A0223
Title: mPower: A real data-based power analysis tool for microbiome study design
Authors: Jun Chen - Mayo Clinic (United States) [presenting]
Abstract: Power analysis is a critical step in designing a microbiome study. Previous power calculation tools mainly rely on parametric models, which underestimate the complexity of microbiome data and could produce overly optimistic power estimates. A simulation-based power analysis tool, mPower, is presented to facilitate realistic power calculation for microbiome studies. The tool uses a real data-based semi-parametric simulation framework to generate realistic microbiome data, upon which the power assessment is performed. Coupled with the recently developed differential analysis tool, LinDA, the power tool supports different study designs, including cross-sectional, case-control, and longitudinal studies, with or without confounders. It allows power analysis for both community-level and taxa-level testing. By using a database of large microbiome datasets from different environments, the users could perform power calculations based on the environment of interest. The application of the power analysis tool is showcased using several real examples.
