Compute coverage of intervals.

Compute coverage of intervals.

Usage

bed_coverage(x, y, ...)

Arguments

x

ivl_df

y

ivl_df

...

extra arguments (not used)

Value

ivl_df with the following additional columns:

• .ints number of x intersections

• .cov per-base coverage of x intervals

• .len total length of y intervals covered by x intervals

• .frac .len scaled by the number of y intervals

Details

input tbls are grouped by chrom by default, and additional groups can be added using dplyr::group_by(). For example, grouping by strand will constrain analyses to the same strand. To compare opposing strands across two tbls, strands on the y tbl can first be inverted using flip_strands().

Note

Book-ended intervals are included in coverage calculations.

See also

https://bedtools.readthedocs.io/en/latest/content/tools/coverage.html

Other multiple set operations: bed_closest(), bed_intersect(), bed_map(), bed_subtract(), bed_window()

Examples

x <- tibble::tribble(
  ~chrom, ~start, ~end, ~strand,
  "chr1", 100,    500,  "+",
  "chr2", 200,    400,  "+",
  "chr2", 300,    500,  "-",
  "chr2", 800,    900,  "-"
)

y <- tibble::tribble(
  ~chrom, ~start, ~end, ~value, ~strand,
  "chr1", 150,    400,  100,    "+",
  "chr1", 500,    550,  100,    "+",
  "chr2", 230,    430,  200,    "-",
  "chr2", 350,    430,  300,    "-"
)

bed_coverage(x, y)
#> # A tibble: 4 × 8
#>   chrom start   end strand .ints  .cov  .len .frac
#>   <chr> <dbl> <dbl> <chr>  <int> <int> <dbl> <dbl>
#> 1 chr1    100   500 +          2   250   400 0.625
#> 2 chr2    200   400 +          2   170   200 0.85 
#> 3 chr2    300   500 -          2   130   200 0.65 
#> 4 chr2    800   900 -          0     0   100 0