BiomeHorizon: Visualizing Microbiome Time Series Data in R

Area of Science:

• Microbiology
• Bioinformatics
• Data Visualization

Background:

• Host-associated microbial communities significantly impact host health and exhibit substantial temporal variation.
• Visualizing the dynamics of thousands of taxa in longitudinal microbiome data presents a significant challenge.
• Existing methods struggle to effectively display both proportional and absolute changes in microbial abundance over time across multiple subjects.

Purpose of the Study:

• To develop an automated, open-source R package for visualizing longitudinal compositional microbiome data.
• To address the need for a method that can visualize changes in multiple taxa across multiple subjects over time.
• To provide a flexible and user-friendly tool for microbiome time series data analysis.

Main Methods:

• Developed BiomeHorizon, an R package utilizing horizon plots for microbiome data visualization.
• The package is designed to handle various data formats and accommodate different study designs (e.g., human health, wildlife).
• Provides automated visualization of proportional and absolute changes in microbial relative abundance.

Main Results:

• BiomeHorizon offers the first automated R package for visualizing longitudinal microbiome data using horizon plots.
• The package facilitates the visualization of temporal dynamics in microbial communities.
• It supports both regularly and irregularly sampled time series data.

Conclusions:

• BiomeHorizon provides a novel and effective approach to visualizing complex longitudinal microbiome data.
• The tool enhances the ability to link microbial community shifts with host health outcomes.
• This package offers a user-friendly solution for researchers studying microbiome dynamics.