DNA segmentation as a model selection process

Authors:
Wentian Li
Affiliations:
Laboratory of Statistical Genetics, The Rockefeller University, Box 192, New York, NY
Venue:
RECOMB '01 Proceedings of the fifth annual international conference on Computational biology
Year:
2001

Citing 5
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Abstract

Previous divide-and-conquer segmentation analyses of DNA sequences do not provide a satisfactory stopping criterion for the recursion. This paper proposes that segmentation be considered as a model selection process. Using the tools in model selection, a limit for the stopping criterion on the relaxed end can be determined. The Bayesian information criterion, in particular, provides a much more stringent stopping criterion than what is currently used. Such a stringent criterion can be used to delineate larger DNA domains. A relationship between the stopping criterion and the average domain size is empirically determined, which may aid in the determination of isochore borders.