HRCM: An Efficient Hybrid Referential Compression Method for Genomic Big Data.

With the maturity of genome sequencing technology, huge amounts of sequence reads as well as assembled genomes are generating. With the explosive growth of genomic data, the storage and transmission of genomic data are facing enormous challenges. FASTA, as one of the main storage formats for genome...

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Published in:BioMed Research International pp. 1 - 14
Main Authors: Haichang Yao, Yimu Ji, Kui Li, ShangdongLiu, Jing He, Ruchuan Wang
Format: algorithm research tables/charts Journal Article
Published: Wiley-Blackwell 11/16/2019
Online Access:View this record in EBSCOhost
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      dt: 11/16/2019
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1155/2019/3108950
        141394401
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        atl: HRCM: An Efficient Hybrid Referential Compression Method for Genomic Big Data.
      aug:
        au:
          Haichang Yao
          Yimu Ji
          Kui Li
          ShangdongLiu
          Jing He
          Ruchuan Wang
        affil: School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
      sug:
        subj:
          Genomics
          Sequence Analysis Methods
          Resource Databases
          Human
          Pedigree
          Health Information
          Information Retrieval
      ab: With the maturity of genome sequencing technology, huge amounts of sequence reads as well as assembled genomes are generating. With the explosive growth of genomic data, the storage and transmission of genomic data are facing enormous challenges. FASTA, as one of the main storage formats for genome sequences, is widely used in the Gene Bank because it eases sequence analysis and gene research and is easy to be read. Many compression methods for FASTA genome sequences have been proposed, but they still have room for improvement. For example, the compression ratio and speed are not so high and robust enough, and memory consumption is not ideal, etc. *erefore, it is of great significance to improve the efficiency, robustness, and practicability of genomic data compression to reduce the storage and transmission cost of genomic data further and promote the research and development of genomic technology. In this manuscript, a hybrid referential compression method (HRCM) for FASTA genome sequences is proposed. HRCM is a lossless compression method able to compress single sequence as well as large collections of sequences. It is implemented through three stages: sequence information extraction, sequence information matching, and sequence information encoding. A large number of experiments fully evaluated the performance of HRCM. Experimental verification shows that HRCM is superior to the best-known methods in genome batch compression. Moreover, HRCM memory consumption is relatively low and can be deployed on standard PCs.
      pubtype: Academic Journal
      doctype:
        algorithm
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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