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Performance comparison of whole-genome sequencing platforms

Nature Biotechnology 30, 78–82 (2012) | Download Citation

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  • A Corrigendum to this article was published on 07 June 2012

This article has been updated

Abstract

Whole-genome sequencing is becoming commonplace, but the accuracy and completeness of variant calling by the most widely used platforms from Illumina and Complete Genomics have not been reported. Here we sequenced the genome of an individual with both technologies to a high average coverage of ∼76×, and compared their performance with respect to sequence coverage and calling of single-nucleotide variants (SNVs), insertions and deletions (indels). Although 88.1% of the ∼3.7 million unique SNVs were concordant between platforms, there were tens of thousands of platform-specific calls located in genes and other genomic regions. In contrast, 26.5% of indels were concordant between platforms. Target enrichment validated 92.7% of the concordant SNVs, whereas validation by genotyping array revealed a sensitivity of 99.3%. The validation experiments also suggested that >60% of the platform-specific variants were indeed present in the genome. Our results have important implications for understanding the accuracy and completeness of the genome sequencing platforms.

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Change history

  • 07 June 2012

    In the version of this article initially published, the accession code to obtain raw sequence data was given as SRA045736.2; the correct code is SRA045736. The error has been corrected in the HTML and PDF versions of the article.

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Acknowledgements

This work is supported by the Stanford Department of Genetics and the US National Institutes of Health.

Author information

    • Hugo Y K Lam
    •  & Rong Chen

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

Affiliations

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

    • Hugo Y K Lam
    • , Michael J Clark
    • , Rui Chen
    • , Maeve O'Huallachain
    •  & Michael Snyder

  2. Division of Systems Medicine, Department of Pediatrics, Stanford University, Stanford, California, USA.

    • Rong Chen
    •  & Atul J Butte

  3. Department of Medicine, Stanford University, Stanford, California, USA.

    • Georges Natsoulis
    •  & Hanlee P Ji

  4. Center for Inherited Cardiovascular Disease, Division of Cardiovascular Medicine, Stanford University, Stanford, California, USA.

    • Frederick E Dewey
    •  & Euan A Ashley

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

    • Lukas Habegger
    •  & Mark B Gerstein

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

    • Mark B Gerstein

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

    • Mark B Gerstein

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Contributions

H.Y.K.L. and M.J.C. did the analysis. G.N. and L.H. assisted in the analysis. Rui C. did DNA sequencing. Rong C. did the disease-association study. Rui C. and M.O'H. did the validation experiments. H.Y.K.L., F.E.D., E.A.A., M.B.G., A.J.B., H.P.J. and M.S. coordinated the analysis and revised the manuscript. H.Y.K.L., M.J.C. and M.S. wrote the manuscript.

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 consultant for Illumina.

Corresponding author

Correspondence to Michael Snyder.

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1 and 2

Excel files

  1. 1.

    Supplementary Table 1

    Disease association of all platform-specific SNPs.

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DOI

https://doi.org/10.1038/nbt.2065

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