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Efficient Calculation of Interval Scores for DNA Copy Number Data Analysis

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Research in Computational Molecular Biology (RECOMB 2005)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 3500))

Abstract

Background. DNA amplifications and deletions characterize cancer genome and are often related to disease evolution. Microarray based techniques for measuring these DNA copy-number changes use fluorescence ratios at arrayed DNA elements (BACs, cDNA or oligonucleotides) to provide signals at high resolution, in terms of genomic locations. These data are then further analyzed to map aberrations and boundaries and identify biologically significant structures.

Methods. We develop a statistical framework that enables the casting of several DNA copy number data analysis questions as optimization problems over real valued vectors of signals. The simplest form of the optimization problem seeks to maximize \(\varphi (I) = \sum v_i/\sqrt{|I|}\) over all subintervals I in the input vector. We present and prove a linear time approximation scheme for this problem. Namely, a process with time complexity O( − 2) that outputs an interval for which ϕ(I) is at least Opt/α(ε), where Opt is the actual optimum and α(ε) → 1 as ε → 0. We further develop practical implementations that improve the performance of the naive quadratic approach by orders of magnitude. We discuss properties of optimal intervals and how they apply to the algorithm performance.

Examples. We benchmark our algorithms on synthetic as well as publicly available DNA copy number data. We demonstrate the use of these methods for identifying aberrations in single samples as well as common alterations in fixed sets and subsets of breast cancer samples.

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© 2005 Springer-Verlag Berlin Heidelberg

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Lipson, D., Aumann, Y., Ben-Dor, A., Linial, N., Yakhini, Z. (2005). Efficient Calculation of Interval Scores for DNA Copy Number Data Analysis. In: Miyano, S., Mesirov, J., Kasif, S., Istrail, S., Pevzner, P.A., Waterman, M. (eds) Research in Computational Molecular Biology. RECOMB 2005. Lecture Notes in Computer Science(), vol 3500. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11415770_6

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  • DOI: https://doi.org/10.1007/11415770_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25866-7

  • Online ISBN: 978-3-540-31950-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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