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. 2014 Dec 11;6(12):117. doi: 10.1186/s13073-014-0117-z

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© Liu et al.; licensee BioMed Central. 2014

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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.

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The integrative model predicts expression alterations and TF activity changes. (A,B) The distribution of Spearman correlations of observed and predicted gene expression for all genes (A) and differentially expressed genes (B). The TF-only model (orange) is significantly better than random (blue, P < 2.2e-16), while the integrative model combining TFs, CNV and methylation (red) is significantly better than the TF only model (P < 2.2e-16). (C) Spearman correlations of observed and predicted expression changes for differentially expressed genes using random, TF-only, and the integrative model connecting TFs, CNV and methylation. (D) Candidate regulators associated with KIRC stage with effect size >0.5 and FDR <0.001.