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. 2020 Dec 3;12:110. doi: 10.1186/s13073-020-00804-8

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© The Author(s) 2020

Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 2 — Outcome-weighted integrative clustering of low-grade glioma (LGG) and kidney papillary cell carcinoma using survClust. a survClust identifies an IDH-mutant CDKN2A-loss subtype similar to IDH-wt tumors in terms of the aggressive clinical behavior. Top: Kaplan-Meier curves of the integrated survClust subtypes of LGG. Middle: Panelmap summarizing major association of mutational and clinical features of the integrated LGG subtypes. Bottom: Copy number profile for each of the integrated subtypes. b survClust identifies prognostic kidney papillary renal cell carcinoma (KIRP) subtypes