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Cloud computing and the DNA data race

Nature Biotechnology volume 28, pages 691–693 (2010)Cite this article

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Given the accumulation of DNA sequence data sets at ever-faster rates, what are the key factors you should consider when using distributed and multicore computing systems for analysis?

In the race between DNA sequencing throughput and computer speed, sequencing is winning by a mile. Sequencing throughput has recently been improving at a rate of about fivefold per year1, whereas computer performance generally follows 'Moore's Law', doubling only every 18 or 24 months2. As this gap widens, the question of how to design higher-throughput analysis pipelines becomes crucial. If analysis throughput does not turn the corner, research projects will continually stall until analyses catch up.

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Figure 1: Map-shuffle-scan framework used by Crossbow.

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Acknowledgements

The authors were supported in part by US National Science Foundation grant IIS-0844494 and by US National Institutes of Health grant R01-LM006845.

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Authors and Affiliations

  1. Michael C. Schatz and Steven L. Salzberg are at the Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, USA.,

    Michael C Schatz & Steven L Salzberg

  2. Ben Langmead is at the Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.,

    Ben Langmead

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Correspondence to Michael C Schatz.

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Schatz, M., Langmead, B. & Salzberg, S. Cloud computing and the DNA data race. Nat Biotechnol 28, 691–693 (2010). https://doi.org/10.1038/nbt0710-691

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