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. 2019 Mar 13;9:4366. doi: 10.1038/s41598-019-40579-6

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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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Pathway analysis of transcriptomics and proteomics data. (A) The transcriptomics data were submitted to pathway analysis using the Ingenuity Pathway Analysis (IPA) software. The heatmap shows the canonical pathways associated with the 3 clusters of DEGs (refer to Supplementary Fig. S1). Values are normalized scores of the -log(p-value) with P < 0.00001 for at least one cluster. (B) Pathway analysis of the proteomics data. Refer to Supplementary Fig. S3 for an overview of the proteomics results. The heatmap shows the canonical pathways associated with the various treatments. STS and LPS were used as positive controls for cell death and cell activation, respectively. Values are scores of the -log(p-value) with P < 0.00001 for at least one treatment. Data displayed in panel A and B were analyzed through the use of IPA (QIAGEN Inc., www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis).