HCP: A Matlab package to create beautiful heatmaps with richly annotated covariates
Manuela Salvucci, Jochen H.M. Prehn · The Journal of Open Source Software · 2019
A heatmap is a graphical technique that maps 2-dimensional matrices of numerical values to colors to provide an immediate and intuitive visualization of the underlying patterns (Eisen, Spellman, Brown, & Botstein, 1998).Heatmaps are often used in conjunction with cluster analysis to re-order observations and/or features by similarity and thus, rendering common and distinct patterns more apparent.When generating these visualizations, it is often of interest to interpret the underlying patterns in the context of other data sources.In the field of bioinformatics, heatmaps are frequently used to visualize high-throughput and high-dimensional datasets, such as those derived from profiling biological samples with -omic technologies (whole genome sequencing, transcriptomics and proteomics).Often, biological samples (for example, patient tumour samples) are characterized at multiple -omic level and it is of interest to contrast and compare patterns captured at the different molecular layers along with their associations with other observable features (covariates).The concurrent display of continuous or categorical covariates enriches the visualization with additional information such as group membership.