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Detecting a changed segment in DNA sequences

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  • P. J. Avery
  • D. A. Henderson

Abstract

Non‐coding deoxyribonucleic acid (DNA) can typically be modelled by a sequence of Bernoulli random variables by coding one base, e.g. T, as 1 and other bases as 0. If a segment of a sequence is functionally important, the probability of a 1 will be different in this changed segment from that in the surrounding DNA. It is important to be able to see whether such a segment occurs in a particular DNA sequence and to pin‐point it so that a molecular biologist can investigate its possible function. Here we discuss methods for testing the occurrence of such a changed segment and how to estimate the end points of it. Maximum‐likelihood‐based methods are not very tractable and so a nonparametric method based on the approach of Pettitt has been developed. The problem and its solution are illustrated by a specific DNA example.

Suggested Citation

  • P. J. Avery & D. A. Henderson, 1999. "Detecting a changed segment in DNA sequences," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 48(4), pages 489-503.
    • Handle: RePEc:bla:jorssc:v:48:y:1999:i:4:p:489-503
    DOI: 10.1111/1467-9876.00167
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    Cited by:

    1. Jurgita Markevičiūtė & Alfredas Račkauskas & Charles Suquet, 2017. "Testing epidemic change in nearly nonstationary process with statistics based on residuals," Statistical Papers, Springer, vol. 58(3), pages 577-606, September.
    2. Pezzatti, Gianni B. & Zumbrunnen, Thomas & Bürgi, Matthias & Ambrosetti, Paolo & Conedera, Marco, 2013. "Fire regime shifts as a consequence of fire policy and socio-economic development: An analysis based on the change point approach," Forest Policy and Economics, Elsevier, vol. 29(C), pages 7-18.
    3. Mijatović, Aleksandar & Pistorius, Martijn, 2015. "Asymptotic independence of three statistics of maximal segmental scores," Statistics & Probability Letters, Elsevier, vol. 99(C), pages 185-191.

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