TAMA

TAMA integrates outputs from three distinct taxonomy classification tools to assign taxonomy to metagenome reads and produce more consistent taxonomic classifications and relative species abundance estimates.

Key Features:

• Integration of Multiple Taxonomy Tools: Combines outputs from three distinct taxonomy classification tools to leverage complementary assignments.
• Meta-Score System: Computes a meta-score using an integrated reference database that integrates taxonomy assignments from the different tools to assign taxonomy to reads.
• Inter-tool Variability Resolution: Addresses variability in taxonomy analysis outputs across different classifiers through a meta-analysis approach.
• Relative Abundance Estimation: Predicts relative species abundance profiles and differences in microbial composition across samples.
• Benchmark Performance: Evaluations on benchmark datasets demonstrated improved precision and reliability in taxonomic classification compared with existing tools.

Scientific Applications:

• Environmental microbiology: Refines taxonomic assignments and abundance estimates for environmental metagenome studies.
• Food science (cheese metagenomics): Applied to cheese metagenomics to predict microbial composition and relative species abundance.
• Human gut microbiome studies: Applied to human gut samples to profile microbial composition and estimate species-level abundance.

Methodology:

Combines outputs from three taxonomy classification tools, computes a meta-score integrating those assignments using an integrated reference database to assign taxonomy to metagenome reads, and evaluates results using benchmark datasets.