eudysbiome

eudysbiome annotates and classifies differential genera in mammalian microbiomes, particularly in the gut-intestinal (GI) ecosystem, to assess their potential contribution to host diseases and categorize them as harmful, harmless, or unknown.

Key Features:

• Annotation of Genera: Automatically annotates pathogenic and non-pathogenic genera within the microbiome to distinguish harmful, harmless, or unknown taxa.
• Quantitative Assessment: Quantitatively evaluates the net variation in frequency of harmless versus harmful organisms to determine eubiotic or dysbiotic impacts.
• Global Composition Analysis: Evaluates the global composition of the microbiome rather than focusing solely on metrics such as α-diversity or the Firmicutes to Bacteroides ratio.
• Integration with Existing Approaches: Complements and integrates with existing metagenomic analyses to provide systemic-level interpretation of microbial composition changes.
• Application in Clinical Research: Applied to human GI-microbiome data to characterize physiological effects of treatments such as Prednisone and Methotrexate for rheumatoid arthritis (RA).
• Computational Efficiency: Implements computationally efficient procedures to address challenges from incomplete species functional knowledge when analyzing large datasets.

Scientific Applications:

• Disease Progression Studies: Quantifies shifts in harmful versus harmless taxa to study microbiome-associated disease progression.
• Therapy Impact Assessment: Assesses long-term effects of therapies on the GI microbiome, including responses to Prednisone and Methotrexate in RA.
• Clinical Interpretation: Provides quantitative evidence to inform clinical decision-making and therapeutic development based on microbial composition changes.

Methodology:

Automatic annotation of genera, quantitative evaluation of net frequency variation between harmless and harmful organisms, global composition analysis, and integration with metagenomic analyses.