Coordinated Meta-Storms enables comparison of million-level microbiomes

Area of Science:

• Microbiome research
• Computational biology
• Bioinformatics

Background:

• Phylogeny-based distance is crucial for microbiome beta diversity analysis.
• Increasing data volumes present significant computational challenges.
• Current methods lack scalability and efficiency for large datasets.

Purpose of the Study:

• To address computational limitations in large-scale microbiome data analysis.
• To introduce a scalable and efficient method for phylogeny-based distance calculation.
• To enable rapid pairwise comparison of millions of microbiomes.

Main Methods:

• Development of Coordinated Meta-Storms (CMS), a novel computational approach.
• Implementation utilizing a dynamic multiple Graphics Processing Unit (GPU) architecture.
• Application of a self-adaptive data decomposition and optimization strategy.

Main Results:

• CMS enables large-scale microbiome phylogeny-based distance calculation.
• Pairwise comparison of million-level microbiomes achieved within 40 hours on a single node.
• Demonstrates significant improvements in scalability and efficiency over existing methods.

Conclusions:

• Coordinated Meta-Storms (CMS) effectively overcomes computational bottlenecks in microbiome analysis.
• The method facilitates large-scale, high-throughput microbiome comparisons.
• CMS represents a significant advancement for microbiome research and bioinformatics.