Skip to contents

ALDEx2 analysis

Source: R/aldex2.R
step_aldex2.Rd

Differential abundance analysis using ALDEx2's Monte Carlo log-ratio transformation and native statistical tests. Requires add_model(), fits a GLM for each planned contrast and reports its coefficient and adjusted P value.

Usage

step_aldex2(
  rec,
  max_significance = 0.05,
  mc.samples = 128,
  denom = "all",
  rarefy = FALSE,
  id = rand_id("aldex2"),
  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.

max_significance

Adjusted P value cutoff for the GLM.

mc.samples

The number of Monte Carlo instances to use to estimate the underlying distributions. The default is 128.

denom

Features used as the geometric-mean denominator: "all" (default) or explicit numeric row indices in the aggregated count matrix. Choose indices a priori and account for native removal of all-zero taxa. Data-dependent denominators are not supported with the shared design.

rarefy

Boolean indicating if OTU counts must be rarefyed. This rarefaction uses the standard R sample function to resample from the abundance values in the otu_table component of the first argument, physeq. Often one of the major goals of this procedure is to achieve parity in total number of counts between samples, as an alternative to other formal normalization procedures, which is why a single value for the sample.size is expected. If 'no_seed', rarefaction is performed without a set seed.

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 clr and fit stages. Effects come from the GLM. Arguments managed by dar or exposed above cannot be overridden.

Value

An object of class Recipe

Details

With add_model(), effect is the contrast-oriented coefficient from ALDEx2::aldex.glm(), averaged over Monte Carlo instances, and effect_metric is "aldex_glm_coefficient". It comes from the same GLM as the reported adjusted P value. Under the default denominator, scale and Gaussian identity-link settings, the response is CLR in base 2; this coefficient is not an absolute-abundance log2 fold change or the standardized effect from ALDEx2::aldex.effect(). Advanced native settings can change the response or link scale.

See also

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

Examples

data(metaHIV_phy)

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

rec_default <- step_aldex2(rec)

# Increase the number of Monte Carlo instances.
rec_more_instances <- step_aldex2(rec, mc.samples = 256)