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Detecting and annotating genetic variations using the HugeSeq pipeline

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Figure 1: A MapReduce approach for detecting genetic variants from high-throughput genome sequencing.
Figure 2: Accuracy and sensitivity of variant detection.

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Acknowledgements

We acknowledge support from the US National Institutes of Health. We also thank K. Ye, K. Chen and A. Abyzov for helpful discussions.

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Author notes

  1. Hugo Y K Lam

    Present address: Present address: Personalis, Inc., Palo Alto, California, USA.,

Authors and Affiliations

  1. Department of Genetics, Stanford University, Stanford, California, USA

    Hugo Y K Lam, Cuiping Pan, Michael J Clark, Phil Lacroute, Rui Chen, Rajini Haraksingh, Maeve O'Huallachain, Jeffrey M Kidd, Carlos D Bustamante & Michael Snyder

  2. Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, USA

    Mark B Gerstein

  3. Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, USA

    Mark B Gerstein

  4. Department of Computer Science, Yale University, New Haven, Connecticut, USA

    Mark B Gerstein

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  1. Hugo Y K Lam
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  2. Cuiping Pan
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  3. Michael J Clark
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  4. Phil Lacroute
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  5. Rui Chen
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  6. Rajini Haraksingh
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  7. Maeve O'Huallachain
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  8. Mark B Gerstein
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  11. Michael Snyder
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Corresponding author

Correspondence to Michael Snyder.

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Competing interests

M.S. is a scientific advisory board member for Genapsys, Inc.; a scientific advisory board member and cofounder of Personalis, Inc.; and a scientific advisory board member for DNA Nexus.

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Supplementary Text and Figures

Supplementary Methods, Supplementary Tables 1, 2 and Supplementary Figs. 1–3 (PDF 1481 kb)

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Lam, H., Pan, C., Clark, M. et al. Detecting and annotating genetic variations using the HugeSeq pipeline. Nat Biotechnol 30, 226–229 (2012). https://doi.org/10.1038/nbt.2134

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