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. 2018 Apr 19;118(10):1349–1358. doi: 10.1038/s41416-018-0048-3

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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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Fig. 2 — Multivariate analyses of ovarian cancer and normal tissue types. a 3-component 3D PCA, percentage of variance explained in PCs1–3: 36.0, 17.6, 9.0%. b 25-component 3D PC-LDA. c Box plots of univariate analysis showing the top m/z peaks contributing to class separation (log₂ fold change), between ovarian cancer and normal samples combined. Ten most significant and intense REIMS spectra peaks shown with P < 0.001, q < 0.001. Figure based on the following sample numbers: ovarian cancer n = 39, normal ovary n = 15, normal fallopian tube n = 15, normal peritoneum n = 14