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. 2022 Sep 21;36(11):2690–2704. doi: 10.1038/s41375-022-01697-9

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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. 5 — A Schematic representation of the experimental strategy, B coordinates and predictability coefficient for LSC+ vs. LSC− for CORE that are detected in either LSC+ or LSC− fractions. C Percentage of LSC− and LSC+ fraction for which CREAM algorithm detects the CORE-chr9 2014811-2032652, out of the 93 fractions sequenced, D IGV representation of the CORE-chr9 2014811-2032652 for primary AML LSC+ and LSC− fractions, E Percentage of LSC+ or LSC− primary AML fractions for which CRE part of the CORE of interest are accessible out of the 93 fractions sequenced.