bebi 21(1): e3

Research Article

Parallel Implementation of String-Based Clustering for HT-SELEX Data

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  • @ARTICLE{10.4108/eai.19-10-2020.166664,
        author={Shintaro Kato and Takayoshi Ono and Masaki Ito and Koichi Ito and Hirotaka Minagawa and Katsunori Horii and Ikuo Shiratori and Iwao Waga and Takafumi Aoki},
        title={Parallel Implementation of String-Based Clustering for HT-SELEX Data},
        journal={EAI Endorsed Transactions on Bioengineering and Bioinformatics},
        volume={1},
        number={1},
        publisher={EAI},
        journal_a={BEBI},
        year={2020},
        month={10},
        keywords={sequence analysis, clustering, SELEX, next-generation sequencing, aptamer, parallel implementation},
        doi={10.4108/eai.19-10-2020.166664}
    }
    
  • Shintaro Kato
    Takayoshi Ono
    Masaki Ito
    Koichi Ito
    Hirotaka Minagawa
    Katsunori Horii
    Ikuo Shiratori
    Iwao Waga
    Takafumi Aoki
    Year: 2020
    Parallel Implementation of String-Based Clustering for HT-SELEX Data
    BEBI
    EAI
    DOI: 10.4108/eai.19-10-2020.166664
Shintaro Kato1,2,*, Takayoshi Ono2, Masaki Ito2, Koichi Ito2, Hirotaka Minagawa1, Katsunori Horii1, Ikuo Shiratori1, Iwao Waga1, Takafumi Aoki2
  • 1: NEC Solution Innovators, Ltd.1-18-7, Shinkiba, Koto-ku, Tokyo, 136-8627, Japan
  • 2: Graduate School of Information Sciences, Tohoku University,6-6-05, Aramaki Aza Aoba, Aoba-ku, Sendai-shi, Miyagi, 980-8579, Japan
*Contact email: katou-s-mxn@nec.com

Abstract

INTRODUCTION: A clustering method for HT-SELEX is crucial for selecting different types of aptamer candidates. We have developed FSBC method for HT-SELEX data implemented in R. FSBC exhibited the highest accuracy of sequence clustering compared with conventional methods, while the processing time of FSBC is longer than AptaCluster.

OBJECTIVES: The objective of this study is to improve the processing time of FSBC.

METHODS: We propose pFSBC, which reduces the processing time of ORS estimation in FSBC by introducing parallel implementation.

RESULTS: The processing time and clustering accuracy were evaluated with the last round of NCBI SRA data of SRR3279661 from BioProject PRJNA315881 comparing with other conventional clustering methods. We demonstrated that pFSBC exhibited the highest clustering accuracy and the shortest processing time.

CONCLUSION: We expect that pFSBC will help to avoid the time-consuming clustering task, and it will provide accurate clustering results for the HT-SELEX data.