c(rep(1, 5), rep(2, 5), rep(3, 5)))
})

# Test stable_rank_response
test_that("stable_rank_response calculates correct response ratios", {
  # Using a small example dataframe similar to your input
  df <- data.frame(binding_signal = c(0.0411612635618076,0.0214105449966155,
                                      0.0453743372531608,0.0322136499872431,
                                      0.00237970236223191),
                   responsive = c(TRUE, FALSE, TRUE, TRUE, FALSE),
                   experiment = "test_experiment",
                   source_expr = "test_source_expr")
  result <- stable_rank_response(df,
                                 "test_experiment;test_source_expr", 2, ";")

  expect_equal(result$response_ratio, c(0,1/2,1/2))

})

# Test rank_response_ratio_summarize
test_that("rank_response_ratio_summarize rr and random test", {
  # Using a small example dataframe similar to your input
  browser()
  df <- data.frame(
    tf_id = c(1, 1, 1, 1, 2, 2, 2, 2),
    experiment = c("exp1", "exp1", "exp2", "exp2",
                   "exp1", "exp1", "exp2", "exp2"),
    binding_signal =  c(0.043410940724425,0.0212696224823594,
                        0.0109933236078359,0.0379419134766795,
                        0.062146974329371,0.0225317380577326,
                        0.0589414950902574,0.0699747833795846),
    effect_expr = c(0.0402821003729988,-0.504356928856001,-1.39675833299841,
                    -0.856505523602546,0.930709218677073,0.341770719151093,
                    1.59561706277361,0.100902824901006),
    p_expr = c(0.0539662160351872,0.011883190611843,0.00552017204230651,
               0.0686250562802888,0.0217834066436626,0.0213548930757679,
               0.0633223048551008,0.0466870082798414),
    source_expr = c("src1", "src1", "src1", "src1",
                    "src2", "src2", "src2", "src2")
  )

  result <- rank_response_ratio_summarize(df, effect_expr_thres = 0.2,
                                          p_expr_thres = 0.05,
                                          normalize = FALSE,
                                          bin_size = 2,
                                          separator = ';')

  expect_equal(result$rr$response_ratio, c(0.5, 1, 0.5, 0))
  expect_equal(result$random$random, c(0.5, 1, 0.5, 0))
})