Linear Models for Differential Expression Analysis using limma

Perform differential expression analysis using linear models with empirical Bayes moderation from the limma package. Supports both two-group and multi-group comparisons.

Usage

gly_limma(
  exp,
  group_col = "group",
  p_adj_method = "BH",
  ref_group = NULL,
  contrasts = NULL,
  add_info = TRUE,
  ...
)

gly_limma_(
  expr_mat,
  groups,
  p_adj_method = "BH",
  ref_group = NULL,
  contrasts = NULL,
  ...
)

Arguments

exp: A glyexp_experiment object containing expression data and sample information.
group_col: A character string specifying the column name in sample information that contains group labels. Default is "group".
p_adj_method: A character string specifying the method for multiple testing correction. Must be one of the methods supported by stats::p.adjust(). Default is "BH" (Benjamini-Hochberg). Set to NULL to skip p-value adjustment.
ref_group: A character string specifying the reference group. If NULL (default), the first level of the group factor is used as the reference. Only used for two-group comparisons.
contrasts: A character vector specifying custom contrasts for multi-group comparisons. If NULL (default), all pairwise comparisons are automatically generated. Supports two formats: "group1-group2" or "group1_vs_group2". Use the second format if group names contain hyphens.
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. Only applicable to gly_limma().
...: Additional arguments passed to limma::lmFit().
expr_mat: A numeric matrix with variables as rows and samples as columns.
groups: A factor or character vector specifying group membership for each sample. Must have at least 2 levels. Character vectors will be automatically converted to factors.

Value

A list with two elements:

tidy_result: A tibble with limma results containing the following columns:
- variable: Variable name
- log2fc: Log2 fold change
- AveExpr: Average expression level
- t: t-statistic
- p: Raw p-value
- p_adj: Adjusted p-value (if p_adj_method is not NULL)
- b: B-statistic (log-odds of differential expression)
- contrast: Contrast name (for multi-group comparisons only)
raw_result: The raw limma fit object(s).

Details

The function performs log2 transformation on the expression data (log2(x + 1)) before statistical testing. The analysis uses linear models with empirical Bayes moderation to improve statistical power, especially for small sample sizes.

gly_limma() is the top-level API that works with glyexp::experiment() objects and supports the add_info parameter for joining experiment metadata.

gly_limma_() is the underlying API that works with matrices and factor vectors directly, providing more flexibility for users who don't use the glyexp package.

For two-group comparisons, a simple contrast is performed between the groups. For multi-group comparisons (3+ groups), all pairwise comparisons are automatically generated and performed using contrast matrices unless custom contrasts are specified.

When specifying custom contrasts, use either "group1-group2" or "group1_vs_group2" format. If group names contain hyphens and you use the first format, an error will be raised suggesting to use the second format.

Required packages

This function requires the following packages to be installed:

limma for linear model fitting and empirical Bayes moderation