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. 2020 May 20;37(7):1623–1635. doi: 10.1007/s10815-020-01802-w

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© The Author(s) 2020

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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Fig. 2 — Differential expression of genes among randomly matched younger (n = 10) vs older (n = 10) patients. a Genes displaying over 1 degree of differential expression with statistical significance of < 0.05 were included in the feature list (Sup. Fig. 1). Unfiltered set of differential gene expression is provided in Sup. Table 3. Feature list genes were hierarchically clustered and normalized via average linkage, Euclidean point distance metric as defaults (Sup. Table 4). b Average expression among all samples for feature list is summarized. each heat map cell contains the average differential expression among all patient comparison samples. c Chart depicting sample demographics for significant values (standard error of the mean) such as AMH, FSH, E2, and age of patients [22]