• DocumentCode
    3645124
  • Title

    Efficient Multiple Samples aCGH Analysis for Rare CNVs Detection

  • Author

    Maciej Sykulski;Tomasz Gambin;Magdalena Bartnik;Katarzyna Derwinska;Barbara Wisniowiecka-Kowalnik;Pawel Stankiewicz;Anna Gambin

  • Author_Institution
    Inst. of Inf., Univ. of Warsaw, Warsaw, Poland
  • fYear
    2011
  • Firstpage
    406
  • Lastpage
    409
  • Abstract
    Abstract-We propose a novel multiple sample aCGH analysis methodology aiming in rare Copy-Number Variations (CNVs) detection. Our method is tested on exon targeted aCGH array of 366 patients affected with developmental delay/intellectual disability, epilepsy, or autism. The proposed algorithms can be applied as a post-processing filtering to any given segmentation method. Thanks to the additional information obtained from multiple samples, we could efficiently detect significant segments corresponding to rare CNVs responsible for pathogenic changes. More detailed description of the method is available in Supplementary Materials at: http://bioputer.mimuw.edu.pl/acgh.
  • Keywords
    "Bioinformatics","Genomics","Arrays","Probes","Databases","Autism"
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedicine (BIBM), 2011 IEEE International Conference on
  • Print_ISBN
    978-1-4577-1799-4
  • Type

    conf

  • DOI
    10.1109/BIBM.2011.38
  • Filename
    6120475