GUniFrac

GUniFrac computes generalized UniFrac distances to quantify phylogenetic beta-diversity and detect compositional shifts across rare, moderately abundant, and dominant microbial lineages in microbiome studies.

Key Features:

• Generalized UniFrac Distances: Extends unweighted and weighted UniFrac to capture a broader spectrum of biologically relevant changes across rare, moderately abundant, and highly abundant lineages.
• Enhanced Statistical Power: Uses Monte Carlo simulations to demonstrate superior power in detecting changes in microbial abundance compared with traditional UniFrac measures.
• Application to Real-World Data: Validated on microbiome datasets to associate human microbiome composition with environmental factors such as diet and smoking.

Scientific Applications:

• Human microbiome association studies: Detects associations between human microbiome composition and environmental covariates such as diet and smoking.
• Microbiome compositional analysis for health and disease: Supports investigation of the human microbiome's role in health and disease and of factors that influence microbiome dynamics, informing potential therapeutic interventions.

Methodology:

Calculation of generalized UniFrac distances and use of Monte Carlo simulations to assess statistical power and balance sensitivity across rare, moderate, and abundant lineages.