Compute all 5 pairwise statistical tables

Orchestrator that returns a [`StatisticsResult-class`] populated with Jaccard, Dice, Overlap Coefficient, Fold Enrichment (square NxN matrices) plus a long-form hypergeometric table with BH-FDR adjustment.

Usage

compute_pairwise(
  set_names,
  inclusive_sizes,
  pairwise_intersections,
  universe_size
)

Arguments

set_names

Ordered character vector of set identifiers (e.g. c("A","B","C")).

inclusive_sizes

Named integer vector of inclusive set sizes (`names(inclusive_sizes)` matches `set_names`).

pairwise_intersections

Named list of pair intersection counts. Keys are "set_a|set_b" with set_a appearing earlier in `set_names` than set_b.

universe_size

Hypergeometric universe N (population size). Integer >= 1.

Value

A [`StatisticsResult-class`] object.

Examples

compute_pairwise(
    set_names = c("A", "B"),
    inclusive_sizes = c(A = 10L, B = 8L),
    pairwise_intersections = list("A|B" = 5L),
    universe_size = 100L
)
#> An object of class "StatisticsResult"
#> Slot "jaccard":
#>           A         B
#> A 1.0000000 0.3846154
#> B 0.3846154 1.0000000
#> 
#> Slot "dice":
#>           A         B
#> A 1.0000000 0.5555556
#> B 0.5555556 1.0000000
#> 
#> Slot "overlap_coefficient":
#>       A     B
#> A 1.000 0.625
#> B 0.625 1.000
#> 
#> Slot "fold_enrichment":
#>      A    B
#> A   NA 6.25
#> B 6.25   NA
#> 
#> Slot "hypergeometric":
#>   set_a set_b intersection expected      p_value   p_adjusted significant
#> 1     A     B            5      0.8 0.0001636692 0.0001636692        TRUE
#>   highly_significant
#> 1               TRUE
#>