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. 2018 Jun 11;8:8826. doi: 10.1038/s41598-018-27189-4

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© The Author(s) 2018

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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Evaluation of the asthma classifier on test sets of independent subjects with non-asthma respiratory conditions. Performance statistics of the classifier when applied to external microarray-generated data sets of nasal gene expression derived from case/control cohorts with non-asthma respiratory conditions. Performance is shown in terms of F-measure (A and C), a conservative mean of precision and sensitivity, as well as positive (B) and negative predictive values (D). The classifier had a low to zero rate of misclassifying other respiratory conditions as asthma, supporting that the classifier is specific to asthma and would not misclassify other respiratory conditions as asthma.