PopPAINTER: Interactive Shiny Apps for Population Genomics

PopPAINTER is a suite of R Shiny applications for interactive visualization and exploration of population genomics data. Currently included:

• PopCanvas — PCA visualizer (inspired by Pollock's vibrant chaos).
• PopMosaic — ADMIXTURE plotter (inspired by Mondrian's orderly grids).

Additional visualization tools (e.g., a Circos-style genomic relationship plot) are planned for future versions.

About

PopPAINTER apps allow users to:

• Render and explore PCA and ADMIXTURE results interactively.
• Modify colors, labels, and subset selections without editing source code.
• Export publication-quality figures (PDF/PNG).

They are intended for research workflows where quick, high-quality data visualization is needed — particularly for human population genomics.

Which Version Should I Use?

Each app is developed in two parallel tracks:

	v1.x (recommended)	v2.0 (preview)
Branch	main	dev
Engine	Base R shiny + ggplot2	plotly + sidebar dashboard layout
Status	Stable, tested	Actively in development
Footprint	Lightweight, fast to launch	Heavier, more dependencies
Online demo	✅ Live on shinyapps.io	⏳ Not yet deployed

For most users, the v1.x apps on main are recommended — they are the most stable and lightweight versions, and are the only ones currently available as hosted online demos (see links below).

The v2.0 apps (PopCanvas-app-v2.0.R, PopMosaic-app-v2.0.R, on the dev branch) introduce a richer, interactive Plotly-based interface with additional features, but are still under active development and may be incomplete or unstable. Try them if you want a preview of upcoming functionality, or want to contribute feedback.

Requirements

• R (≥ 4.0)
• RStudio (recommended)
• Packages: shiny, shinyjs, tidyverse, scales, RColorBrewer, pheatmap, colourpicker (full per-app lists in each app's DESCRIPTION and README).
• Input files depend on the app (see below).

PopCanvas (PCA Viewer)

Purpose: Explore principal component analysis results with dynamic subsetting and coloring.

Required files:

• .eval and .evec files (from smartpca or similar), one of each per dataset.
• popinfo file (see About the popinfo file below).

Features:

• Point/tag view modes.
• Subset and highlight populations.
• Color by region, population, or custom categories.
• Interactive zoom and panning.

Output:

• Export plots to high-quality PNG or PDF.

Online version (v1.4): https://epsalazarf.shinyapps.io/PopCanvas/

Docs: App README · Quick Start Guide

PopMosaic (ADMIXTURE Plotter)

Purpose: Display and customize ADMIXTURE results across multiple K values.

Required files:

• .Q files from ADMIXTURE (all K values for the same dataset).
• popinfo file.

Features:

• Switch between K values dynamically.
• Subset and sort samples by population or ancestry proportion.
• Recolor components interactively.
• Add population labels or collapse to group bars.

Output:

• Export plots to PNG or PDF.

Online version (v1.43): https://epsalazarf.shinyapps.io/PopMosaic/

Docs: App README · Quick Start Guide

Usage

Running an App

From RStudio:

1. Open the app file in the relevant directory — PopCanvas/PopCanvas-app.R or PopMosaic/PopMosaic-app.R.
2. Click Run App on the top right corner of the code window.
3. Upload your data, or click Load Demo Data to try the app with a built-in 1000 Genomes example.

From R console:

shiny::runApp("PopCanvas/PopCanvas-app.R")   # or PopMosaic/PopMosaic-app.R

Online versions:

Open the URL indicated above for each app — no installation required.

Quick Start Guides

Each app includes a short slide-style guide (built with Marp) covering setup, inputs, and key controls:

• PopCanvas-guide.md
• PopMosaic-guide.md

These render as readable Markdown on GitHub, or as a slide deck via the Marp CLI/VS Code extension, or an online converter such as marp.vercel.app.

Repository Structure

PopPAINTER/
├── PopCanvas/      # PCA visualizer app (v1.x on main, v2.0 preview on dev)
├── PopMosaic/      # ADMIXTURE visualizer app (v1.x on main, v2.0 preview on dev)
├── README.md
└── .gitignore

• main branch — stable releases for public use.
• dev branch — internal experimental development with new features (v2.0 apps).

About the popinfo file

A popinfo file links sample IDs to population and metadata categories.

• Required columns:
  • ID — unique sample names.
  • POP — population code.
• Recommended columns:
  • POPULATION — human-readable population name.
  • META — grouping of populations for broader categories, typically linguistic, ethnic, or subcontinental groupings.
  • SUPER — grouping into very broad categories, typically continental-level.

Recommended columns are optional, but when present PopPAINTER apps expect them to follow a loose hierarchy: ID → POP → META → SUPER, from most to least granular. PopPAINTER apps rely on popinfo for added functions like grouping, coloring, and filtering. Ensure the file matches your dataset and contains only relevant samples.

Format:

• Tab- or space-delimited TXT/TSV file.
• First row contains column headers.
• One sample per line.

License

This software is free to use and modify under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

Citation

If you use PopPAINTER in your work, please cite:

Salazar-Fernandez, E. P. (2026). PopPAINTER: Population genomics visualization suite [Computer software]. DOI: https://doi.org/10.5281/zenodo.20724143

This DOI always resolves to the latest version. See the Zenodo record for version-specific citations.

Disclaimers

1000 Genomes Project

Population metadata, PCA and ADMIXTURE results for the demo were derived from the 1000 Genomes Project dataset (Phase 3):

A global reference for human genetic variation, The 1000 Genomes Project Consortium, Nature 526, 68-74 (01 October 2015) doi:10.1038/nature15393

Generative AI Disclaimer

• Release apps version 1.3+ used Claude Code (Sonnet 5) for minor bug fixes and modifications for online upload to shinyapps.io.
• Development apps version 2.0+ used Claude Code (Sonnet 5) for the major rework and re-implementation in R::Dashboard and R::Plotly engines.
• Quickguides and extra documentation were written by Claude Sonnet 5.

Contact

For issues, suggestions, or contributions, feel free to reach out at epsalazarf@gmail.com.