This article examines methods, issues and controversies that have arisen over the last decade in the effort to organize sequences of DNA base information into homogeneous segments. An array of different models and techniques have been considered and applied. We demonstrate that most approaches can be embedded into a suitable version of the multiple change-point problem, and we review the various methods in this light. We also propose and discuss a promising local segmentation method, namely, the application of split local polynomial fitting. The genome of bacteriophage λ serves as an example sequence throughout the paper. © 1998 Rocky Mountain Mathematics Consortium.
CITATION STYLE
Braun, J. V., & Müller, H. G. (1998). Statistical methods for dna sequence segmentation. Statistical Science, 13(2), 142–162. https://doi.org/10.1214/ss/1028905933
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