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. 2021 Jan 12;11:616. doi: 10.1038/s41598-020-79733-w

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© The Author(s) 2021

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 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/.

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Comparison of network utilization in RA-CH-1 and RA-CH-2. (a) HAC of 24 biomarkers in two RA strains. RA-CH-1 (8 samples) and RA-CH-2 (8 samples) belonged to two subgroups. (b) Activities of RA metabolic pathways according to comparisons between two RA strains. The activity scores (AS) for each pathway were calculated using the PAPi algorithm. PAPi calculates an AS for each metabolic pathway listed in the KEGG database based on the number of metabolites identified from each pathway and their relative abundances. Related pathways are grouped according to their cellular metabolism and only pathways with statistically significant differences in activity (p < 0.05 by ANOVA) are shown. (c) The pathway of Purine metabolism in RA.