A noticeable part of the microbiome literature, especially that working with low-biomass samples, is plagued by reagent contamination. Here we describe visual, statistical, methodical and ecological techniques to facilitate recognition of signals that represent contamination.

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Acknowledgements

The work was supported by the Medical Research Council (UK; G1100221) and the National Institute for Health Research (NIHR) Cambridge Comprehensive Biomedical Research Centre (Women’s Health theme).

Author information

Affiliations

  1. Wellcome Sanger Institute, Cambridge, UK

    • Marcus C. de Goffau
    • , Susannah J. Salter
    • , Josef Wagner
    • , Sharon J. Peacock
    •  & Julian Parkhill
  2. Department of Obstetrics and Gynaecology, University of Cambridge, NIHR Cambridge Comprehensive Biomedical Research Centre, Cambridge, UK

    • Susanne Lager
    • , D. Stephen Charnock-Jones
    •  & Gordon C. S. Smith
  3. Centre for Trophoblast Research (CTR), Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK

    • Susanne Lager
    • , D. Stephen Charnock-Jones
    •  & Gordon C. S. Smith
  4. Department of Internal Medicine IV (Nephrology and Hypertension), Medical University Innsbruck, Innsbruck, Austria

    • Andreas Kronbichler
  5. Vasculitis and Lupus Clinic, Addenbrooke’s Hospital, Cambridge, UK

    • Andreas Kronbichler
  6. Department of Medicine, University of Cambridge, Cambridge, UK

    • Sharon J. Peacock
  7. London School of Hygiene and Tropical Medicine, London, UK

    • Sharon J. Peacock

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Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Julian Parkhill.

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DOI

https://doi.org/10.1038/s41564-018-0202-y

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