POMS

POMS integrates phylogenetic and functional data to identify microbial functions consistently enriched across independent taxonomic lineages.

Key Features:

• Phylogeny-Aware Frameworks: Implements multiple frameworks that account for phylogenetic relationships to distinguish explanations for variation in functional profiles.
• Extended Balance-Tree Workflow: Combines functional and taxonomic data using an extended balance-tree approach to identify functions enriched in sample groups across lineages.
• Phylogenetic Regression Analysis: Includes a workflow for phylogenetic regression to account for evolutionary relationships when assessing functional associations.
• Enhanced Accuracy (Simulation-Based): Demonstrates superior accuracy on simulated data for identifying gene families that confer selective advantages compared to commonly used tools.
• Application to Metagenomics: Applied to metagenomics datasets to identify enriched functions that are potential targets of selection across multiple microbiome members.

Scientific Applications:

• Gene Family Identification: Identifies gene families associated with selective advantages within microbial communities.
• Functional Trait Analysis: Analyzes metagenomics data to uncover functional traits linked to specific sample groups.
• Evolutionary Pressure Inference: Provides insights into evolutionary pressures acting on microbial community functions by integrating phylogeny and function.

Methodology:

POMS implements multiple phylogeny-aware frameworks, notably an extended balance-tree workflow that integrates taxonomic and functional data and a phylogenetic regression analysis, with performance evaluated on simulated data.