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. 2019 Nov 21;26(8):3858–3875. doi: 10.1038/s41380-019-0579-x

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© The Author(s) 2019

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. 3 — Evaluation of the probability of health measured for Temperament and Character associations in the three phenotypic subnetworks using ANOVA statistics (p value < 1E−20), and T-test among the three subnetworks. The three networks, Creative-Reliable, Organized-Reliable, and Emotional-Unreliable, significantly differ from each other (p value < 1E−04) in their probability of well-being (a) and ill-being (d). b, e Evaluation of probability of health in Temperament and Character Sets and their relationships with SNP Sets using ANOVA statistics. b Well-being and e Ill-being evaluated for Temperament and Character Sets with respect to their profiles. c, f Surfaces representing the health function of the uncovered relationships between Temperament and Character Sets. The probability of health (z-axis; red high; green: low) was calculated based on the distribution of the status of subjects within each relationship, and the surface was plotted interpolating the relation domains. The order adopted for plotting relationships are calculated based on clustering shared subjects in Character (x-axis) and in Temperament (y-axis) Sets using Hypergeometric statistics (see “Method” section). (Close-located sets in an edge share more subjects than those located far away.) c Well-being surface. f Ill-being surface