Fig. 2

Inferring functional epigenetic alterations through integration of DNA methylation and gene expression data. A Schema depicting the integration of DNA methylation and RNA-Seq data using the ELMER algorithm. Values indicate the number of significant common hyper- or hypomethylated CpGs used in the context of the 450 K arrays and the number of genes expressed in the TCGA-COAD RNA-seq dataset. B Barplot illustrating the number of significant gene expression–correlating hyper- or hypomethylated CpGs associated with promoter regions with an absolute Pearson’s correlation > 0.5. C Barplot displaying gene ontology enrichment analyses of the significant gene expression–correlating hyper- or hypomethylated CpGs. Genes with a consistent correlation with DNA methylation were used for enrichment calculation versus the background dataset (16,838). Colour range denotes the odds ratio of the represented ontology, while bar size represents the significance of these enrichments (−Log10 adj. p value) as calculated with the GORILLA tool. D Graph illustrating the gene-CpG promoter network associated with significant gene expression–correlating hyper- (red) or hypomethylated (blue) CpGs in CRC samples. Genes that are down- or upregulated in CRC samples cells as compared to healthy controls are shown in blue or orange, respectively. E Scatter plots displaying the correlations between DNA methylation and gene expression for the genes MAL (top) and MDFI (bottom). Control and CRC samples are coloured according to their CIMP status, and the resulting significant correlation (p value < 0.001) is indicated for each gene comparison