Run limma-based gene set analysis (camera/fry) — run_limma

This internal function implements limma's camera and fry methods for gene set enrichment analysis with support for covariates.

Usage

run_limma_gsea(
  abundance_mat,
  metadata,
  group,
  covariates = NULL,
  contrast = NULL,
  gene_sets,
  method = "camera",
  inter.gene.cor = 0.01,
  min_size = 5,
  max_size = 500,
  p.adjust.method = "BH",
  transformation = c("voom", "logCPM")
)

Arguments

abundance_mat: A matrix of abundance data with features as rows and samples as columns
metadata: A data frame containing sample metadata
group: A character string specifying the grouping variable column name
covariates: A character vector of covariate column names (optional)
contrast: Contrast specification for camera/fry. See pathway_gsea for the public contract.
gene_sets: A named list of gene sets (pathway -> gene IDs)
method: Either "camera" or "fry"
inter.gene.cor: Inter-gene correlation for camera (default 0.01)
min_size: Minimum gene set size
max_size: Maximum gene set size
p.adjust.method: P-value adjustment method
transformation: Either "voom" or "logCPM"; see pathway_gsea.

Value

A data frame containing gene set analysis results