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. 2019 May 27;19:111. doi: 10.1186/s12866-019-1466-y

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© 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.

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Fig. 2 — Clustering of the microbiota data supervised by the age based on MRT (multivariate regression trees) analysis and the result of variation partitioning analysis exploring explanatory power of numerical and categorial variant of age in relation to the microbiota data matrix. (a) The MRT analysis indicates that supervised by the age variant, the microbiota data could be stratified as 75 and younger group and 76 and older group. (b) The variation partitioning analysis indicates that the most part of the explanatory power of the numerical variant of age in relation to the microbiota data matrix could be explained by the two categorial variant of age (age of ≤75 or ≥ 76)