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Journal Article

Effects of Long-Range Correlations in DNA on Sequence Alignment Score Statistics.

MPS-Authors

Messer,  Philipp W.
Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons50613

Vingron,  Martin
Gene regulation (Martin Vingron), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons50074

Arndt,  Peter F.
Evolutionary Genomics (Peter Arndt), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Citation

Messer, P. W., Bundschuh, R., Vingron, M., & Arndt, P. F. (2007). Effects of Long-Range Correlations in DNA on Sequence Alignment Score Statistics. Journal of Computational Biology: A Journal of Computational Molecular Cell Biology, 14(5), 655-668. doi:10.1089/cmb.2007.R008.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0010-81C0-2
Abstract
Long-range correlations in genomic base composition are a ubiquitous statistical feature among many eukaryotic genomes. In this article, these correlations are shown to substantially influence the statistics of sequence alignment scores. Using a Gaussian approximation to model the correlated score landscape, we calculate the corrections to the scale parameter lambda of the extreme value distribution of alignment scores. Our approximate analytic results are supported by a detailed numerical study based on a simple algorithm to efficiently generate long-range correlated random sequences. We find both, mean and exponential tail of the score distribution for long-range correlated sequences to be substantially shifted compared to random sequences with independent nucleotides. The significance of measured alignment scores will therefore change upon incorporation of the correlations in the null model. We discuss the magnitude of this effect in a biological context.