perform_pairwise_non_parametric: Perform pairwise non-parametric tests

In antonvsdata/notame: Workflow for non-targeted LC-MS metabolic profiling

Perform pairwise non-parametric tests

Description

Performs pairwise non-parametric tests between all study groups. Use is_paired = FALSE for Mann-Whitney u-tests Use is_paired = TRUE for Wilcoxon signed rank tests. NOTE! Does not use formula interface

Usage

perform_pairwise_non_parametric(
  object,
  group = group_col(object),
  is_paired = FALSE,
  id = NULL,
  all_features = FALSE,
  ...
)

Arguments

object	a MetaboSet object
group	character, column name of phenoData giving the groups
is_paired	logical, use pairwise tests
id	character, name of the subject identification column for paired version
all_features	should all features be included in FDR correction?
...	other parameters passed to test functions

Details

P-values of each comparison are corrected separately from each other.

Value

data frame with the results

See Also

perform_mann_whitney, perform_wilcoxon_signed_rank, wilcox.test

Examples

# Including QCs as a study group for example
mann_whitney_results <- perform_pairwise_non_parametric(merged_sample, group = "Group")
# Using paired mode (pairs with QC are skipped as there are no common IDs in 'example_set')
wilcoxon_signed_results <- perform_pairwise_non_parametric(example_set,
  group = "Time",
  is_paired = TRUE,
  id = "Subject_ID"
)

antonvsdata/notame documentation built on Sept. 14, 2024, 11:09 p.m.