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Scan Statistics pp 319–350Cite as

How Can Pattern Statistics Be Useful for DNA Motif Discovery?

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

Abstract

Statistics of motifs have been widely revisited in the last 15 years due to the increasing availability of genomic sequences. The identification of DNA motifs with biological functions is still a huge challenge of genome analysis. Many functional and essential motifs have the particularity to be very frequent all along the chromosome or to be concentrated in some particular regions (e.g. in front of genes) or to be co-oriented with the replication direction. The prediction of functional motifs is then mostly based on statistical properties of pattern occurrences in Markovian sequences. This chapter is primarily devoted to such properties with a special focus on pattern frequency. How does one compute or approximate the count distribution to assess motif exceptionality? How can we test if a motif is significantly unbalanced between two (sets of) sequences? How should one deal with degenerated patterns? How can we model occurrences to find regions significantly enriched with a given pattern? Examples of functional motifs will illustrate all these questions, and we will see how the Chi motif has been identified in Staphylococcus aureus because of its statistical properties.

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Notes

  1. 1.

    The backbone of a bacterial genome is composed of the genomic regions conserved in several strains of the bacteria. Here, we used the backbone obtained from the alignment of the three strains K12, O157:H7 and CFT and available at http://genome.jouy.inra.fr/mosaic/

  2. 2.

    In contrast to Section 15.2.5, the backbone here is the one obtained from the alignment of two strains: K12 and 0157:H7.

  3. 3.

    a is the complement of t whereas c is the complement of g.

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Authors
  1. Sophie Schbath
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  2. Stéphane Robin
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Editor information

Editors and Affiliations

  1. Dept. Statistics, University of Connecticut, Glenbrook Rd. 215, Storrs, 06269-3120, U.S.A.

    Joseph Glaz

  2. Dept. Statistics, University of Connecticut, Glenbrook Road 215, Storrs, 06269-4120, U.S.A.

    Vladimir Pozdnyakov

  3. Center for Biomathematical Sciences, Mount Sinai School of Medicine, Gustave L Levy Place 1, New York, 10029, U.S.A.

    Sylvan Wallenstein

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Schbath, S., Robin, S. (2009). How Can Pattern Statistics Be Useful for DNA Motif Discovery?. In: Glaz, J., Pozdnyakov, V., Wallenstein, S. (eds) Scan Statistics. Statistics for Industry and Technology. Birkhäuser Boston. https://doi.org/10.1007/978-0-8176-4749-0_15

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