TAILIEUCHUNG - Taxonomic assignment for large scale metagenomic data on high perfomance systems

This study proposes a parallel algorithm for the taxonomic assignment problem, called SeMetaPL, which aims to deal with the computational challenge. The proposed algorithm is evaluated with both simulated and real datasets on a high performance computing system. Experimental results demonstrate that the algorithm is able to achieve good performance and utilize resources of the system efficiently | Journal of Computer Science and Cybernetics, , (2017), 119–130 DOI TAXONOMIC ASSIGNMENT FOR LARGE-SCALE METAGENOMIC DATA ON HIGH-PERFOMANCE SYSTEMS LE VAN VINH1 , TRAN VAN HOAI2 , DUONG NGOC HIEU2 , BUI XUAN GIANG2 , TRAN VAN LANG3,4 1 Faculty of Information Technology, HCMC University of Technology and Education of Computer Science and Engineering, Bach Khoa University 3 Institute of Applied Mechanics and Informatics, VAST 4 Lac Hong University vinhlv@ 2 Faculty Abstract. Metagenomics is a powerful approach to study environment samples which do not require the isolation and cultivation of individual organisms. One of the essential tasks in a metagenomic project is to identify the origin of reads, referred to as taxonomic assignment. Due to the fact that each metagenomic project has to analyze large-scale datasets, the metatenomic assignment is computationally intensive. This study proposes a parallel algorithm for the taxonomic assignment problem, called SeMetaPL, which aims to deal with the computational challenge. The proposed algorithm is evaluated with both simulated and real datasets on a high performance computing system. Experimental results demonstrate that the algorithm is able to achieve good performance and utilize resources of the system efficiently. The software implementing the algorithm and all test datasets can be downloaded at . Keywords. DNA sequences, homology search, metagenomics, parallel algorithm, taxonomic assignment 1. INTRODUCTION Metagenomics is the study of the genomic content derived directly from complex microbial environment, instead of from culture in laboratories. The discipline offers opportunities to discover microbial communities, and thus brings benefits in many fields, ., biotechnology, agriculture, earth sciences [5]. Earlier metagenomic projects usually take many costs to get genomic information directly

• Cơ sở dữ liệu
• Journal of Computer Science and Cybernetics
• Taxonomic assignment for large scale metagenomic data
• High perfomance systems
• Large scale metagenomic data
• Achieve good performance
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