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.

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

A character string that is unique to this step to identify it.

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_aldex(), step_ancom(), step_corncob(), step_deseq(), step_lefse(), step_linda(), step_maaslin()

Examples

data(metaHIV_phy)

## Init Recipe
rec <-
  recipe(metaHIV_phy) |>
  add_model(~ RiskGroup2, targets = "RiskGroup2", tax_level = "Phylum") |>
  step_subset_taxa(tax_level = "Kingdom", taxa = c("Bacteria", "Archaea"))

## Define step with default parameters
rec <- step_wilcox(rec)
#> Registered S3 method overwritten by 'car':
#>   method           from
#>   na.action.merMod lme4
rec
#> ── DAR Recipe ──────────────────────────────────────────────────────────────────
#> Inputs:
#> 
#>      ℹ phyloseq object with 451 taxa and 156 samples 
#>      ℹ variable of interes RiskGroup2 (class: character, levels: hts, msm, pwid) 
#>      ℹ taxonomic level Phylum 
#> 
#> Statistical model:
#> 
#>      ℹ ~RiskGroup2 
#> 
#> Preprocessing steps:
#> 
#>      ◉ step_subset_taxa() id = subset_taxa__Bizcocho 
#> 
#> DA steps:
#> 
#>      ◉ step_wilcox() id = wilcox__Apple_pie