GO ENRICHMENT ANALYSIS OF CLOCK GENES USING DIFFERENTIALLY METHYLATED BACKGROUND

SUMMARYThis script performs Gene Ontology (GO) enrichment analysis on a set of clock-related CpGs in Nasonia vitripennis, using a background of differentially methylated genes. It identifies over-represented GO terms, applies FDR correction, and visualizes significant terms using semantic similarity metrics.ORIGINAdapted from code by Alun Jones (see Bebane et al., 2019).KEY STEPS1. Load GO annotations for the background gene set (differentially methylated genes).2. Create GOFrame and GeneSetCollection objects compatible with GOstats.3. Load a user-defined list of clock genes.4. Filter gene list to those with GO annotations.5. Run a hypergeometric test for enrichment across BP, CC, and MF ontologies.6. Apply FDR correction (Benjamini-Hochberg).7. Visualize enriched Biological Process terms using: - Treemap - Scatter plot - Heatmap - Word cloudINPUT FILES- diff_backgroundGOannotations.csv (GO annotations for differentially methylated genes)- clock_genes.csv (list of clock-related CpGs)OUTPUT FILES- `supplementary_tables_pnas.xlsx` → Sheet: Table_S4_GOterms (FDR-filtered GO terms)- `diff_erin_methylated_clock_genes_GO_treemap.png` → Treemap of reduced GO termsSOFTWARE REQUIREMENTS- R packages: GOstats, GSEABase, treemap, readr, dplyr, rrvgo, openxlsx, org.Dm.eg.dbNOTES- Uses Drosophila GO database for semantic similarity.- Focuses on over-representation in the Biological Process ontology.CITATIONBebane, P. et al. (2019). "Neonics and bumblebees." [Insert DOI]CONTACTEamonn [e-mail]