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Statistical evaluation of diet-microbe associations

BACKGROUND: Statistical evaluation of the association between microbial abundance and dietary variables can be done in various ways. Currently, there is no consensus on which methods are to be preferred in which circumstances. Application of particular methods seems to be based on the tradition of a...

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Autores principales: Zhang, Xiang, Nieuwdorp, Max, Groen, Albert K., Zwinderman, Aeiko H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6506950/
https://www.ncbi.nlm.nih.gov/pubmed/31072384
http://dx.doi.org/10.1186/s12866-019-1464-0
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author Zhang, Xiang
Nieuwdorp, Max
Groen, Albert K.
Zwinderman, Aeiko H.
author_facet Zhang, Xiang
Nieuwdorp, Max
Groen, Albert K.
Zwinderman, Aeiko H.
author_sort Zhang, Xiang
collection PubMed
description BACKGROUND: Statistical evaluation of the association between microbial abundance and dietary variables can be done in various ways. Currently, there is no consensus on which methods are to be preferred in which circumstances. Application of particular methods seems to be based on the tradition of a particular research group, availability of experience with particular software, or depending on the outcomes of the analysis. RESULTS: We applied four popular methods including edgeR, limma, metagenomeSeq and shotgunFunctionalizeR, to evaluate the association between dietary variables and abundance of microbes. We found large difference in results between the methods. Our simulation studies revealed that no single method was optimal. CONCLUSIONS: We advise researchers to run multiple analyses and focus on the significant findings identified by multiple methods in order to achieve a better control of false discovery rate, although the false discovery rate can still be substantial.
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spelling pubmed-65069502019-05-13 Statistical evaluation of diet-microbe associations Zhang, Xiang Nieuwdorp, Max Groen, Albert K. Zwinderman, Aeiko H. BMC Microbiol Research Article BACKGROUND: Statistical evaluation of the association between microbial abundance and dietary variables can be done in various ways. Currently, there is no consensus on which methods are to be preferred in which circumstances. Application of particular methods seems to be based on the tradition of a particular research group, availability of experience with particular software, or depending on the outcomes of the analysis. RESULTS: We applied four popular methods including edgeR, limma, metagenomeSeq and shotgunFunctionalizeR, to evaluate the association between dietary variables and abundance of microbes. We found large difference in results between the methods. Our simulation studies revealed that no single method was optimal. CONCLUSIONS: We advise researchers to run multiple analyses and focus on the significant findings identified by multiple methods in order to achieve a better control of false discovery rate, although the false discovery rate can still be substantial. BioMed Central 2019-05-09 /pmc/articles/PMC6506950/ /pubmed/31072384 http://dx.doi.org/10.1186/s12866-019-1464-0 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Zhang, Xiang
Nieuwdorp, Max
Groen, Albert K.
Zwinderman, Aeiko H.
Statistical evaluation of diet-microbe associations
title Statistical evaluation of diet-microbe associations
title_full Statistical evaluation of diet-microbe associations
title_fullStr Statistical evaluation of diet-microbe associations
title_full_unstemmed Statistical evaluation of diet-microbe associations
title_short Statistical evaluation of diet-microbe associations
title_sort statistical evaluation of diet-microbe associations
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6506950/
https://www.ncbi.nlm.nih.gov/pubmed/31072384
http://dx.doi.org/10.1186/s12866-019-1464-0
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