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. 2024 May 8;24:373. doi: 10.1186/s12870-024-05086-5

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© The Author(s) 2024

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/. 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. 2 — K-means clustering of Camellia sinensis RNA-seq samples and comparative analysis of global vs. cluster-specific co-expression modules. (A) Pie chart showing the proportion of k-means clusters. (B) Scatter plots of t-SNE show the spatial distribution of all Camellia sinensis RNA-seq samples on Component 1 and Component 2. Different clusters are distinguished using different colors, while the same cluster remains consistent across A and B. (C) Similarity analysis of global and cluster-specific co-expression modules. The intensity of colors in the heatmap represents the magnitude of the Fowlkes-Mallows score (FMS). (D) Comparison of the gene-module consistency coefficient (GMC) of all genes between the global module and the cluster-specific module for each cluster