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
• data/ for raw and processed data
• scripts/ for analysis code
• results/ for outputs
• reports/ for R Markdown or Quarto reports

1. Set up environment
• Initialize .Rproj (if using RStudio)
• Create renv environment for reproducibility
• Install required CRAN/Bioconductor packages

1. Generate analysis scripts
• Data loading and cleaning
• Statistical analysis or modeling
• Visualization with ggplot2
• Save outputs (CSV, plots, model summaries)

1. Create a report
• R Markdown / Quarto document
• Includes methods, results, and figures
• 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