use base pipe

README.Rmd

@@ -51,7 +51,7 @@ intergenic <- bed_subtract(snps, genes)
 # find distance from intergenic snps to nearest gene
 nearby <- bed_closest(intergenic, genes)
 
-nearby %>%
-  select(starts_with("name"), .overlap, .dist) %>%
+nearby |>
+  select(starts_with("name"), .overlap, .dist) |>
   filter(abs(.dist) < 5000)
 ```

README.md

@@ -48,8 +48,8 @@ intergenic <- bed_subtract(snps, genes)
 # find distance from intergenic snps to nearest gene
 nearby <- bed_closest(intergenic, genes)
 
-nearby %>%
-  select(starts_with("name"), .overlap, .dist) %>%
+nearby |>
+  select(starts_with("name"), .overlap, .dist) |>
   filter(abs(.dist) < 5000)
 #> # A tibble: 1,047 × 4
 #>    name.x      name.y   .overlap .dist

bench/benchmarks.Rmd

@@ -79,20 +79,20 @@ res <- mark(
   time_unit = 's')
 
 # covert nanoseconds to seconds
-res2<- res %>%
-  as_tibble() %>%
-  mutate(expression = as.character(expression)) %>% 
-  tidyr::unnest(time) %>% 
+res2<- res |>
+  as_tibble() |>
+  mutate(expression = as.character(expression)) |> 
+  tidyr::unnest(time) |> 
   arrange(time)
 
 # futz with the x-axis
-maxs <- res2 %>%
-  group_by(expression) %>%
+maxs <- res2 |>
+  group_by(expression) |>
   summarize(max.time = max(boxplot.stats(time)$stats))
 
 # filter out outliers
-res <- res2 %>%
-  left_join(maxs) %>%
+res <- res2 |>
+  left_join(maxs) |>
   filter(time <= max.time * 1.05)
 
 ggplot(res, aes(x=reorder(expression, time), y=time)) +
@@ -157,28 +157,28 @@ res2 <- mark(
   time_unit = 's')
 
 # label experiment pair and software
-comp <- as_tibble(summary(res2)) %>% 
-  mutate(pair = as.numeric(row_number()) %% (nrow(res2) / 1 / 2)) %>% 
-  mutate(software = rep(c("valr", "GR"), each = (nrow(res2) / 1 / 2))) %>%
-  select(expression, pair, software) %>% 
+comp <- as_tibble(summary(res2)) |> 
+  mutate(pair = as.numeric(row_number()) %% (nrow(res2) / 1 / 2)) |> 
+  mutate(software = rep(c("valr", "GR"), each = (nrow(res2) / 1 / 2))) |>
+  select(expression, pair, software) |> 
   mutate(expression = as.character(expression))
 
 # convert time table
-res2 <- res2 %>%
-  mutate(expression = as.character(expression)) %>% 
-  as_tibble() %>%
-  left_join(comp) %>%
-  tidyr::unnest(time) %>% 
+res2 <- res2 |>
+  mutate(expression = as.character(expression)) |> 
+  as_tibble() |>
+  left_join(comp) |>
+  tidyr::unnest(time) |> 
   arrange(time)
 
 # futz with the x-axis
-maxs2 <- res2 %>%
-  group_by(expression) %>%
+maxs2 <- res2 |>
+  group_by(expression) |>
   summarize(max.time = max(boxplot.stats(time)$stats))
 
 # filter out outliers
-res2 <- res2 %>%
-  left_join(maxs2) %>%
+res2 <- res2 |>
+  left_join(maxs2) |>
   filter(time <= max.time * 1.05)
 
 #label

tests/testthat/test_closest.r

@@ -486,9 +486,9 @@ test_that("ensure that subtraction is done with respect to input tbls issue#108"
     "chr1", 125, 175, "C",
     "chr2", 150, 200, "A"
   )
-  x_grouped <- arrange(x, chrom, start) %>%
+  x_grouped <- arrange(x, chrom, start) |>
     group_by(group, chrom)
-  y_grouped <- arrange(y, chrom, start) %>%
+  y_grouped <- arrange(y, chrom, start) |>
     group_by(group, chrom)
   res <- bed_closest(x_grouped, y_grouped)
   expect_true(all(res$group.x == res$group.y))

tests/testthat/test_cluster.r

@@ -39,13 +39,13 @@ x <- tibble::tribble(
 test_that("cluster ids are not repeated per group issue #171", {
   res <- bed_cluster(x)
   # test that groups have unique ids
-  chr1_ids <- filter(res, chrom == "chr1") %>%
-    select(.id) %>%
-    unique() %>%
+  chr1_ids <- filter(res, chrom == "chr1") |>
+    select(.id) |>
+    unique() |>
     unlist()
-  chr2_ids <- filter(res, chrom == "chr2") %>%
-    select(.id) %>%
-    unique() %>%
+  chr2_ids <- filter(res, chrom == "chr2") |>
+    select(.id) |>
+    unique() |>
     unlist()
   shared_ids <- intersect(chr1_ids, chr2_ids)
   expect_equal(length(shared_ids), 0)

tests/testthat/test_coverage.r

@@ -74,7 +74,7 @@ test_that("coverage of stranded tbls can be calc", {
     "chr2", 150, 200, 4, 25, "+", 3, 50, 50, 1.0000000,
     "chr2", 180, 230, 2, 25, "-", 4, 34, 50, 0.6800000
   )
-  res <- bed_coverage(group_by(a, strand), group_by(b, strand)) %>%
+  res <- bed_coverage(group_by(a, strand), group_by(b, strand)) |>
     arrange(chrom, start)
   expect_true(all(res == pred))
 })
@@ -89,7 +89,7 @@ test_that(" strand_opp coverage works (strand_opp = TRUE)", {
     "chr2", 150, 200, 4, 25, "+", 4, 50, 50, 1.0000000,
     "chr2", 180, 230, 2, 25, "-", 2, 50, 50, 1.0000000
   )
-  res <- bed_coverage(group_by(a, strand), group_by(flip_strands(b), strand)) %>%
+  res <- bed_coverage(group_by(a, strand), group_by(flip_strands(b), strand)) |>
     arrange(chrom, start)
   expect_true(all(res == pred))
 })

tests/testthat/test_features.r

@@ -17,22 +17,22 @@ test_that("feature lengths are valid", {
 
 test_that("introns and exons don't overlap", {
   # substracting exons from introns should be empty
-  expect_equal(nrow(introns %>%
+  expect_equal(nrow(introns |>
     bed_subtract(x)), 0)
 })
 
 test_that("there is 1 feature from each gene", {
-  expect_true(all(utrs5 %>%
-    group_by(name) %>%
-    tally() %>%
+  expect_true(all(utrs5 |>
+    group_by(name) |>
+    tally() |>
     pull(n) == 1))
-  expect_true(all(utrs3 %>%
-    group_by(name) %>%
-    tally() %>%
+  expect_true(all(utrs3 |>
+    group_by(name) |>
+    tally() |>
     pull(n) == 1))
-  expect_true(all(tss %>%
-    group_by(name) %>%
-    tally() %>%
+  expect_true(all(tss |>
+    group_by(name) |>
+    tally() |>
     pull(n) == 1))
 })
 
@@ -41,8 +41,8 @@ test_that("TSS are single base features", {
 })
 
 test_that("intron numbers are not duplicated #377", {
-  expect_true(group_by(introns, name) %>%
-    summarize(no_duplicates = !any(duplicated(score))) %>%
-    pull(no_duplicates) %>%
+  expect_true(group_by(introns, name) |>
+    summarize(no_duplicates = !any(duplicated(score))) |>
+    pull(no_duplicates) |>
     all())
 })

tests/testthat/test_flank.r

@@ -43,7 +43,7 @@ test_that("all left and right intervals are reported with both arg", {
   out_left <- bed_flank(x, genome, left = dist)
   out_right <- bed_flank(x, genome, right = dist)
   out_both <- bed_flank(x, genome, both = dist)
-  out_left_right <- dplyr::bind_rows(out_left, out_right) %>%
+  out_left_right <- dplyr::bind_rows(out_left, out_right) |>
     arrange(chrom, start)
   expect_true(all(out_both == out_left_right))
 })

tests/testthat/test_intersect.r

@@ -292,10 +292,10 @@ test_that("same intervals are reported with single and multiple intersection", {
   )
   a <- bed_intersect(x, y)
   b <- bed_intersect(x, z)
-  orig <- bind_rows(a, b) %>%
+  orig <- bind_rows(a, b) |>
     arrange(chrom, start.x, start.y)
-  new <- bed_intersect(x, y, z) %>%
-    arrange(chrom, start.x, start.y) %>%
+  new <- bed_intersect(x, y, z) |>
+    arrange(chrom, start.x, start.y) |>
     select(-.source)
   expect_true(all(orig == new))
 })
@@ -307,15 +307,15 @@ test_that("unmatched groups are included when invert = TRUE", {
     "chr2", 200, 400, "B", # unmatched
     "chr2", 300, 500, "A",
     "chr2", 800, 900, "A"
-  ) %>% group_by(chrom, group)
+  ) |> group_by(chrom, group)
 
   y <- tibble::tribble(
     ~chrom, ~start, ~end, ~group,
     "chr1", 150, 400, "A",
     "chr1", 500, 550, "A",
     "chr2", 230, 430, "A",
     "chr2", 350, 430, "A"
-  ) %>% group_by(chrom, group)
+  ) |> group_by(chrom, group)
 
   pred <- tibble::tribble(
     ~chrom, ~start, ~end, ~group,

tests/testthat/test_map.r

@@ -4,15 +4,15 @@ test_that("x/y groupings are respected", {
     "chr1", 100, 250, 1,
     "chr2", 250, 500, 2,
     "chr2", 250, 500, 3
-  ) %>%
+  ) |>
     group_by(id)
 
   y <- tibble::tribble(
     ~chrom, ~start, ~end, ~value, ~id,
     "chr1", 100, 250, 10, 1,
     "chr1", 150, 250, 20, 2,
     "chr2", 250, 500, 500, 3
-  ) %>%
+  ) |>
     group_by(id)
 
   pred <- tibble::tribble(
@@ -167,7 +167,7 @@ y <- tibble::tribble(
 test_that("test count", {
   res <- bed_map(x, y, vals = n())
   expect_equal(res$vals, c(3, 1, NA, NA, 3, 1))
-  res2 <- bed_map(x, y, vals = n()) %>% mutate(vals = ifelse(is.na(vals), 0, vals))
+  res2 <- bed_map(x, y, vals = n()) |> mutate(vals = ifelse(is.na(vals), 0, vals))
   expect_equal(res2$vals, c(3, 1, 0, 0, 3, 1))
 })
 

tests/testthat/test_merge.r

@@ -164,8 +164,8 @@ test_that("Test stranded merge with bedPlus files that have strand", {
   skip_if(packageVersion("readr") <= "1.4.0")
 
   expect_warning(x <- read_bed(valr_example("bug254_e.bed"), skip = 1, lazy = FALSE))
-  x <- x %>% group_by(strand)
-  res <- bed_merge(x, 200) %>% arrange(end)
+  x <- x |> group_by(strand)
+  res <- bed_merge(x, 200) |> arrange(end)
   expect_equal(res$end, c(20000, 25000))
 })
 

tests/testthat/test_random.r

@@ -16,8 +16,8 @@ test_that("returns correctly sized intervals", {
 
 test_that("all ends are less or equal to than chrom size", {
   len <- 1000
-  res <- bed_random(genome, length = len, n = 1e4, seed = seed) %>%
-    mutate(chrom = as.character(chrom)) %>%
+  res <- bed_random(genome, length = len, n = 1e4, seed = seed) |>
+    mutate(chrom = as.character(chrom)) |>
     left_join(genome, by = "chrom")
   expect_true(all(res$end <= res$size))
 })
@@ -36,7 +36,7 @@ test_that("intervals are sorted by default", {
   expect_false(all(x == y))
 
   # default sort
-  x_sort <- x %>%
+  x_sort <- x |>
     arrange(chrom, start)
   expect_true(all(x == x_sort))
 })

tests/testthat/test_shift.r

@@ -41,7 +41,7 @@ test_that("starts forced to 0", {
 
 test_that("end forced to chrom length", {
   size <- 1675
-  out <- bed_shift(bed_tbl, genome, size) %>%
+  out <- bed_shift(bed_tbl, genome, size) |>
     left_join(genome, by = "chrom")
   expect_true(all(out$end <= out$size))
 })

tests/testthat/test_shuffle.r

@@ -9,7 +9,7 @@ genome <- tibble::tribble(
 seed <- 1010486
 
 # Random genome intervals for bed_shuffle tests
-x <- bed_random(genome, n = 100, seed = seed) %>%
+x <- bed_random(genome, n = 100, seed = seed) |>
   arrange(chrom, start)
 
 test_that("within = TRUE maintains chroms", {

tests/testthat/test_slop.r

@@ -11,21 +11,21 @@ x <- tibble::tribble(
 
 test_that("left arg works", {
   dist <- 100
-  out <- x %>%
+  out <- x |>
     bed_slop(genome, left = dist)
   expect_true(all(x$start - out$start == dist))
 })
 
 test_that("right arg works", {
   dist <- 100
-  out <- x %>%
+  out <- x |>
     bed_slop(genome, right = dist)
   expect_true(all(out$end - x$end == dist))
 })
 
 test_that("both arg works", {
   dist <- 100
-  out <- x %>%
+  out <- x |>
     bed_slop(genome, both = dist)
   expect_true(all(x$start - out$start == dist))
   expect_true(all(out$end - x$end == dist))

tests/testthat/test_spacing.r

@@ -8,12 +8,12 @@ test_that("start intervals are NA", {
 
   res <- interval_spacing(x)
 
-  first <- res %>%
-    group_by(chrom) %>%
-    slice(1) %>%
+  first <- res |>
+    group_by(chrom) |>
+    slice(1) |>
     select(chrom:end)
 
-  nas <- filter(res, is.na(.spacing)) %>%
+  nas <- filter(res, is.na(.spacing)) |>
     select(chrom:end)
 
   expect_true(all(first == nas))