SURVIVAL AND EPIGENETIC AGE VISUALIZATION FOR DIAPAUSE DATA

SUMMARYThis script generates a publication-ready figure combining:1. A scatter plot of predicted epigenetic age vs. chronological age2. A Kaplan-Meier survival curve comparing control and post-diapause treatmentsBoth plots are combined side-by-side into a high-resolution PDF output suitable for publication.INPUT FILES- Epigenetic age predictions: glmnet_erin_only_uniCorrCpGs_predictions_data.csv- Lifespan data: Diapause.csvMAIN STEPS1. Load prediction and survival datasets2. Standardize factor levels (e.g., Treatment) and harmonize column names3. Apply a custom publication theme (based on Times New Roman)4. Create a scatter plot: chronological vs epigenetic age5. Perform survival analysis using Kaplan-Meier and Cox proportional hazards6. Combine both plots using patchwork and add panel labels7. Export the combined figure to PDFOUTPUT FILE- combined_figure_pnas_v5.pdf: 2-panel figure with survival and scatter plotsPLOT DETAILS- Colors: Control (black), Post-diapause (orange)- Scatter plot includes linear regression lines with confidence intervals- Survival plot includes shaded confidence ribbons and median survival lineSCRIPT FEATURES- Automatically detects and corrects column names (e.g., `pred_age` vs `pred_age_glmnet`)- Includes robust font handling via `showtext` (Times New Roman fallback supported)- Publication-style theme applied consistently across both plotsREQUIREMENTS- R packages: ggplot2, patchwork, survival, survminer, dplyr, data.table, showtext- Font: Times New Roman (must be installed on system)USAGE NOTES- Font embedding in PDF is handled via cairo_pdf for compatibility with journals- Ensure all input file paths are updated to your local system if running elsewhere- Script auto-generates panel tags (A, B) for figure panelsContact: Eamonn Mallon, [e-mail]