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. 2020 Mar 12;20:199. doi: 10.1186/s12885-020-6676-z

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© The Author(s). 2020

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. 2 — Gene dendrogram and module cluster for Histopathological feature. a Clustering dendrogram of genes, with dissimilarity based on topological overlap, is merged with assigned module colors and the original module colors. b The correlation of Module-clinical traits. Each row corresponds to a module; each column corresponds to a clinical trait feature. Each cell contains the test statistic value and its corresponding p value from the linear mixed-effects model. Network of eigengene represents the relationships among the modules and the histological traits. c There are total 6 Module memberships vs. gene significance cluster for histopathology trait. Module membership vs gene significance is correlating to thyroid nodule histopathological status. Panel d shows a hierarchical clustering dendrogram of the eigengenes in which the dissimilarity of eigengenes (EI, EJ is given by 1 − cor(EI, EJ). The heatmap in panel (e) shows the eigengene adjacency (AI J = (1 + cor (EI, EJ))/2)