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One-way or Repeated-Measures ANOVA for Differential Expression Analysis

gly_anova.Rd

Perform one-way or repeated-measures ANOVA for glycomics or glycoproteomics data. For significant results, Tukey's HSD post-hoc test is automatically performed. P-values are adjusted for multiple testing using the method specified by p_adj_method.

Usage

gly_anova(
  exp,
  group_col = "group",
  p_adj_method = "BH",
  add_info = TRUE,
  ...,
  subject_col = NULL,
  log_transform = TRUE
)

Arguments

exp

A glyexp::GlycomicSE() or glyexp::GlycoproteomicSE() object, or another SummarizedExperiment containing an expression matrix and sample information.

group_col

A character string specifying the column name of the grouping variable in the sample information. Default is "group".

p_adj_method

A character string specifying the method to adjust p-values. See p.adjust.methods for available methods. Default is "BH". If NULL, no adjustment is performed.

add_info

A logical value. If TRUE (default), variable information from the experiment will be added to the result tibble. If FALSE, only the statistical results are returned.

...

Additional arguments passed to stats::aov().

subject_col

An optional character string naming the subject identifier column in sample information. When supplied, a subject-blocked repeated-measures ANOVA is performed.

log_transform

A single non-missing logical value. If TRUE (default), transform expression values using log2(x + 1e-6) before analysis. If FALSE, use the supplied values unchanged, for example for already log-transformed data.

Value

A list containing three elements:

  • tidy_result: A list containing:

    • main_test: A tibble with ANOVA results containing the following columns:

      • variable: Variable name

      • term: ANOVA term (usually "groups")

      • df: Degrees of freedom

      • sumsq: Sum of squares

      • meansq: Mean squares

      • statistic: F-statistic

      • p_val: Raw p-value from ANOVA

      • effect_size: Eta-squared, or partial eta-squared for paired analyses

      • p_adj: Adjusted p-value (if p_adj_method is not NULL)

      • post_hoc: Significant group pairs from post-hoc test, in the format of "ref_vs_test".

    • post_hoc_test: A tibble with pairwise comparison results containing the following columns:

      • variable: Variable name

      • ref_group: Reference group

      • test_group: Test/treatment/case group

      • p_val: Raw post-hoc p-value

      • p_adj: Adjusted post-hoc p-value

  • raw_result: A list containing:

    • main_test: A list of raw aov model objects.

    • post_hoc_test: A list of raw TukeyHSD objects or paired t-test summaries.

  • meta_data: A list containing metadata from the input experiment.

Details

Tests and effect sizes use the selected analysis scale. Reported fold changes continue to use ratios of group means from the original supplied values.

By default, expression data are transformed using log2(x + 1e-6) before statistical testing. Set log_transform = FALSE to skip this transformation. At least 2 groups are required in the grouping variable. In paired analyses, only subjects observed in every group are used, with at most one sample per subject and group. The reported effect size is partial eta-squared for the group term.

For any variable failed to fit a stats::aov() model, NAs will be assigned to the results in both main test and post-hoc test.

Post-hoc Test: Tukey's HSD test for pairwise comparisons (stats::TukeyHSD()) is performed for variables with significant main effects (p_adj < 0.05). Paired analyses instead use paired t-tests with Holm correction.

See also

stats::aov(), stats::TukeyHSD()