Fig. 2

The integrative heatmap generated by the compEpiTools heatmapData and heatmapPlot functions. Heatmaps can easily be obtained incorporating any mixture of data and annotation tracks. Heatmap rows represent ROIs, while columns represent tracks profiled over those ROIs (or bins thereof). Data and annotation tracks might contain either quantitative (e.g. normalized reads counts) or categorical (e.g. presence/absence of a ChIP-seq peak) data. If available, the significance of associated data can be incorporated affecting colour brightness. In this example, generated as described in detail in the supplemental material, NIH Roadmap DNA methylation data where visualized together with ENCODE histone marks for a set of differentially methylated regions. ROIs were clustered based on the data available in all the displayed tracks including gene models annotations. The schema on the top of the figure depicts the workflow leading to the heatmap. A set of standard Bioconductor objects, listed in red, is the input for the heatmapData and heatmapPlot compEpiTools functions. The underlined text points to the key analysis steps automatically performed internally to the functions generating the heatmap, calling routines available in the same packages