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. 2021 Apr 20;12:643682. doi: 10.3389/fmicb.2021.643682

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Copyright © 2021 Parks, Rigato, Vera-Wolf, Krause, Hugenholtz, Tyson and Wood.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Performance of metagenomic classifiers to predict species abundances. (A) L1 distance (0% = identical to ground truth; 200% = no species in common with ground truth) between the ground truth and predicted species profiles. (B) Mean relative error of species present in both the ground truth and predicted species profiles. (C) Sum of false positive species abundances. (D) Sum of false negative species abundances. Lower values indicate better performance. Results are provided across mock communities of increasing ANI divergence from the reference database. Results for Centrifuge, DIAMOND-LCA, Kaiju, and mOTUs are not shown as they have substantially worse species abundance estimates than the other classifiers (Supplementary Figure 2).