Wilcox analysis

Performs a wilcox test to determine features (be it Operational Taxanomic Unit (OTU), species, etc.) that are differentially abundant between two or more groups of multiple samples.

Usage

step_wilcox(
  rec,
  norm_method = "compositional",
  max_significance = 0.05,
  p_adj_method = "BH",
  rarefy = FALSE,
  id = rand_id("wilcox"),
  engine_args = list()
)

Arguments

rec

A Recipe object. The step will be added to the sequence of operations for this Recipe. Execution requires add_model() before prep(); the step can be configured before adding the model.

norm_method

Transformation to apply. The options include: 'compositional' (ie relative abundance), 'Z', 'log10', 'log10p', 'hellinger', 'identity', 'clr', 'alr', or any method from the vegan::decostand function.

max_significance

The q-value threshold for significance.

p_adj_method

Character. Specifying the method to adjust p-values for multiple comparisons. Default is “BH” (Benjamini-Hochberg procedure).

rarefy

Boolean indicating if OTU counts must be rarefyed.

id

Unique, non-empty identifier for this step. DA step IDs must not use the reserved internal names taxa_id, contrast_id, comparison, contrast_type, var, effect, sum, .tax_order, .contrast_order or .effect_order. Other identifiers, including names such as .custom, are retained unchanged.

engine_args

Named lists of advanced arguments for the native test stage. Arguments managed by dar or exposed above cannot be overridden.

Value

An object of class Recipe

See also

Other Diff taxa steps: step_aldex2(), step_aldex3(), step_ancom(), step_corncob(), step_deseq(), step_lefse(), step_linda(), step_maaslin(), step_rademu()

Examples

data(metaHIV_phy)

rec <- recipe(metaHIV_phy) |>
  add_model(~ RiskGroup2, targets = "RiskGroup2", tax_level = "Phylum")

rec_default <- step_wilcox(rec)

# Use Holm's multiple-testing correction.
rec_holm <- step_wilcox(rec, p_adj_method = "holm")