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. 2021 Jul 1;11:13713. doi: 10.1038/s41598-021-93250-4

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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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Clustering by pretty heatmaps and PCA. (a) A heatmap hierarchical clustering based on the top 40 DEGs. (b) The 2D coordinates of each sample profile based on the scores of the first two PCs—PC1 and PC2 in PCA analysis. (c) The 2D coordinates of each sample profile based on the scores of PC1 and PC3. (d) Contributors of each PC.