Inferring human microbial dynamics from temporal metagenomics data: Pitfalls and lessons

Hong Tai Cao, Travis E. Gibson, Amir Bashan, Yang Yu Liu

Research output: Contribution to journalArticlepeer-review

46 Scopus citations


The human gut microbiota is a very complex and dynamic ecosystem that plays a crucial role in health and well-being. Inferring microbial community structure and dynamics directly from time-resolved metagenomics data is key to understanding the community ecology and predicting its temporal behavior. Many methods have been proposed to perform the inference. Yet, as we point out in this review, there are several pitfalls along the way. Indeed, the uninformative temporal measurements and the compositional nature of the relative abundance data raise serious challenges in inference. Moreover, the inference results can be largely distorted when only focusing on highly abundant species by ignoring or grouping low-abundance species. Finally, the implicit assumptions in various regularization methods may not reflect reality. Those issues have to be seriously considered in ecological modeling of human gut microbiota.

Original languageEnglish
Article number1600188
Issue number2
StatePublished - 1 Feb 2017

Bibliographical note

Publisher Copyright:
© 2016 WILEY Periodicals, Inc.


This work was partially supported by the John Templeton Foundation (award number 51977).

FundersFunder number
National Heart, Lung, and Blood InstituteT32HL007627
John Templeton Foundation51977


    • dynamics inference
    • ecological modeling
    • human microbiome
    • temporal metagenomics


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