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. 2017 Oct 18;7:13467. doi: 10.1038/s41598-017-13338-8

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© The Author(s) 2017

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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Performance of the algorithms on a real world data set validated with deep targeted sequencing data at single nuclei resolution from³. (a) Distribution of copy numbers across the targeted SNVs. (b–d) Co-clustering performance of PyClone, SciClone and Clomial, respectively.