tests/testthat/test_coreFeatures.R

In hiAnnotator: Functions for annotating GRanges objects

test_that("all core function tests", {

  #### Basic tests ####
  query <- GRanges("A", IRanges(c(1, 5, 12, 20), width = 1),
                   strand = c("-", "+", "-", "+"))
  subject <- GRanges("A", IRanges(c(1, 5, 10, 15, 21), width = 8:4),
                     strand = c("+", "+", "-", "-", "-"))
  
  #### test count based annotations ####
  res <- findOverlaps(query, rep(subject, each = 3),
                      maxgap = 10, ignore.strand = TRUE)
  expect_that(countQueryHits(res), is_identical_to(c(9L, 12L, 15L, 12L)))
  
  #### test in/out based annotations ####
  res <- overlapsAny(query, subject, ignore.strand = TRUE)
  expect_that(res, is_identical_to(c(TRUE, TRUE, TRUE, FALSE)))
  
  #### test nearest type annotations relative to query ####
  res <- as.data.frame(nearest(query, subject, 
                               select = "all", ignore.strand = TRUE))
  res <- getLowestDists(query, subject, res, "either", "query")
  rownames(res) <- NULL
  
  ## for getNearestFeature() ##
  expect_that(res,
              is_identical_to(structure(
                list(
                  queryHits = c(1L, 2L, 3L, 4L, 4L),
                  subjectHits = c(1L, 2L, 2L, 4L, 5L),
                  dist = c(0L, 0L, 1L, -1L, 1L)
                ),
                class = "data.frame",
                row.names = c(NA, -5L),
                .Names = c("queryHits", "subjectHits", "dist")
              )))
  
  ## for get2NearestFeature() ##
  res$qStrand <- as.character(strand(query))[res$queryHits]
  res <- res %>%
    mutate(u2 = ifelse(dist < 0,
                       ifelse(qStrand == "+", subjectHits - 1,
                              subjectHits + 1),
                       ifelse(qStrand == "+", subjectHits - 2,
                              subjectHits + 2)),
           u1 = ifelse(dist < 0, 
                       subjectHits,
                       ifelse(qStrand == "+", subjectHits - 1, 
                              subjectHits + 1)),
           d1 = ifelse(dist < 0,
                       ifelse(qStrand == "+", subjectHits + 1,
                              subjectHits - 1), 
                       subjectHits),
           d2 = ifelse(dist < 0,
                       ifelse(qStrand == "+", subjectHits + 2,
                              subjectHits - 2),
                       ifelse(qStrand == "+", subjectHits + 1,
                              subjectHits - 1)))
  
  expect_that(res,
              is_identical_to(structure(
                list(
                  queryHits = c(1L, 2L, 3L, 4L, 4L),
                  subjectHits = c(1L, 2L, 2L, 4L, 5L),
                  dist = c(0L, 0L, 1L, -1L, 1L),
                  qStrand = c("-", "+", "-", "+", "+"),
                  u2 = c(3, 0, 4, 3, 3),
                  u1 = c(2, 1, 3, 4, 4),
                  d1 = c(1, 2, 2, 5, 5),
                  d2 = c(0, 3, 1, 6, 6)
                ),
                class = "data.frame",
                .Names = c(
                  "queryHits", "subjectHits", "dist", "qStrand",
                  "u2", "u1", "d1", "d2"
                ),
                row.names = c(NA, -5L)
              )))
  
  ## for getNearestFeature(): 5p, 3p, and midpoint ##
  subject5p <- flank(subject, width = -1)
  subject3p <- flank(subject, width = -1, start = FALSE)
  ranges(subject) <- IRanges(mid(ranges(subject)), width = 1)
  
  res <- as.data.frame(nearest(query, subject5p, 
                               select = "all", ignore.strand = TRUE))
  res <- getLowestDists(query, subject5p, res, "5p", "query")
  expect_that(res,
              is_identical_to(structure(
                list(
                  queryHits = 1:4,
                  subjectHits = 1:4,
                  dist = c(0L, 0L, -3L, -1L)
                ),
                .Names = c("queryHits", "subjectHits", "dist"),
                row.names = c(NA, -4L),
                class = "data.frame"
              )))
  
  res <- as.data.frame(nearest(query, subject3p, 
                               select = "all", ignore.strand = TRUE))
  res <- getLowestDists(query, subject3p, res, "3p", "query")
  expect_that(res,
              is_identical_to(structure(
                list(
                  queryHits = 1:4,
                  subjectHits = c(1L, 1L, 2L, 5L),
                  dist = c(-7L, 3L, 1L, 1L)
                ),
                .Names = c("queryHits", "subjectHits", "dist"),
                row.names = c(NA, 4L),
                class = "data.frame"
              )))
  
  res <- as.data.frame(nearest(query, subject, 
                               select = "all", ignore.strand = TRUE))
  res <- getLowestDists(query, subject, res, "midpoint", "query")
  expect_that(res,
              is_identical_to(structure(
                list(
                  queryHits = 1:4,
                  subjectHits = c(1L, 1L, 3L, 5L),
                  dist = c(-3L, -1L, 0L, 2L)
                ),
                .Names = c("queryHits", "subjectHits", "dist"),
                row.names = c(NA, 4L),
                class = "data.frame"
              )))
  
  ## test relative to subject ##
  res <- getLowestDists(query, subject, res, "midpoint", "subject")
  expect_that(res,
              is_identical_to(structure(
                list(
                  queryHits = 1:4,
                  subjectHits = c(1L, 1L, 3L, 5L),
                  dist = c(-3L, 1L, 0L, 2L)
                ),
                .Names = c("queryHits", "subjectHits", "dist"),
                row.names = c(NA, 4L),
                class = "data.frame"
              )))
})