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. 2019 Aug 6;2:294. doi: 10.1038/s42003-019-0545-9

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© The Author(s) 2019

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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 2 — On-target classification rate of each method for each confirmed resistance class in the Pediatric and Soil datasets. Alignment and Meta-MARC HTS had improved performance on the Pediatric data than the Soil data, as evidenced by the higher quantiles of sample-wise classification rates shown here for the Pediatric data. Meta-MARC Assembly performed comparably to Resfams. Although alignment and Meta-MARC HTS classified fewer sequence reads overall, their on-target classification rates are comparable to Resfams and Meta-MARC Assembly on the Pediatric dataset