ARGscape: A modular, interactive tool for manipulation of spatiotemporal ancestral recombination graphs

Area of Science:

• Population Genetics
• Computational Biology
• Bioinformatics

Background:

• Ancestral Recombination Graphs (ARGs) and tree sequences are crucial for understanding population history.
• Visualizing ARGs, especially in a geographic context, is challenging due to a lack of interactive tools.
• Existing methods for ARG analysis are often fragmented across different platforms.

Purpose of the Study:

• To introduce ARGscape, an interactive platform for simulating, analyzing, and visualizing ARGs in spatiotemporal contexts.
• To provide dynamic 2D and 3D visualizations for exploring ARG data.
• To integrate various command-line, Python, and R-based ARG tools into a unified framework.

Main Methods:

• Development of ARGscape with a Python FastAPI backend and React/TypeScript frontend.
• Implementation of dynamic 2D and 3D visualization capabilities.
• Integration of ARG simulation, manipulation, and spatiotemporal inference tools.

Main Results:

• ARGscape offers a user-friendly graphical interface for exploring ARGs across space and time.
• A novel 'spatial diff' visualization is included for quantitative comparison of geographic inference methods.
• The platform seamlessly integrates diverse ARG analysis tools, facilitating data exploration.

Conclusions:

• ARGscape lowers the barrier to entry for spatiotemporal ARG analysis in research and education.
• The platform supports novel data exploration and hypothesis generation in population genetics.
• ARGscape provides a unified framework for interactive visualization and analysis of ARGs.