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. 2020 Sep 3;21:98. doi: 10.1186/s12863-020-00907-6

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© The Author(s) 2020

Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.

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Fig. 3 — Pairwise correlation between editing levels and gene expression levels (Ribo-seq RPKM) in six samples used in this study. a Heatmap showing the Spearman correlation coefficient between editing levels and gene expression levels. b Numbers of significantly correlated (multiple testing corrected FDR < 0.05) genes of each C-to-U editing site. The editing sites are classified into three classes based on the numbers of positively and negatively correlated genes. c Box-and-whiskers showing the editing levels of three classes of editing sites. P-values are calculated by Wilcoxon rank sum tests. d Box-and-whiskers showing the standard deviation of editing levels of three classes of editing sites. e Barplot showing the fractions of nonsynonymous editing sites among three classes of sites