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. 2017 May 23;18:270. doi: 10.1186/s12859-017-1647-3

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© The Author(s) 2017

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 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.

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Fig. 6 — ROC curves from different conditions. The DTWscore method was applied to two different scRNA-seq time series data sets. The algorithm’s performance was assessed by their sensitivity, illustrated in the ROC curves, which demonstrate good performance in all cases. The black curve represents condition 1 simulated by the biological functions f ₂(t) and f ₃(t). The red curve represents condition 2 simulated by the biological functions f ₂(t) and f ₄(t)