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. 2018 Jun 27;8:9743. doi: 10.1038/s41598-018-28066-w

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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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Biomarker discovery scheme. (a) Input matrices are multi-dimensional pharmacological, genomic, transcriptomic, and tumour-type data aligned by cell lines. (b) The joint non-negative matrix factorization (JNMF) method detects multi-dimensional co-modules. Each module shows the co-occurrence between genetic (red) and pharmacological (blue) features. (c) Pathway analysis provides causal relationship based on biological knowledge in co-module features. (d) Gene signature analysis clarifies the relationship between pathway activation and sensitivity to compounds.