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. 2020 Nov 12;19:159. doi: 10.1186/s12943-020-01280-9

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© The Author(s) 2020

Open AccessThis 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. 2 — The performance of the TRY-RNA signature in the validation cohort. a Expression heatmap of the sncRNA species within the TRY-RNA signature in the validation cohort. b Principal component analysis of the TRY-RNA signature. PC1: the first principal component; PC2: the second principal component. PC1 significantly differed between the controls and lung cancer patients (t-test: P = 3.1 × 10^− 3), between the controls and TB patients (t-test: P = 4.7 × 10^− 6), and between the lung cancer and TB patients (t-test: P = 4.1 × 10^− 8). c Comparison of the TRY-RNA index among the control, lung cancer, and TB subjects in the validation cohort. d The ROC curve of the TRY-RNA index in distinguishing between lung cancer and non-cancer subjects and between TB and non-TB subjects in the validation cohort