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      A survey of sequence alignment algorithms for next-generation sequencing.

      1 ,
      Briefings in bioinformatics
      Oxford University Press (OUP)

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          Abstract

          Rapidly evolving sequencing technologies produce data on an unparalleled scale. A central challenge to the analysis of this data is sequence alignment, whereby sequence reads must be compared to a reference. A wide variety of alignment algorithms and software have been subsequently developed over the past two years. In this article, we will systematically review the current development of these algorithms and introduce their practical applications on different types of experimental data. We come to the conclusion that short-read alignment is no longer the bottleneck of data analyses. We also consider future development of alignment algorithms with respect to emerging long sequence reads and the prospect of cloud computing.

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          Author and article information

          Journal
          Brief Bioinform
          Briefings in bioinformatics
          Oxford University Press (OUP)
          1477-4054
          1467-5463
          Sep 2010
          : 11
          : 5
          Affiliations
          [1 ] Broad Institute, Cambridge, MA 02142, USA. hengli@broadinstitute.org
          Article
          bbq015
          10.1093/bib/bbq015
          2943993
          20460430
          48fa261e-7b95-40df-b591-5aba71c7e757
          History

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