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Fast, accurate error-correction of amplicon pyrosequences using Acacia

Nature Methods volume 9, pages 425–426 (2012)Cite this article

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To the Editor:

Microbial diversity metrics based on high-throughput amplicon sequencing are compromised by read errors. Roche 454 GS FLX Titanium pyrosequencing is currently the most widely used technology for amplicon-based microbial community studies, despite high homopolymer-associated insertion-deletion error rates1,2. Currently, there are two software packages, AmpliconNoise3 and Denoiser4, that are commonly used to correct amplicon pyrosequencing errors. AmpliconNoise applies an approximate likelihood using empirically derived error distributions to remove pyrosequencing noise from reads. AmpliconNoise is highly effective at noise removal but is computationally intensive3. Denoiser is a faster algorithm that uses frequency-based heuristics rather than statistical modeling to cluster reads. Neither tool modifies individual reads; instead both select an 'error-free' read to represent reads in a given cluster.

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Figure 1: Benchmarking sensitivity and specificity of Acacia.

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Acknowledgements

L.B. was supported by a PhD scholarship funded by the Commonwealth Scientific and Industrial Research Organisation Transformational Biology capability platform. G.W.T. was supported by a Queen Elizabeth II Fellowship from the Australian Research Council, grant DP1093175. Work was also supported by strategic University of Queensland funding of the Australian Centre for Ecogenomics.

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Authors and Affiliations

  1. Advanced Water Management Centre, The University of Queensland, St. Lucia, Queensland, Australia

    Lauren Bragg, Michael Imelfort & Gene W Tyson

  2. Australian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences, The University of Queensland, St. Lucia, Queensland, Australia

    Lauren Bragg, Michael Imelfort, Philip Hugenholtz & Gene W Tyson

  3. Commonwealth Scientific and Industrial Research Organisation Mathematics, Informatics and Statistics, Queensland, Australia

    Lauren Bragg

  4. School of Computing and Mathematics, University of Western Sydney, New South Wales, Australia

    Glenn Stone

  5. Institute for Molecular Bioscience, The University of Queensland, St. Lucia, Queensland, Australia

    Philip Hugenholtz

Authors
  1. Lauren Bragg
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  2. Glenn Stone
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  3. Michael Imelfort
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  4. Philip Hugenholtz
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  5. Gene W Tyson
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Corresponding author

Correspondence to Gene W Tyson.

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Supplementary Figures 1—5, Supplementary Tables 1—3, Supplementary Notes 1—3 and Supplementary Methods (PDF 1429 kb)

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Bragg, L., Stone, G., Imelfort, M. et al. Fast, accurate error-correction of amplicon pyrosequences using Acacia. Nat Methods 9, 425–426 (2012). https://doi.org/10.1038/nmeth.1990

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