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. 2022 Mar 3;13:847634. doi: 10.3389/fmicb.2022.847634

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Copyright © 2022 Chen, Yang, Dai, Yi, Peng, Li and Chen.

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) and the copyright owner(s) 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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Identification of biomarkers and iPath analysis in PA-R_SCF. (A) The PCA analysis between PA-S and PA-R_SCF. Each dot represents the technique replicas in the plot. (B) S-plot generated from OPLS-DA. Triangle represents individual metabolite, where potential biomarkers are highlighted with blue, which is greater than or equal to 0.05 and 0.5 for absolute value of covariance p [1] and correlation p(corr) [1], respectively. (C) The scatter plot of biomarkers in data (B). (D) iPath analysis. Blue and yellow lines represent decreased and increased metabolisms, respectively. Out of 49 significant metabolites (p < 0.05), 46 were submitted to the online website (https://pathways.embl.de).