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. 2018 Jan 24;8:1979. doi: 10.3389/fimmu.2017.01979

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Copyright © 2018 Reikvam, Grønningsæter, Mosevoll, Lindås, Hatfield and Bruserud.

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) or licensor 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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Random forest analysis based on the overall metabolomics profile for all 51 patients included in the study, a comparison of patients receiving and not receiving treatment with cyclosporine. Random forest analysis could distinguish between these two patient subsets with a predictive accuracy of 60%. The figure presents the 30 top-ranked metabolites and their classification (indicated in the figure, lower right) based on their importance for the identification of the two patient subsets.