Author

Nicole E. McCormick

Dalhousie University

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Bioinformatics· 1

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Organism:bacteria (other)· 1 Approach:benchmark study· 1 Research Focus:benchmarking· 1 Research Focus:differential expression· 1 Organism:human· 1 Assay:metagenomics· 1 Approach:statistical model· 1

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A. ComeauiD· 1 shared Akhilesh S. DhananiiD· 1 shared Casey M. A. JonesiD· 1 shared Dhwani DesaiiD· 1 shared Gavin M. DouglasiD· 1 shared Jacob T. NearingiD· 1 shared Jocelyn MacDonald· 1 shared Molly G. HayesiD· 1 shared

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2022-2022 · peak 1/yr

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1 paper

Recent·Most cited

Microbiome differential abundance methods produce disturbingly different results across 38 datasets

Jacob T. Nearing, Gavin M. Douglas, Molly G. Hayes, Jocelyn MacDonald, Dhwani Desai, Nicole E. McCormick, Casey M. A. Jones, Robyn Wright, Akhilesh S. Dhanani, A. Comeau, Morgan G. I. Langille

In 38 two-group 16S rRNA datasets, 14 differential abundance tools disagreed sharply; ALDEx2 and ANCOM-II were conservative and consistent, while edgeR and LEfSe inflated false positives.

Nature Communications · Jan 17, 2022Peer-reviewedBioinformatics✦ In-depth digest