Meta-Storms

Meta-Storms computes quantitative phylogenetic similarity metrics between microbial community samples to enable large-scale comparative metagenomic analyses.

Key Features:

• GPU Optimization: Uses GPU (Graphics Processing Unit) acceleration via CUDA (Compute Unified Device Architecture) to accelerate computations on large metagenomic datasets.
• Quantitative Phylogenetic Similarity Measurement: Computes quantitative phylogenetic similarity among microbial community samples.
• High-Speed Performance: Achieves over 17,000× speed-up versus single-core CPU and over 2,600× versus 16-core CPU, enabling pairwise similarity computation for up to 10,240 samples within approximately 20 minutes.
• Real-Time Analysis and Monitoring: Enables near real-time analysis and monitoring of temporal or conditional changes in microbial communities through high-performance computation.
• Implementation: Implemented in C++ with CUDA for GPU-accelerated computation.

Scientific Applications:

• Environmental Monitoring: Facilitates analysis of microbial community dynamics in environmental monitoring studies.
• Disease Microbiome Profiling: Enables large-scale comparative profiling of disease-associated microbiomes.
• Biotechnology and Microbial Consortia Analysis: Supports analysis and comparison of microbial consortia in biotechnological applications.
• Microbial Ecology and Evolution Studies: Supports discovery of ecological and evolutionary patterns across extensive metagenomic datasets.
• High-Throughput Data Mining: Enables mining of large metagenomic datasets to identify novel biological patterns and relationships.

Methodology:

Implemented in C++ and CUDA to compute quantitative phylogenetic similarity and pairwise similarity scores on GPUs.