Massively Parallel Sequencing Approaches for Characterization of Structural Variation

  • Daniel C. Koboldt
  • David E. Larson
  • Ken Chen
  • Li Ding
  • Richard K. Wilson
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 838)

Abstract

The emergence of next-generation sequencing (NGS) technologies offers an incredible opportunity to comprehensively study DNA sequence variation in human genomes. Commercially available platforms from Roche (454), Illumina (Genome Analyzer and Hiseq 2000), and Applied Biosystems (SOLiD) have the capability to completely sequence individual genomes to high levels of coverage. NGS data is particularly advantageous for the study of structural variation (SV) because it offers the sensitivity to detect variants of various sizes and types, as well as the precision to characterize their breakpoints at base pair resolution. In this chapter, we present methods and software algorithms that have been developed to detect SVs and copy number changes using massively parallel sequencing data. We describe visualization and de novo assembly strategies for characterizing SV breakpoints and removing false positives.

Key words

Next-generation sequencing Paired-end sequencing 454 Illumina Solexa Abi solid Insertions Deletions Duplications Inversions Translocations Indels Copy number variants 

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Daniel C. Koboldt
    • 1
  • David E. Larson
    • 1
  • Ken Chen
    • 1
  • Li Ding
    • 1
  • Richard K. Wilson
    • 1
  1. 1.The Genome Institute at Washington University School of MedicineSt. LouisUSA

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