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. 2022 Oct 28;32(12):1047–1067. doi: 10.1038/s41422-022-00736-5

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© The Author(s) 2022

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. 2 — a Gene-wise mRNA-protein Spearman’s correlation in tumors. Red, pathways involving positively correlated genes; blue, pathways involving negatively correlated genes (Spearman’s correlation, FDR < 0.05). b The correlation of CNAs to mRNA (left) or protein abundance (right), with significant positive correlations in red and negative correlations in green (Spearman’s correlation, FDR < 0.05). Genes were sorted by chromosomal location on the x- and y-axes. c Cascading effects of CNAs and the overlap between cis events via the transcriptome and proteome analyses (Spearman’s correlation, FDR < 0.05). d Prioritized cis effect CNA drivers were used for pathway enrichment analysis in ConsensusPathDB. e Venn diagram showing the CAGs with significant CNA cis effects via multi-omics data analyses (Spearman’s correlation, FDR < 0.1). f Genes with cascading copy number cis regulation of their cognate mRNA, protein, and phosphoprotein levels. Shapes indicate the cis effects across the indicated datasets.