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. 2021 Feb 22;12:1226. doi: 10.1038/s41467-021-21254-9

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© The Author(s) 2021

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. 4 — Top: Boxplots of Sample to Sample Correlation between GDC and TCGA by Project. n = 79/427/1202/309/45/328/48/171/170/546/89/603/321/145/525/423/573/550/86/265/182/186/548/105/265/472/404/156/564/121/199/56/80 biologically independent samples for projects ACC/BLCA/BRCA/CESC/CHOL/COAD/DLBC/ESCA/GBM/HNSC/KICH/KIRC/KIRP/LAML/LGG/LIHC/LUAD/LUSC/MESO/OV/PAAD/PCPG/PRAD/READ/SARC/SKCM/STAD/TGCT/THCA/THYM/UCEC/UCS/UVM, respectively. Bottom: Combined Boxplots and Density Plots of Gene to Gene Correlation between GDC and TCGA. All genes are categorized by four GDC groups (Q1–4) based on their average expression values. Mean and standard deviation of gene to gene Spearman’s correlations are calculated by these four groups.