micropower

micropower estimates statistical power for PERMANOVA analyses of microbiome beta diversity by simulating pairwise distance matrices.

Key Features:

• Pairwise Distance Simulation: Simulates distance matrices that model within-group pairwise distances according to specified population parameters while enforcing the triangle inequality and incorporating group-level effects quantified by omega-squared (ω²).
• Effect Size Incorporation: Integrates varying effect sizes into simulated distance matrices to model different magnitudes of exposure or intervention impacts on community composition.
• Simulation-Based Power Estimation: Estimates PERMANOVA statistical power via simulation of distance matrices and permutation-based testing to determine available power or required sample size.
• R Implementation: Provides the framework as an R statistical software package for executing the simulations and power estimations.

Scientific Applications:

• Marker-gene microbiome studies: Assess impacts of exposures or interventions on microbial community composition (beta diversity) using PERMANOVA on simulated distance matrices.
• Study design and sample size estimation: Determine required sample sizes or achievable power for planned microbiome experiments through simulation-based PERMANOVA power analysis.

Methodology:

Simulate pairwise distance matrices that adhere to specified population parameters and the triangle inequality while incorporating group-level effects quantified by omega-squared (ω²) and varying effect sizes; estimate statistical power by applying permutation-based PERMANOVA to the simulated distance matrices.