Function inference of million-scale microbiomes using multi-GPU acceleration.

ABSTRACT: Amplicon sequencing enables taxonomic profiling of microbial communities but offers limited insight into their functional potential. Existing tools such as Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2) infer functions through phylogenetic placement and ancestral state reconstruction; however, these methods are computationally intensive and inefficient for large-scale data sets. To address these challenges, we introduce microbiome graphics processing unit (GPU)-based function inference (MGFunc), an ultra-high-throughput framework for microbiome functional inference leveraging multi-GPU acceleration. MGFunc transforms functional prediction for amplicons into standardized matrix multiplication using a pre-constructed genomic content network. It fu

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC12671092 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature