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. 2020 Feb 18;10:2860. doi: 10.1038/s41598-020-59529-8

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© The Author(s) 2020

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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Pearson correlation analysis and the power of the relative abundance of microbiomes and metabolites to discriminate CRC from healthy controls. (A) Pearson correlation analysis was performed to investigate the association between metagenomic and metabolomic analysis data. The y-axis represents the result of the metagenomic analysis, and the x-axis represents metabolic biomarkers, both obtained through statistical comparisons. Each square shows the correlation coefficient value. Red squares indicate a positive correlation and blue squares indicate a negative correlation between microbial and metabolite abundances. (B) Receiver operating characteristic (ROC) curves for the markers leucine, butanoic acid, isoleucine, succinic acid, Bifidobacterium, Lactobacillus, Faecalibacterium, Pseudomonas, and Methylobacterium based on their ability to discriminate CRC patients from healthy controls. The red line indicates the model based on metagenomics analysis, the blue line indicates the model based on metabolomics analysis, and the green line indicates the model based on combination of metabolomics and metagenomics data. CRC, colorectal cancer.