tests/testthat/test-easyquant.R

In TRON-Bioinformatics/splice2neo: Aberrant splice junction analysis with associated mutations

test_that("transform_for_requant works", {
  cts_id <- c("0cb012d5e", "0cb012d5e", "1276125bbd07")
  cts_seq <- c("GCAAATATGGATTAAGCCGC", "GCAAATATGGATTAAGCCGC", "CCGCCAAAGCATTATGGAG")
  cts_junc_pos <- c(7, 7, 7)
  df <- tibble(cts_id , cts_seq, cts_junc_pos)

  df_easy <- transform_for_requant(df)
  expect_equal(nrow(df_easy), 2)
  expect_equal(ncol(df_easy), 3)


  cts_id <- c("0cb012d5e", "0cb012d5e", "1276125bbd07")
  cts_seq <- c("GCAAATATGGATTAAGCCGC", NA, "CCGCCAAAGCATTATGGAG")
  cts_junc_pos <- c(7, NA, 7)
  df <- tibble(cts_id , cts_seq, cts_junc_pos)

  df_easy <- transform_for_requant(df)
  expect_equal(nrow(df_easy), 2)
  expect_equal(ncol(df_easy), 3)
})


test_that("transform_for_requant works with IR", {

  toy_junc_df_annot <- toy_junc_df %>%
    add_context_seq(transcripts = toy_transcripts)
  df_easy <- toy_junc_df_annot %>%
    transform_for_requant()

  expect_equal(nrow(df_easy), length(unique(toy_junc_df_annot$cts_id)))
  expect_equal(ncol(df_easy), 3)
  expect_true(length(grep(",", df_easy$position)) > 0)



})