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Calculate the Jaccard statistic for two sets of intervals.

Source: R/bed_jaccard.r
bed_jaccard.Rd

Quantifies the extent of overlap between to sets of intervals in terms of base-pairs. Groups that are shared between input are used to calculate the statistic for subsets of data.

Usage

bed_jaccard(x, y)

Arguments

x

ivl_df

y

ivl_df

Value

tibble with the following columns:

  • len_i length of the intersection in base-pairs

  • len_u length of the union in base-pairs

  • jaccard value of jaccard statistic

  • n_int number of intersecting intervals between x and y

If inputs are grouped, the return value will contain one set of values per group.

Details

The Jaccard statistic takes values of [0,1] and is measured as:

$$ J(x,y) = \frac{\mid x \bigcap y \mid} {\mid x \bigcup y \mid} = \frac{\mid x \bigcap y \mid} {\mid x \mid + \mid y \mid - \mid x \bigcap y \mid} $$

Interval statistics can be used in combination with dplyr::group_by() and dplyr::do() to calculate statistics for subsets of data. See vignette('interval-stats') for examples.

See also

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

Other interval statistics: bed_absdist(), bed_fisher(), bed_projection(), bed_reldist()

Examples

genome <- read_genome(valr_example("hg19.chrom.sizes.gz"))

x <- bed_random(genome, seed = 1010486)
y <- bed_random(genome, seed = 9203911)

bed_jaccard(x, y)
#> # A tibble: 1 × 4
#>       len_i      len_u jaccard      n
#>       <dbl>      <dbl>   <dbl>  <dbl>
#> 1 236184699 1708774142   0.160 399981

# calculate jaccard per chromosome
bed_jaccard(
  dplyr::group_by(x, chrom),
  dplyr::group_by(y, chrom)
)
#> # A tibble: 25 × 5
#>    chrom    len_i     len_u jaccard     n
#>    <chr>    <dbl>     <dbl>   <dbl> <dbl>
#>  1 chr1  18939046 137345996   0.160 32156
#>  2 chr10 10524360  75209830   0.163 17830
#>  3 chr11 10378246  74655177   0.161 17497
#>  4 chr12 10146255  73725046   0.160 17163
#>  5 chr13  8867024  63737541   0.162 14992
#>  6 chr14  8047103  59033144   0.158 13647
#>  7 chr15  7794057  56514322   0.160 13236
#>  8 chr16  6907575  49874077   0.161 11650
#>  9 chr17  6186446  44917522   0.160 10487
#> 10 chr18  6044900  43248877   0.162 10129
#> # ℹ 15 more rows