PopPAINTER: Interactive Shiny Apps for Population Genomics

By Pavel Salazar-Fernandez (epsalazarf@gmail.com)

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.

Requirements

• R (≥ 4.0)

• RStudio (recommended)

• Packages: shiny, shinyjs, ggplot2, dplyr, plotly, and others (listed in each app’s DESCRIPTION).

• 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.

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.

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:

  • POP_SIMPLE — human-readable population name.

  • REGION — grouping of populations for broader categories.

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 file.

• First row contains column headers.

• One sample per line.

Running an App

From RStudio:

1. Open the app.R file in the relevant app directory (PopCanvas or PopMosaic).

2. Click Run App.

From R console:

shiny::runApp("path/to/PopCanvas")

Repository Structure

PopPAINTER/
├── PopCanvas/      # PCA visualizer app
├── PopMosaic/      # ADMIXTURE visualizer app
├── common/         # Shared code, themes, data
├── README.md
└── .gitignore

• main branch — beta releases for internal use.

• dev branch — active development and new features.

License

This software is completely free to use, but credits to this repo is very well appreciated.