DAG Builder

A browser-based causal diagram (DAG) editor that exports dagitty R code. No installation required for end users — just open in a browser.

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Quickstart (run locally)

Requirements: Node.js ≥ 18 — download from https://nodejs.org

# 1. Go into the project folder
cd dag-builder

# 2. Install dependencies (one time only)
npm install

# 3. Start the app
npm run dev

Then open http://localhost:5173 in your browser. Done.

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Build for sharing (optional)

To create a standalone folder you can host anywhere:

npm run build

This creates a dist/ folder. You can:

• Drag dist/ to Netlify Drop (netlify.com/drop) → get a public URL instantly
• Push to GitHub and enable GitHub Pages pointing to dist/
• ZIP and send to a colleague — they open dist/index.html directly

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Project structure

dag-builder/
├── index.html          # HTML entry point
├── package.json        # Dependencies
├── vite.config.js      # Build config
└── src/
    ├── main.jsx        # React root
    └── App.jsx         # Full application

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Features

• Edge-by-edge DAG construction (From → To with role assignment)
• 9 variable roles: Exposure, Outcome, Confounder, Mediator, Collider, Unmeasured, Proxy of unmeasured, Effect modifier, Selection bias
• Live DAG rendering with force-directed layout
• Structural validation warnings (e.g. Outcome → Exposure flagged)
• Effect modifiers shown in footnote (not as structural edges)
• Unmeasured nodes rendered with dashed borders
• R code export (dagitty + ggdag ready to paste)
• SVG download

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Citation

If used in a manuscript:

• Raj Subedi. (2026). rajsubediresearch/dag-builder: DAG Builder v1.0.0 (v1.0.0). Zenodo. https://doi.org/10.5281/zenodo.20058009
• Textor J et al. (2016). Robust causal inference using directed acyclic graphs: the R package 'dagitty'. Int J Epidemiol. 45(6):1887–1894.