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. 2021 Aug 21;158:31. doi: 10.1186/s41065-021-00196-8

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© The Author(s) 2021

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. 4 — Dynamic co-expression module identification during NAFLD progression. A Sample dendrogram and clinical trait heatmap. B Analysis of scale independence for various soft-thresholding powers. C Analysis of mean connectivity for various soft-thresholding powers. D Modules were enriched by co-expression network analysis. The activities of modules at different stage during NAFLD progression were calculated by NES from GSEA, and the modules enriched in each stage with adjust P value < 0.05 were shown in heatmap. E Module-node relationships were assessed by WGCNA. Nine common node genes identified above were selected to evaluate the correlation with Modules