Run differential association tests between between all combinations of a factor variable. Can be used as post-hoc test for regression.

Source: R/testing.R

Run differential association tests between between all combinations of a factor variable. Can be used as post-hoc test for regression.

combinatorial_association(ps, variable, tax = "genus",
  confounders = NULL, min_count = 10, in_samples = 0.1,
  independent_weighting = TRUE, standardize = TRUE, shrink = TRUE)

Arguments

ps

A phyloseq object containing the taxa counts.
variable

The factor variable to permute.
tax

The taxa level on which to run differential tests. Defaults to genus.
confounders

A character vector containing the confounders that should be used.
min_count

Minimum required number of average counts for a taxa.
in_samples

Taxa must be present in at least this fraction of samples.
independent_weighting

Whether to adjust p values by independent weighting or normal Benjamini-Hochberg. factors.
standardize

Whether to standardize continuous variables to a mean of zero and a variance of 1. If True log fold changes for those variables denote are relative to a change of one standard deviation in the variable value.
shrink

Whether to return shrunken log fold changes. Defaults to true.

Value

A data.table containing the results.

Examples

 NULL
#> NULL