Survey of gene splicing algorithms based on reads. Issue 6 (2nd November 2017)

• Record Type: Journal Article
• Authors: Si, Xiuhua; Wang, Qian; Zhang, Lei; Wu, Ruo; Ma, Jiquan
• Is Part Of: Bioengineered. Volume 8:Issue 6(2017)
• Page Start: 750
• Page End: 758
• Publication Date: 2017-11-02
• Subjects: De Bruijn graph -- gene splicing -- Hadoop -- MapReduce -- read; Biomedical engineering -- Periodicals; Biotechnology -- Periodicals; Microbiology -- Periodicals; 660.6
• DOI: 10.1080/21655979.2017.1373538
• Languages: English
• ISSNs: 2165-5987

Abstract

ABSTRACT: Gene splicing is the process of assembling a large number of unordered short sequence fragments to the original genome sequence as accurately as possible. Several popular splicing algorithms based on reads are reviewed in this article, including reference genome algorithms and de novo splicing algorithms (Greedy-extension, Overlap-Layout-Consensus graph, De Bruijn graph). We also discuss a new splicing method based on the MapReduce strategy and Hadoop. By comparing these algorithms, some conclusions are drawn and some suggestions on gene splicing research are made.