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running-r-analysis-in-existing-projects

// Work inside an existing R project to extend analyses, modify scripts, run statistical models, update visualizations, and regenerate reports.

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stars:1,933
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updated:March 4, 2026
SKILL.mdreadonly
SKILL.md Frontmatter
namerunning-r-analysis-in-existing-projects
descriptionWork inside an existing R project to extend analyses, modify scripts, run statistical models, update visualizations, and regenerate reports.

Running R Analysis in Existing Projects

This skill operates inside an already structured R project. It helps extend, debug, or enhance existing analyses without recreating the project from scratch.

Use this skill when the user wants to:

  • Continue analysis in an existing R project
  • Modify or extend R scripts
  • Add new statistical models or tests
  • Update plots or figures
  • Regenerate reports after data or code changes
  • Debug R errors in a project

What This Skill Does

When activated, this skill will:

  1. Understand the project structure

    • Detect folders like data/, scripts/, results/, reports/
    • Identify .Rproj, .Rmd, .qmd, or .R files
  2. Inspect existing analysis

    • Read current scripts and reports
    • Identify which packages and methods are being used
    • Avoid rewriting working components unnecessarily
  3. Extend or modify analysis

    • Add new models or statistical tests
    • Introduce new plots using ggplot2
    • Add new data processing steps
    • Improve code structure or reproducibility
  4. Re-run and update outputs

    • Recompute results
    • Overwrite or version new outputs in results/
    • Re-render R Markdown or Quarto reports
  5. Debug issues

    • Fix missing packages
    • Resolve file path problems
    • Handle common R errors and warnings

Example User Requests That Should Trigger This Skill

  • "Add a survival analysis to this R project"
  • "Update the plots in my report"
  • "This R Markdown file throws an error, fix it"
  • "Extend this analysis with a mixed-effects model"
  • "Re-run everything after I updated the data"

Example Workflow

User: Add a logistic regression model and update the report.

Skill actions:

  • Locate main analysis script
  • Add logistic regression using glm()
  • Save model summary to results/
  • Update report with new section and plot
  • Re-render HTML/PDF report

Tools & Packages Commonly Used

PurposeR Packages
Data wranglingtidyverse, dplyr
Modelingstats, lme4, glmnet
Visualizationggplot2
Reportingrmarkdown, quarto
Project managementhere, renv

Notes

  • Respect the existing project structure and style
  • Do not delete user code unless explicitly requested
  • Prefer incremental updates over full rewrites
  • Always regenerate reports after modifying analysis