q2-longitudinal: Longitudinal and Paired-Sample Analyses of Microbiome Data

Area of Science:

• Microbiology
• Bioinformatics
• Computational Biology

Background:

• Longitudinal sampling in microbiome studies reveals temporal dynamics and heterogeneity.
• Traditional cross-sectional or pre-post designs offer limited insights compared to longitudinal approaches.
• Microbiome research increasingly requires robust tools for analyzing time-series data.

Purpose of the Study:

• To introduce q2-longitudinal, a novel software plugin for QIIME 2.
• To provide microbiome researchers with advanced analytical capabilities for longitudinal and paired-sample data.
• To enhance the accessibility of longitudinal microbiome data analysis.

Main Methods:

• Development of the q2-longitudinal plugin for the QIIME 2 platform.
• Integration of interactive plotting, linear mixed-effects models, and paired analyses.
• Inclusion of microbial interdependence testing, first differencing, feature selection, and volatility analyses.

Main Results:

• The q2-longitudinal plugin offers a comprehensive suite of tools for longitudinal microbiome analysis.
• The plugin facilitates the exploration of temporal trends and subject heterogeneity in microbiome data.
• Open-source availability under a BSD license ensures broad accessibility for research and commercial use.

Conclusions:

• q2-longitudinal significantly enhances the analytical capacity for longitudinal microbiome studies within the QIIME 2 ecosystem.
• The plugin democratizes advanced statistical and visualization techniques for time-series microbiome data.
• This tool will empower researchers to gain deeper insights into dynamic microbial communities.