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. 2023 Jun 19;20(7):1037–1047. doi: 10.1038/s41592-023-01903-1

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© The Author(s) 2023

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. 10 — a, PCA eigenvalues from GAM and Hi-C for mouse chromosome 1. b, Correlation heatmap for GAM and Hi-C eigenvalues. A small subset of windows assigned to the A compartment by GAM (positive eigenvalues) are assigned to the B compartment by Hi-C (negative eigenvalues). Value histograms indicate that Hi-C eigenvalues are clearly bimodal distributed while GAM finds an increased number of eigenvalues in the transition zone. c, Agreement between GAM and Hi-C compartment calls for GAM-preferred (left), Hi-C preferred (middle) and common (right) regions. d, Absolute number (left) and enrichment over random background (right) of compartment combinations observed in the sets of Hi-C-specific contacts (blue) and GAM-specific contacts (red). Compartment definitions of 1Mb resolution were obtained from Hi-C data (top) or GAM data (bottom); * P < 0.05, ** P < 0.01, empirical test, n = 500 contact permutations.