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. 2019 May 2;20:223. doi: 10.1186/s12859-019-2840-3

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© The Author(s). 2019

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. 1 — Correction of technical variability. a The clustered dendrogram of samples before applying CQN to remove technical variability. Many highly related samples are not clustered closely. b The clustered dendrogram of samples after applying CQN to remove technical variability. More related samples are clustered together, suggesting that the application of CQN in the analysis is very effective