Run a differential test by name: Wilcoxon or label-shuffle

Thin wrapper that selects between `wilcoxon()` and `label_shuffling()`.

Usage

test_differential(
  x,
  samples,
  control = NULL,
  method = c("wilcoxon", "shuffle"),
  fc_method = "mean",
  paired = FALSE,
  exact = FALSE,
  randomizations = 100,
  pcorr = "BH",
  seed = 123L,
  paired_method = c("swap", "signflip"),
  nthreads = 1
)

Arguments

x: A matrix with splicing diversity values (rows = features).
samples: Character vector of sample group labels (length = ncol(x)).
control: Name of the control group (required for label-shuffle).
method: Character; one of `'wilcoxon'` or `'shuffle'`.
fc_method: Character; aggregation method used by the permutation test when `method = 'shuffle'` ('mean' or 'median').
paired: Logical passed to `wilcoxon()` when using the Wilcoxon test.
exact: Logical passed to `wilcoxon()` to request exact p-values.
randomizations: Integer number of permutations for `label_shuffling()`.
pcorr: P-value adjustment method (passed to `p.adjust`).
seed: Integer seed used to make permutations reproducible (default 123). The function sets a temporary RNG seed via `withr::local_seed(seed)` before running `label_shuffling()` when `method = 'shuffle'`.
paired_method: Character; forwarded to `label_shuffling()` when `method = 'shuffle'`. See `label_shuffling()` for details.
nthreads: Number of threads for parallel processing (default: 1). Set to > 1 to parallelize per-feature statistical tests in `wilcoxon()` or `label_shuffling()`.

Value

A two-column matrix with raw and adjusted p-values (as returned by the underlying functions).

Examples

mat <- matrix(rnorm(20), nrow = 5)
samples <- rep(c('A', 'B'), length.out = ncol(mat))
test_differential(mat, samples, control = 'A', method = 'wilcoxon')
#>      raw_p_values adjusted_p_values
#> [1,]    0.6985354         0.8731692
#> [2,]    0.2452781         0.6131953
#> [3,]    0.2452781         0.6131953
#> [4,]    0.6985354         0.8731692
#> [5,]    1.0000000         1.0000000