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. 2020 Apr 23;20(Suppl 1):83. doi: 10.1186/s12866-020-01762-2

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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. 3 — Comparison of the mucosal metabolome between tumour tissues and normal tissues in CRC patients a. OPLS-DA scores plot of metabolome between tissue samples. Each point represents one sample with colour indicating tumour tissues (red) and adjacent normal tissues (blue). b. OPLS-DA model validation based on seven-fold cross-validation and 200 permutation tests. Y axis: the R2 (green; goodness of fit) and Q2 (blue; predictability) of the all newly calculated and the original OPLS-DA models. X axis: correlation between the original Y observation and the permuted Y observation. R²_inter and Q²_inter are the intercept of the linear regression of R² and Q² from random models against those from original model. The negative Q²_inter indicated the validity of the model. c. Heatmap visualizing the significantly differentially abundant metabolites between tumour (red) and normal tissues (blue) based on hierarchical clustering analysis. The rows demonstrate the metabolites and the columns display samples