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The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Differential abundance analysis for microbial marker-gene surveys

Open access
Paulson, Joseph N, Stine, O Colin, Bravo, Héctor Corrada, Pop, Mihai·2013·Nature Methods
DOI 10.1038/nmeth.2658
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Abstract

We introduce a methodology to assess differential abundance in sparse high-throughput microbial marker-gene survey data. Our approach, implemented in the metagenomeSeq Bioconductor package, relies on a novel normalization technique and a statistical model that accounts for undersampling—a common feature of large-scale marker-gene studies. Using simulated data and several published microbiota data sets, we show that metagenomeSeq outperforms the tools currently used in this field.

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Show all 9 references

Research works printed but not linked: 21

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Metadata

Authors
Paulson, J. N., Stine, O. C., Bravo, H. C., & Pop, M.
Venue
Nature Methods
Publisher
Springer Science and Business Media LLC
Published
2013-09-29
Volume
10
Issue
12
Pages
1200-1202
ISSN
  • 1548-7091 (ISSN-L)
  • 1548-7105
DOI
10.1038/nmeth.2658
OpenAlex
W2026006003
Cited by
2,428
References
9
FWCI
23.67
Type
journal article
Language
en
Open access
green
Licence
www.springer.com/tdm (tdm)

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CoChat. (2026). Citation check: Differential abundance analysis for microbial marker-gene surveys. https://app.cochat.ai/papers/10.1038/nmeth.2658
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Paulson, J. N., Stine, O. C., Bravo, H. C., & Pop, M. (2013). Differential abundance analysis for microbial marker-gene surveys. Nature Methods. https://doi.org/10.1038/nmeth.2658

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.