Skip to contents

Categorize Differential Expression Results (DESeq2 or edgeR)

dot-categorize_deg_results.Rd

This function classifies genes as "Up", "Down", or "Other" based on fold-change and p-value thresholds. It supports input from DESeq2 (DESeqResults), edgeR (e.g., topTags()), or a general tibble/data frame.

Usage

.categorize_deg_results(
  de_results,
  log2fc_cutoff = 1,
  pval_cutoff = 0.05,
  p_value_type = c("padj", "pvalue", "FDR", "PValue")
)

Arguments

de_results

A differential expression results object. Can be a DESeqResults object, an edgeR topTags() table, or a data frame/tibble containing fold changes and p-values.

log2fc_cutoff

Numeric; minimum absolute log2 fold change to classify a DEG. Default is 1.

pval_cutoff

Numeric; p-value or FDR threshold to define significance. Default is 0.05.

p_value_type

String; which column to use for filtering significance. One of "padj", "pvalue", "FDR", "PValue". Default is "padj".

Value

A tibble with gene IDs, fold changes, p-values, and a new regulation column, indicating the category of each gene:

  • "Up": Genes with log2 fold change >= log2fc_cutoff and p-value <= pval_cutoff.

  • "Down": Genes with log2 fold change <= -log2fc_cutoff and p-value <= pval_cutoff.

  • "Other": Genes not meeting the above criteria.