Creating R Research Projects

This skill helps create and manage a complete R-based research analysis workflow. It is designed for scientific computing, statistical modeling, bioinformatics, and data visualization tasks.

Use this skill when the user wants to: - Analyze datasets using R - Perform statistical tests or modeling - Run bioinformatics or omics analysis in R - Generate plots, figures, or reports - Create a reproducible R project structure - Install and manage R package dependencies

What This Skill Does

When activated, this skill will:

1. Create a structured R project
2. data/ for raw and processed data
3. scripts/ for analysis code
4. results/ for outputs

5. reports/ for R Markdown or Quarto reports

6. Set up environment

7. Initialize .Rproj (if using RStudio)
8. Create renv environment for reproducibility

9. Install required CRAN/Bioconductor packages

10. Generate analysis scripts

11. Data loading and cleaning
12. Statistical analysis or modeling
13. Visualization with ggplot2

14. Save outputs (CSV, plots, model summaries)

15. Create a report

16. R Markdown / Quarto document
17. Includes methods, results, and figures
18. Render to HTML or PDF

Example User Requests That Should Trigger This Skill

• "Use R to analyze this CSV and generate plots"
• "Run differential expression analysis in R"
• "Create a statistical report for this dataset"
• "Build an R project for microbiome analysis"
• "Fit a regression model in R and summarize results"

Example Workflow

User: Analyze this gene expression dataset and produce figures.

Skill actions: - Create project structure - Install tidyverse, DESeq2, ggplot2 - Write analysis script - Generate PCA plot and volcano plot - Produce an HTML report

Tools & Packages Commonly Used

Notes

• Prefer reproducible workflows (renv, scripted analysis)
• Avoid interactive-only steps unless requested
• All outputs should be saved to files, not just printed to console