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BreakDancer: an algorithm for high-resolution mapping of genomic structural variation

Abstract

Detection and characterization of genomic structural variation are important for understanding the landscape of genetic variation in human populations and in complex diseases such as cancer. Recent studies demonstrate the feasibility of detecting structural variation using next-generation, short-insert, paired-end sequencing reads. However, the utility of these reads is not entirely clear, nor are the analysis methods with which accurate detection can be achieved. The algorithm BreakDancer predicts a wide variety of structural variants including insertion-deletions (indels), inversions and translocations. We examined BreakDancer's performance in simulation, in comparison with other methods and in analyses of a sample from an individual with acute myeloid leukemia and of samples from the 1,000 Genomes trio individuals. BreakDancer sensitively and accurately detected indels ranging from 10 base pairs to 1 megabase pair that are difficult to detect via a single conventional approach.

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Figure 1: Overview of BreakDancer algorithm.
Figure 2: Performance of BreakDancer in simulation.
Figure 3: Size distribution of deletions detected in the genome of an individual with AML.
Figure 4: Accuracy of predicted variant sizes. Plotted are variant sizes predicted by BreakDancer and by local assembly (estimated) versus true sizes determined from the PCR resequencing (validated).

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Acknowledgements

We thank the Genomics of AML Program Project Grant team at Washington University Medical School (US National Cancer Institute PO1 CA101937; principal investigagor, T.J.L.) and the 1,000 Genomes Consortium members for providing the data. We thank members of the 1,000 Genomes structural variation group and H. Li for methodology discussions; D. Bentley and M. Ross (Illumina), C. Alkan and J. Kidd (University of Washington), and Y. Li and H. Zheng (Beijing Genome Institute) for providing validation data; and A. Chinwalla, D. Dooling, S. Smith, J. Eldred, C. Harris, L. Cook, V. Magrini, Y. Tang, H. Schmidt, C. Haipek, G. Elliott and R. Abbott for assistance. This work was supported by the National Human Genome Research Institute (HG003079; principal investigator, R.K.W.).

Author information

Authors and Affiliations

Authors

Contributions

E.R.M., R.K.W., L.D. and T.J.L.: project conception and oversight. K.C.: algorithm design and implementation. J.W.W.: variant assembly. J.M.K., M.D.M. and R.S.F.: experimental validation. C.S.P. and L.D.: primer design. S.D.M. and D.P.L.: Illumina library preparation. Q.Z. and M.C.W.: statistical insight. J.W.W., D.E.L., X.S., and D.P.L.: variant characterization and visualization. K.C., E.R.M., M.C.W., L.D. and J.W.W.: manuscript preparation.

Corresponding author

Correspondence to Ken Chen.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–12, Supplementary Tables 2, 4–8 and Supplementary Note (PDF 1386 kb)

Supplementary Table 1

List of structural variants detected in simulation. (XLS 72 kb)

Supplementary Table 3

A list of AML2 structural variants detected by BreakDancer, refined by local assembly and validated via PCR resequencing. (XLS 99 kb)

Supplementary Software

The BreakDancer software package encompasses two algorithms: BreakDancerMax detects large structural variants (deletions, insertions, inversions, and intra- and interchromosomal translocations), and BreakDancerMini detects small (10–100 bp) insertions and deletions. (ZIP 16 kb)

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Chen, K., Wallis, J., McLellan, M. et al. BreakDancer: an algorithm for high-resolution mapping of genomic structural variation. Nat Methods 6, 677–681 (2009). https://doi.org/10.1038/nmeth.1363

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