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. 2019 Jul 18;9:10442. doi: 10.1038/s41598-019-46540-x

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© The Author(s) 2019

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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ROC curves of combining the final prediction scores with different types of disease related genes as negative sample sets. Curve in red represents the performance using curated disease genes from DisGeNET database as negative samples (AUC = 0.8536). Curve in blue represents the performance using known human drug target genes from DrugBank database as negative samples (AUC = 0.8122). And curve in green represents the performance using cancer driver genes as negative samples (AUC = 0.7132).