HCP (HeatmapCovariatePlot) provides a simple high level application programming interface (API) to design elaborated visualizations in a modular fashion. The user can select which elements to include, covariate row annotations and/or heatmaps, by invoking the AddCovariateRow or the AddHeatmap methods. Elements can be vertically stacked and also grouped in functionally related sub-blocks encapsulated by the AddSubBlock method to adjust the figure layout. The plotting options in HCP are chosen sensibly to create production-quality out-of-the-box visualizations in most use-case. HCP features several plotting options to adjust the plot aesthetics to cater for the user preferences in terms of colormaps, labelling, legends and layouts (margins and positions). HCP ease-of-use and rapidity enables the users to iterate through multiple visualization alternatives while focusing on the message conveyed by the data rather than the technicalities involved in generating the plot.
Salvucci, Manuela, and Jochen Prehn. “HCP: A Matlab Package to Create Beautiful Heatmaps with Richly Annotated Covariates.” Journal of Open Source Software, vol. 4, no. 38, The Open Journal, June 2019, p. 1291, doi:10.21105/joss.01291.
Salvucci, Manuela, and Jochen H. M. Prehn. HCP: A Matlab Package to Create Beautiful Heatmaps with Richly Annotated Covariates. Zenodo, 2019, doi:10.5281/zenodo.3242593.