Indicator species analysis on each phyloseq object in a list_phyloseq

Performs indicator species analysis using indicspecies::multipatt() on each phyloseq object in a list_phyloseq and returns a combined result table of significant indicator taxa.

Usage

multipatt_lpq(
  x,
  fact,
  p_adjust_method = "BH",
  pval = 0.05,
  control = permute::how(nperm = 999),
  verbose = TRUE,
  ...
)

Arguments

x: (required) A list_phyloseq object.
fact: (character, required) The name of a column in sample_data to use as the grouping factor. Must be present in all phyloseq objects.
p_adjust_method: (character, default "BH") The p-value adjustment method. See stats::p.adjust() for available methods.
pval: (numeric, default 0.05) The significance threshold for adjusted p-values.
control: (list, default permute::how(nperm = 999)) Permutation control settings for the permutation test.
verbose: (logical, default TRUE) If TRUE, print progress messages.
...: Additional arguments passed to indicspecies::multipatt().

Value

A tibble with the combined significant indicator taxa from all phyloseq objects. Contains columns from multipatt()$sign output plus taxon (taxon name), p.adj (adjusted p-value), and name (identifying the source phyloseq object). Only taxa with p.adj < pval are included.

Details

This function requires that the list_phyloseq type is NOT SEPARATE_ANALYSIS, as the factor must be common across all phyloseq objects.

Unlike MiscMetabar::multipatt_pq() which returns a plot, this function returns the underlying data as a tibble, making it easier to compare results across phyloseq objects.

When no common taxa exist across the phyloseq objects, taxa names are suffixed with the phyloseq object name to make them distinguishable.

Examples

if (FALSE) { # \dontrun{
lpq <- list_phyloseq(
  list(
    fungi = data_fungi,
    fungi_clust = postcluster_pq(data_fungi)
  ),
  same_bioinfo_pipeline = FALSE
)

results <- multipatt_lpq(lpq, fact = "Height")
results
} # }