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. 2020 Aug 28;8:124. doi: 10.1186/s40168-020-00900-2

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© The Author(s) 2020

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.

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Fig. 3 — MAPE and Bray-Curtis dissimilarity. This plot evaluates classification accuracy by using the inverse of two error metrics: mean absolute proportion error (MAPE) and Bray-Curtis dissimilarity (BC). a Comparison of the accuracy of Kraken, Bracken, and Qiime’s q2-feature-classifier when predicting the genus read counts across all samples for given metagenome/database. b Comparison of the accuracy between the individual primers averaged across all 3 metagenomes for a given software/database. The top plots calculate accuracy as 1−MAPE while the bottom plots evaluate 1−BC

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