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. 2020 Jul 28;18:286. doi: 10.1186/s12967-020-02454-1

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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. 6 — Selection of the optimal survival-related AS events in TNBC used for construction of the final prediction model by using Upset plot and LASSO Cox regression based on OS and PFS. a Upset plots of the intersections between the seven types of survival-related AS events. b LASSO coefficient profiles of the candidate survival-related AS events. A coefficient profile plot was produced against the logλ sequence. LASSO coefficient profiles of the candidate survival-related AS events. c Dotted vertical lines were drawn at the optimal values by using the minimum criteria. The upper parts and the bottom are related to OS and PFS, respectively. AS alternative splicing, TNBC triple negative breast cancer, LASSO least absolute shrinkage and selection operator, OS overall survival, PFS progression-free survival