miaSim

miaSim simulates microbiome time series dynamics using ecological models including the generalized Lotka-Volterra model, Self-Organized Instability (SOI), stochastic logistic model, MacArthur's consumer-resource model, and Hubbell's neutral model, with outputs formatted for (Tree)SummarizedExperiment objects.

Key Features:

• Multiple ecological models: Implements four core models (stochastic logistic model, MacArthur's consumer-resource model, Hubbell's neutral model, and generalized Lotka-Volterra model) with several derivations.
• Unified data structures: Diverse model implementations share the same data structures and state variables to facilitate cross-model combinations and comparisons.
• miaverse compatibility: Fully compatible with the miaverse R/Bioconductor framework for microbiome data science.
• Abundance matrix generation: Hubbell's Neutral model determines the abundance matrix, which is applied to (Tree)SummarizedExperiment objects.

Scientific Applications:

• Microbiome dynamics simulation: Simulates microbial community dynamics under varied assumptions and scenarios to explain how, why and when specific microbiome states are reached.
• Cross-model comparison: Enables combination and comparison of different ecological models and testing of diverse model assumptions.
• Integration with experimental data: Allows combination and comparison of model simulations with microbiome datasets within the miaverse framework.

Methodology:

miaSim implements mathematical models of microbiome dynamics including the generalized Lotka-Volterra model, Self-Organized Instability (SOI), stochastic logistic model, MacArthur's consumer-resource model, and Hubbell's neutral model; the resulting abundance matrices are applied to (Tree)SummarizedExperiment objects.