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. 2018 Nov 26;19:839. doi: 10.1186/s12864-018-5227-3

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© The Author(s). 2018

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 — Dimension reduction of features extracted from xenomiRs and non-xenomiRs. Dimension reduction of features extracted from xenomiRs and non-xenomiRs was performed using LDA to show the differences between them. Overall, the xenomiRs and non-xenomiRs could be separated with partial overlap in the middle, and the distribution of xenomiRs is more compact than that of non-xenomiRs