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. 2018 Sep 10;8:13513. doi: 10.1038/s41598-018-31902-8

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© The Author(s) 2018

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

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Comparison of R values for different competitors against BI, the most accurate method in our study. For each competitor, we plot the distribution of all R values as a box plot. Each box covers the values within boundaries X,Y. Competitors are sorted according to their median deviations to BI values. The best competitors are ABI and CHD, which have an absolute difference in R values of 0.01–0.02 for the majority of network instances. Moreover, their maximum deviation is between 0.05–0.08. Other competitors, including AB and DEG, have much higher deviations, with a difference of 0.5 as the maximum case, which essentially renders them useless for accurate estimations of network robustness.