TMAT

TMAT tests associations between operational taxonomic units (OTUs) in microbiome data and host disease phenotypes by incorporating phylogenetic tree information into node-level statistical analyses.

Key Features:

• Phylogenetic Tree Utilization: Leverages phylogenetic trees to incorporate evolutionary relationships among OTUs and contrasts this approach with rank-based non-parametric tests such as the Mann-Whitney U-test and Wilcoxon rank-sum test.
• Efficient Association Analysis: Computes test statistics for each node in the phylogenetic tree to identify associations between OTU abundances and host diseases, retaining more information than rank-based approaches and reducing false negatives.
• Statistical Robustness: Simulation studies demonstrate preservation of the nominal type-1 error rate and generally higher statistical power than existing methods across evaluated scenarios.
• Detection of Phylogenetic Mutations: Detects phylogenetic mutations linked to host diseases to provide insights into bacterial pathology and potential disease mechanisms.

Scientific Applications:

• Metagenomics and microbial ecology: Applied to 16S rRNA amplicon sequencing metagenomics to study the role of human microbiota in health and disease.
• Disease association studies: Used in analyses of colorectal carcinoma and myalgic encephalomyelitis/chronic fatigue syndrome datasets, including European Nucleotide Archive project accessions PRJEB6070 and PRJEB13092.

Methodology:

Constructs a phylogenetic tree of OTUs, computes test statistics at each tree node, and combines node-level statistics to identify significant associations between OTU abundances and disease phenotypes while accounting for evolutionary context.