RabbitKSSD: accelerating genome distance estimation on modern multi-core architectures

SUMMARY: We propose RabbitKSSD, a high-speed genome distance estimation tool. Specifically, we leverage load-balanced task partitioning, fast I/O, efficient intermediate result accesses, and high-performance data structures to improve overall efficiency. Our performance evaluation demonstrates that...

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Detalles Bibliográficos
Autores principales: Xu, Xiaoming, Yin, Zekun, Yan, Lifeng, Yi, Huiguang, Wang, Hua, Schmidt, Bertil, Liu, Weiguo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Applications Note
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10681859/
https://www.ncbi.nlm.nih.gov/pubmed/37971961
http://dx.doi.org/10.1093/bioinformatics/btad695
Descripción
Sumario:SUMMARY: We propose RabbitKSSD, a high-speed genome distance estimation tool. Specifically, we leverage load-balanced task partitioning, fast I/O, efficient intermediate result accesses, and high-performance data structures to improve overall efficiency. Our performance evaluation demonstrates that RabbitKSSD achieves speedups ranging from 5.7× to 19.8× over Kssd for the time-consuming sketch generation and distance computation on commonly used workstations. In addition, it significantly outperforms Mash, BinDash, and Dashing2. Moreover, RabbitKSSD can efficiently perform all-vs-all distance computation for all RefSeq complete bacterial genomes (455 GB in FASTA format) in just 2 min on a 64-core workstation. AVAILABILITY AND IMPLEMENTATION: RabbitKSSD is available at https://github.com/RabbitBio/RabbitKSSD.

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