Nature Communications (Jan 2022)

Microbiome differential abundance methods produce different results across 38 datasets

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

DOI
https://doi.org/10.1038/s41467-022-28034-z
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 16

Abstract

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Many microbiome differential abundance methods are available, but it lacks systematic comparison among them. Here, the authors compare the performance of 14 differential abundance testing methods on 38 16S rRNA gene datasets with two sample groups, and show ALDEx2 and ANCOM-II produce the most consistent results.