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. 2022 Jun 30;54(7):963–975. doi: 10.1038/s41588-022-01100-4

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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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Extended Data Fig. 5 — a. Log2 copy-number ratios for each chromosome arm in iCMS2_MSS (n = 363), iCMS3_MSS (n = 189) and iCMS3_MSI (n = 107) from TCGA and SG-Bulk datasets. P-values for pairwise comparisons are by two-sided Wilcoxon rank-sum test; overall p-value is by Kruskal-Wallis test. Scatterplot of proportion of TCGA and SG-Bulk samples with mutations in 333 CRC-associated genes, in b. MSS (n = 519) vs MSI (n = 101) and c. iCMS3_MSS (n = 181) vs iCMS3_MSI (n = 99) (right). Dot size corresponds to q-value by Fisher’s exact test with Benjamini-Hochberg correction. Only genes with q-value <0.05 and proportion mutated > 0.5 are labelled. (d) Heatmap of differentially methylated CpG sites (n = 978) between iCMS2 and iCMS3 subtypes in 176 TCGA samples.