The paper introduces the *ComplexHeatmap* package, which is designed to enhance the visualization of multidimensional genomic data through the use of parallel heatmaps and user-defined annotation graphics. The package overcomes limitations of traditional heatmaps by providing rich functionalities such as customizing heatmaps, arranging multiple parallel heatmaps, and including various types of annotation graphics. The authors demonstrate the effectiveness of *ComplexHeatmap* by applying it to four real-world datasets, including genomic alterations in lung adenocarcinoma, heterogeneity of mouse T-cells, and correlations between methylation, gene expression, and enhancers. The package is freely available from the Bioconductor project and is implemented in an object-oriented manner, offering a flexible and user-friendly API.The paper introduces the *ComplexHeatmap* package, which is designed to enhance the visualization of multidimensional genomic data through the use of parallel heatmaps and user-defined annotation graphics. The package overcomes limitations of traditional heatmaps by providing rich functionalities such as customizing heatmaps, arranging multiple parallel heatmaps, and including various types of annotation graphics. The authors demonstrate the effectiveness of *ComplexHeatmap* by applying it to four real-world datasets, including genomic alterations in lung adenocarcinoma, heterogeneity of mouse T-cells, and correlations between methylation, gene expression, and enhancers. The package is freely available from the Bioconductor project and is implemented in an object-oriented manner, offering a flexible and user-friendly API.