This function performs pathway enrichment analysis for differentially expressed genes (DEGs), which are already categorized into different types (e.g., Dimorphic, Neutral, Sex-specific) via the `categorize_sex_sc` function. The function analyzes their enrichment in KEGG, GO, or Reactome pathways.
categorized_enrich_sc(
DEGs_category,
enrichment_db = "KEGG",
organism = "hsa",
org_db = org.Hs.eg.db,
pvalueCutoff = 0.05,
qvalueCutoff = 0.2
)A named list of enriched pathways for each DEG category, structured as a data frame.
Data frame containing gene symbols and their corresponding DEG types. Must include columns 'DEG_Type' (DEGs categories) and 'Gene_Symbols'.
Character string specifying the enrichment database to use: "KEGG", "GO", or "REACTOME" (default: "KEGG").
Character string representing the organism code. For KEGG enrichment, use "hsa" (default). For Reactome enrichment, use "human".
databse of the organism (e.g: Org.Hs.eg.db)
Numeric value specifying the p-value cutoff for statistical significance (default: 0.05).
Numeric value specifying the q-value cutoff for multiple testing correction (default: 0.2).
- The input DEGs are already categorized by the `categorize_sex_sc` function. - For GO enrichment, an appropriate OrgDb object (e.g., org.Hs.eg.db for humans) must be available. - For KEGG and Reactome enrichment, gene symbols are first converted to ENTREZ IDs. - Requires the 'clusterProfiler' package for enrichment analysis. - Ensures appropriate error handling for missing genes or database issues.