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. 2023 Jun 21;14:3675. doi: 10.1038/s41467-023-39173-2

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© The Author(s) 2023

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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 6 — a Schematic of CN identification. CN was defined by its center cell and the 20 nearest neighbor cells. b Identification of 15 distinct CNs based on the 17 original CTs and their respective abundances (column scaled) within each CN. c Representative Voronoi diagrams of CNs (upper panels) and corresponding IMC images (lower panels) in the normal and inflammatory region. d Dot plots showing the abundance of selected CNs (CN4, CN5, CN6, CN8, CN10, CN14) between normal and UC samples (Normal, n = 19; UC, n = 33 from two independent experiments). Dashed black line labeling mean value of each group and statistics were performed with two-sided Wilcoxon rank-sum tests. Exact P values were provided in the plot and Source Data file. e Schematic of the tensor decomposition analysis and decomposition results of selected modules for normal and UC groups. Weight of the line connecting CN and CT modules indicating interaction potentials between each pair.