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. 2021 Dec 13;8:761841. doi: 10.3389/fmolb.2021.761841

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Copyright © 2021 Hu, Zhang, Li, Liu, Ao, Li, Zeng and Li.

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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The weighted gene co-expression network analysis (WGCNA) algorithm was applied to explore the most correlated gene modules. The sample dendrogram and trait heatmaps of the GPL96 database (A) and GPL570 database (B). The optimum soft threshold power was determined based on the scale independence plot and mean connectivity plot in the GPL570 (C and D) and GPL96 databases (E and F). The gene clustering dendrogram was constructed based on dissimilarity, and the related gene modules were merged with the dynamic tree cut method by hierarchical clustering in the GPL570 (G–I) and GPL96 databases (J–L).