Meta-Prism 2.0: Enabling algorithm and web server for ultra-fast, memory-efficient, and accurate analysis among millions of microbial community samples

Author:

Kang Kai12ORCID,Chong Hui1ORCID,Ning Kang1ORCID

Affiliation:

1. Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology , Wuhan 430074, China

2. Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University , Beijing 100871, China

Abstract

Abstract Background Microbial community samples have been accumulating at a speed faster than ever, with hundreds of thousands of samples been sequenced each year. Mining such a huge amount of multisource heterogeneous data is becoming an increasingly difficult challenge, so efficient and accurate compare and search of samples is in urgent need: faced with millions of samples in the data repository, traditional sample comparison and search approaches fall short in speed and accuracy. Findings Here we proposed Meta-Prism 2.0, a microbial community sample analysis method that has pushed the time and memory efficiency to a new limit without compromising accuracy. Based on sparse data structure, time-saving instruction pipeline, and SIMD optimization, Meta-Prism 2.0 has enabled ultra-fast, memory-efficient, flexible, and accurate search among millions of samples. Meta-Prism 2.0 was put to test on several data sets, with the largest containing 1 million samples. Results show that Meta-Prism 2.0’s 0.00001-s per sample pair compare speed and 8-GB memory needs for searching against 1 million samples have made it one of the most efficient sample analysis methods. Additionally, Meta-Prism 2.0 can achieve accuracy comparable with or better than other contemporary methods. Third, Meta-Prism 2.0 can precisely identify the original biome for samples, thus enabling sample source tracking. Finally, we have provided a web server for fast search of microbial community samples online. Conclusions In summary, Meta-Prism 2.0 has changed the resource-intensive sample search scheme to an effective procedure, which could be conducted by researchers every day even on a laptop, for insightful sample search, similarity analysis, and knowledge discovery. Meta-Prism 2.0 can be accessed at https://github.com/HUST-NingKang-Lab/Meta-Prism-2.0, and the web server can be accessed at https://hust-ningkang-lab.github.io/Meta-Prism-2.0/.

Funder

National Natural Science Foundation of China

Publisher

Oxford University Press (OUP)

Subject

Computer Science Applications,Health Informatics

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