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. 2019 Aug 8;20:638. doi: 10.1186/s12864-019-5997-2

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© The Author(s). 2019

Open AccessThis 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. 3 — (a) Principle Component Analysis (PCA) by features extracted by HetEnc and its three encoding networks: AE, CombNet and CrossNet. RNA-seq and Microarray samples are combined for PCA analysis. Green and red dots represent RNA-seq and Microarray samples, respectively. (b) A sample-wise scatter plot of PC2 correlation analysis between Microarray and RNA-seq platform