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. 2019 Mar 7;9:3877. doi: 10.1038/s41598-019-40629-z

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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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Overview of TACCO. TACCO was constructed using transcriptome data downloaded from several databases and provides GSEA results for gene sets from MSigDB, GO terms and KEGG pathways in 26 cancer types. In addition to GSEA, users can either identify DEGs/DEmiRNAs in TACCO or upload a gene set of interest. After a gene list is defined, users can construct a prediction model for pathological staging or clinical prognosis using the clinical or survival data in TACCO. For prognosis analysis, Kaplan-Meier survival plots with log-rank test p-values are provided for prediction results. Users can also perform a GO enrichment analysis, carry out KEGG pathway enrichment analysis²¹ and get the details of specific pathway by visiting external databases.