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. 2021 Mar 2;22:102. doi: 10.1186/s12859-021-04040-8

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© The Author(s) 2021

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. 4 — Classifying cancer cell lines into predicted LP-184 sensitivity groups based on gene expression levels. a This panel of box plots shows the differential expression of each of the top 20 correlated genes (10 positively correlated and 10 negatively correlated) with actual known LP-184 sensitivity in NCI-60 training data across the top 25 predicted sensitive and top 25 predicted resistant cell lines in the CCLE testing data. b This panel of box plots shows the differential expression of each of the 16 signature genes of LP-184 response across the top 25 predicted sensitive and top 25 predicted resistant cell lines in the CCLE testing data