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Applications of the Scan Statistic in DNA Sequence Analysis

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Book cover Scan Statistics and Applications

Part of the book series: Statistics for Industry and Technology ((SIT))

Abstract

Advances of biochemical techniques have made available large databases of long DNA sequences. These sequences reflect conglomerates of random and nonrandom letter strings from the nucleotide alphabet {A, C, G, T}. As the databases expand, mathematical methods play an increasingly important role in analyzing and interpreting the rapidly accumulating DNA data. In this chapter, we discuss a specific example of identifying nonrandom clusters of palindromes in a family of herpesvirus genomes using the r-scan statistic. Palindrome positions on the genome are modeled by i.i.d. random variables uniformly distributed on the unit interval (0,1). After a comparison of three Poisson-type approximations, the r-scan distribution is computed by a compound Poisson approximation proposed by Glaz (1994). Some of the significant palindrome clusters are located at genome regions containing origins of replication and regulatory signals of the herpesviruses.

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Author information

Authors and Affiliations

  1. University of Texas at San Antonio, San Antonio, TX, USA

    Ming-Ying Leung & Traci E. Yamashita

  2. Johns Hopkins School of Hygiene and Public Health, Baltimore, MD, USA

    Ming-Ying Leung & Traci E. Yamashita

Authors
  1. Ming-Ying Leung
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  2. Traci E. Yamashita
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Editor information

Editors and Affiliations

  1. Department of Statistics, University of Connecticut at Storrs, Storrs, CT, 06269-3120, USA

    Joseph Glaz

  2. Department of Mathematics and Statistics, McMaster University, Hamilton, Ontario, L8S 4K1, Canada

    N. Balakrishnan

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© 1999 Springer Science+Business Media New York

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Leung, MY., Yamashita, T.E. (1999). Applications of the Scan Statistic in DNA Sequence Analysis. In: Glaz, J., Balakrishnan, N. (eds) Scan Statistics and Applications. Statistics for Industry and Technology. Birkhäuser, Boston, MA. https://doi.org/10.1007/978-1-4612-1578-3_12

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  • DOI: https://doi.org/10.1007/978-1-4612-1578-3_12

  • Publisher Name: Birkhäuser, Boston, MA

  • Print ISBN: 978-1-4612-7201-4

  • Online ISBN: 978-1-4612-1578-3

  • eBook Packages: Springer Book Archive

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