• DocumentCode
    2764632
  • Title

    CONDEX: Copy number detection in exome sequences

  • Author

    Ramachandran, Arthi ; Micsinai, Mariann ; Pe´er, Itsik

  • Author_Institution
    Dept. of Comput. Sci., Columbia Univ., New York, NY, USA
  • fYear
    2011
  • fDate
    12-15 Nov. 2011
  • Firstpage
    87
  • Lastpage
    93
  • Abstract
    Exome sequencing by hybrid capture facilitates obtaining cost-effective, comprehensive data on coding sequence variation from short reads. Standard analysis tools focus on detecting and characterizing variants of single or a few nucleotides while copy number variants (CNVs) that span multiple regions of exon baits have not yet been considered. Here, we present a Hidden Markov Model based method to identify CNVs from exome sequencing data. Using depth coverage and the heterozygosity of SNPs, we call CNVs with per-exon training data from other samples. The method has >;90% accuracy in identification of deletions and insertions in simulations. Availability - http://code.google.com/p/condr/(Java).
  • Keywords
    bioinformatics; genetics; genomics; hidden Markov models; molecular biophysics; CONDEX; HMM; coding sequence variation; comprehensive data; copy number detection; copy number variants; cost-effective data; depth coverage; exome sequences; heterozygosity; hidden Markov model; hybrid capture; nucleotides; per-exon training data; span multiple regions; standard analysis tools; Accuracy; Arrays; Bioinformatics; Cancer; Computational modeling; Genomics; Hidden Markov models;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedicine Workshops (BIBMW), 2011 IEEE International Conference on
  • Conference_Location
    Atlanta, GA
  • Print_ISBN
    978-1-4577-1612-6
  • Type

    conf

  • DOI
    10.1109/BIBMW.2011.6112359
  • Filename
    6112359