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Bioinformatics for Copy Number Variation Data

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Bioinformatics for Omics Data

Part of the book series: Methods in Molecular Biology ((MIMB,volume 719))

Abstract

Copy number variation is known to be an important component of structural variation in the human genome. Greater than 1 kb in size, these gains and losses of genetic material are known to confer risk to many human diseases, both Mendelian and complex. Therefore, the technologies used to detect copy number variation have been quickly improving in both throughput and cost. From comparative genomic hybridization to synthetic high-density oligonucleotide arrays to next-generation sequencing methods, algorithms used to estimate copy number are plentiful. Here we describe a practical introduction to the copy number variation technology and available analysis methods, and demonstrate the analysis flow on an example case.

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Author information

Authors and Affiliations

  1. Department of Pediatrics and Pathology, Keck School of Medicine, Childrens Hospital Los Angeles, University of Southern California, Los Angeles, CA, USA

    Melissa Warden & Shahab Asgharzadeh

  2. Department of Human Genetics, University of Chicago, Chicago, IL, USA

    Roger Pique-Regi

  3. Department of Electrical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA

    Antonio Ortega

Authors
  1. Melissa Warden
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  2. Roger Pique-Regi
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  3. Antonio Ortega
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  4. Shahab Asgharzadeh
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Corresponding author

Correspondence to Shahab Asgharzadeh .

Editor information

Editors and Affiliations

  1. emergentec biodevelopment GmbH, Gersthofer Strasse 29-31, Vienna, 1180, Austria

    Bernd Mayer

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Warden, M., Pique-Regi, R., Ortega, A., Asgharzadeh, S. (2011). Bioinformatics for Copy Number Variation Data. In: Mayer, B. (eds) Bioinformatics for Omics Data. Methods in Molecular Biology, vol 719. Humana Press. https://doi.org/10.1007/978-1-61779-027-0_11

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  • DOI: https://doi.org/10.1007/978-1-61779-027-0_11

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  • Publisher Name: Humana Press

  • Print ISBN: 978-1-61779-026-3

  • Online ISBN: 978-1-61779-027-0

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