Bayesian Joint Estimation of CN and LOH Aberrations

  • Paola M. V. Rancoita
  • Marcus Hutter
  • Francesco Bertoni
  • Ivo Kwee
Conference paper

DOI: 10.1007/978-3-642-02481-8_168

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5518)
Cite this paper as:
Rancoita P.M.V., Hutter M., Bertoni F., Kwee I. (2009) Bayesian Joint Estimation of CN and LOH Aberrations. In: Omatu S. et al. (eds) Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living. IWANN 2009. Lecture Notes in Computer Science, vol 5518. Springer, Berlin, Heidelberg

Abstract

SNP-microarrays are able to measure simultaneously both copy number and genotype at several single nucleotide polymorphism positions. Combining the two data, it is possible to better identify genomic aberrations. For this purpose, we propose a Bayesian piecewise constant regression which infers the type of aberration occurred, taking into account all the possible influence in the microarray detection of the genotype, resulting from an altered copy number level. Namely, we model the distributions of the detected genotype given a specific genomic alteration and we estimate the hyper-parameters used on public reference datasets.

Keywords

Bayesian regression piecewise constant function change point problem DNA copy number estimation LOH estimation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Paola M. V. Rancoita
    • 1
    • 2
    • 3
  • Marcus Hutter
    • 4
  • Francesco Bertoni
    • 2
  • Ivo Kwee
    • 1
    • 2
  1. 1.Istituto Dalle Molle di Studi sull’Intelligenza ArtificialeMannoSwitzerland
  2. 2.Laboratory of Experimental OncologyOncology Institute of Southern SwitzerlandBellinzonaSwitzerland
  3. 3.Dipartimento di MatematicaUniversità degli Studi di MilanoMilanoItaly
  4. 4.RSISE, ANU and SML, NICTACanberraAustralia

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